library.bib

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@Book{Ketelaar2009,
  author    = {{(Gini) Ketelaar}, V. B. H.},
  title     = {{Satellite Radar Interferometry}},
  date      = {2009},
  volume    = {14},
  series    = {Remote Sensing and Digital Image Processing},
  publisher = {Springer Netherlands},
  isbn      = {978-1-4020-9427-9},
  pages     = {243},
  doi       = {10.1007/978-1-4020-9428-6},
  file      = {:home/baffelli/Library/(Gini) Ketelaar - 2009 - Satellite Radar Interferometry.pdf:pdf},
}

@Article{AlvarezLopez2012,
  author       = {{{\'{A}}lvarez Lopez}, Y. and Garc{\'{a}}, C. and V{\'{a}}zquez, C. and Ver-Hoeye, S. and Las-Heras, F.},
  title        = {{Frequency scanning based radar system}},
  journaltitle = {Progress in Electromagnetics Research},
  date         = {2012},
  volume       = {132},
  pages        = {275--296},
  issn         = {10704698},
  doi          = {10.2528/pier12071811},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84867522329{\&}partnerID=tZOtx3y1},
  abstract     = {A novel imaging technique based on a frequency scanning antenna array is presented. The method is conceived to provide angular information in range-based radar systems which do not allow mechanical or electronic beam steering. The beam steering is changed with frequency, which requires a novel scattered field data processing scheme/algorithm to recover the SAR image. System features, advantages and limitations are discussed, presenting simulation and measurement results, which show the system capabilities to resolve the range and angular position of the objects.},
  file         = {:home/baffelli/Library/{'{A}}lvarez Lopez et al. - 2012 - Frequency scanning based radar system.pdf:pdf},
}

@Misc{Lecture2008,
  Title                    = {{Kalman Filtering , EKF , Unscented KF , Smoother , EM Kalman Filtering}},

  Author                   = {Abbeel, Pieter},

  Booktitle                = {ReCALL},
  Date                     = {2008},
  File                     = {:home/baffelli/Library/Abbeel - 2008 - Kalman Filtering , EKF , Unscented KF , Smoother , EM Kalman Filtering.pdf:pdf},
  Pages                    = {1--4}
}

@Article{Agram2015,
  author       = {Agram, P. S. and Simons, M.},
  title        = {{A noise model for {InSAR} time series}},
  journaltitle = {Journal of Geophysical Research : Solid Earth},
  date         = {2015},
  pages        = {1--20},
  doi          = {10.1002/2014JB011271.1},
  file         = {:home/baffelli/Library/Agram, Simons - 2015 - A noise model for InSAR time series.pdf:pdf},
  keywords     = {10.1002/2014JB011271 and InSAR,inteferometry,noise budget,radar,time series},
}

@InProceedings{Aguasca2004,
  author       = {A. Aguasca and A. Broquetas and J.J. Mallorque and X. Fabregas},
  title        = {A solid state {L} to {X}-band flexible ground-based {SAR} system for continuous monitoring applications},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2004},
  volume       = {2},
  publisher    = {{IEEE}},
  isbn         = {0-7803-8742-2},
  pages        = {757--760},
  doi          = {10.1109/IGARSS.2004.1368512},
  url          = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=1368512{\%}5Cnhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1368512},
  abstract     = {Continuous terrain fast changes monitoring is difficult to implement via airborne/satellite SAR systems, mainly due to the lack of flexibility and low revisiting times. Other SAR approaches based on small and simple ground-based systems, easy to deploy wherever are needed, must be considered. Transportability, low cost, and ruggedized structure are the main constrains, but the required resolution and performances have to be preserved. An experimental, short to medium range, ground-based, with optional polarimetric capability, Synthetic Aperture Radar (SAR) will be presented. First results of an experimental X-band SAR with a 100 MHz bandwidth, with 20 dBm of radiated power in differential interferometry operation will be shown},
  file         = {:home/baffelli/Library/Aguasca et al. - 2004 - A solid state L to X-band flexible ground-based SAR system for continuous monitoring applications.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {-sar,building deformation,differential interferometry,ground-based,hardware,interferometry,subsidence},
}

@Article{Ainsworth2006a,
  author        = {T.L. Ainsworth and L. Ferro-Famil and Jong-Sen Lee},
  title         = {Orientation angle preserving a posteriori polarimetric {SAR} calibration},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2006},
  date          = {2006-04},
  volume        = {44},
  month         = {apr},
  pages         = {994--1003},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2005.862508},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1610834},
  file          = {:home/baffelli/Library/Ainsworth, Ferro-Famil, Jong-Sen Lee - 2006 - Orientation angle preserving a posteriori polarimetric SAR calibration.pdf:pdf},
  isbn          = {2011049008},
  keywords      = {Calibration,Costs,Covariance matrix,Data analysis,Equations,Parameter estimation,Radar polarimetry,Radar scattering,SAR data analysis,Soil moisture,a posteriori polarimetric SAR calibration,anechoic chamber data,backscatter,calibration,covariance matrices,geophysical techniques,orientation angle,polarimetric channels,polarimetric covariance matrix,polarimetric distortion,polarimetric fidelity,polarimetric synthetic aperture radar,radar polarimetry,remote sensing by radar,scattering reciprocity,synthetic aperture radar},
  mendeley-tags = {Costs,Covariance matrix,Data analysis,Equations,Parameter estimation,Radar scattering,SAR data analysis,Soil moisture,a posteriori polarimetric SAR calibration,anechoic chamber data,backscatter,calibration,covariance matrices,geophysical techniques,orientation angle,polarimetric channels,polarimetric covariance matrix,polarimetric distortion,polarimetric fidelity,polarimetric synthetic aperture radar,radar polarimetry,remote sensing by radar,scattering reciprocity,synthetic aperture radar},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Aitken1936,
  author       = {Aitken, A. C.},
  title        = {{IV.---On Least Squares and Linear Combination of Observations.}},
  journaltitle = {Proceedings of the Royal Society of Edinburgh},
  date         = {1936},
  volume       = {55},
  pages        = {42--48},
  issn         = {0370-1646},
  doi          = {10.1017/S0370164600014346},
  url          = {http://www.journals.cambridge.org/abstract{\_}S0370164600014346},
  abstract     = {{\textless}p{\textgreater}In a series of papers W. F. Sheppard (1912, 1914) has considered the approximate representation of equidistant, equally weighted, and uncorrelated observations under the following assumptions:–{\textless}/p{\textgreater}},
}

@Article{Akaike1974,
  author       = {H. Akaike},
  title        = {A new look at the statistical model identification},
  journal      = {{IEEE} Transactions on Automatic Control},
  journaltitle = {IEEE Transactions on Automatic Control},
  year         = {1974},
  date         = {1974},
  volume       = {19},
  month        = {dec},
  pages        = {716--723},
  issn         = {15582523},
  doi          = {10.1109/tac.1974.1100705},
  abstract     = {The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.},
  file         = {:home/baffelli/Library/Akaike - 1974 - A New Look at the Statistical Model Identification.pdf:pdf},
  isbn         = {0018-9286 VO - 19},
  pmid         = {1100705},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Akbari2013,
  author        = {Akbari, Vahid and Anfinsen, Stian N. and Doulgeris, Anthony P. and Eltoft, Torbjorn},
  title         = {{The Hotelling-Lawley trace statistic for change detection in polarimetric SAR data under the complex Wishart distribution}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {2013-07},
  isbn          = {978-1-4799-1114-1},
  pages         = {4162--4165},
  doi           = {10.1109/IGARSS.2013.6723750},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6723750},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Approximation methods,Data models,Fisher-Snedecor distribution,Hotelling-Lawley trace,Hotelling-Lawley trace statistic,PolSAR data sets,Sociology,Sparse matrices,change detection,complex Wishart distribution,constant false alarm rate change detector,covariance matrices,likelihood ratio test statistic,multilook complex covariance matrix data,polarimetric SAR data,radar polarimetry,remote sensing,synthetic aperture radar,test statistic,unsupervised change detection},
  mendeley-tags = {Approximation methods,Data models,Fisher-Snedecor distribution,Hotelling-Lawley trace,Hotelling-Lawley trace statistic,PolSAR data sets,Sociology,Sparse matrices,change detection,complex Wishart distribution,constant false alarm rate change detector,covariance matrices,likelihood ratio test statistic,multilook complex covariance matrix data,polarimetric SAR data,radar polarimetry,remote sensing,synthetic aperture radar,test statistic,unsupervised change detection},
}

@Article{Allen2007,
  Title                    = {{Synthetic-aperture radar images polar ice-sheet bed}},
  Author                   = {Allen, Chris},
  Pages                    = {3--5},

  Date                     = {2007},
  Doi                      = {10.1117/2.1200706.0780},
  File                     = {:home/baffelli/Library/Allen - 2007 - Synthetic-aperture radar images polar ice-sheet bed.pdf:pdf},
  ISSN                     = {18182259},
  Journaltitle             = {SPIE Newsroom},
  Url                      = {http://www.spie.org/x14509.xml}
}

@Article{Allstadt2015,
  author       = {K. E. Allstadt and D. E. Shean and A. Campbell and M. Fahnestock and S. D. Malone},
  title        = {Observations of seasonal and diurnal glacier velocities at {Mount Rainier}, {Washington}, using terrestrial radar interferometry},
  journal      = {The Cryosphere},
  journaltitle = {Cryosphere},
  year         = {2015},
  date         = {2015},
  volume       = {9},
  month        = {dec},
  pages        = {2219--2235},
  issn         = {19940424},
  doi          = {10.5194/tc-9-2219-2015},
  abstract     = {We present spatially continuous velocity maps using repeat terrestrial radar interferometry (TRI) measurements to examine seasonal and diurnal dynamics of alpine glaciers at Mount Rainier, Washington. We show that the Nisqually and Emmons glaciers have small slope-parallel velocities near the summit (−1), high velocities over their upper and central regions (1.0–1.5 m day−1), and stagnant debris-covered regions near the terminus (−1). Velocity uncertainties are as low as ±0.02–0.08 m day−1. We document a large seasonal velocity decrease of 0.2–0.7 m day−1 (−25 to −50 {\%}) from July to November for most of the Nisqually glacier, excluding the icefall, suggesting significant seasonal subglacial water storage under most of the glacier. We did not detect diurnal variability above the noise level. Preliminary 2-D ice flow modeling using TRI velocities suggests that sliding accounts for roughly 91 and 99 {\%} of the July velocity field for the Emmons and Nisqually glaciers, respectively. We validate our observations against recent in situ velocity measurements and examine the long-term evolution of Nisqually glacier dynamics through comparisons with historical velocity data. This study shows that repeat TRI measurements with {\textgreater} 10 km range can be used to investigate spatial and temporal variability of alpine glacier dynamics over large areas, including hazardous and inaccessible areas.},
  publisher    = {Copernicus {GmbH}},
}

@InProceedings{Alonso-Gonzalez2011,
  author        = {Alonso-Gonzalez, A.},
  title         = {Binary partition tree as a polarimetric SAR data representation in the space-time domain},
  date          = {2011-07},
  isbn          = {9781457710056},
  pages         = {3819--3822},
  doi           = {10.1109/IGARSS.2011.6050063},
  url           = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=6050063},
  abstract      = {The aim of this paper is to present a Polarimetric Synthetic Aperture Radar data processing technique on the space-time domain. This approach is based on a Binary Partition Tree (BPT), which is a region-based and multi-scale data represen- tation. Results with series of RADARSAT-2 real data are an- alyzed from the point of view of speckle filtering and change detection applications, to illustrate the capabilities to detect and preserve spatial and temporal contours. Index},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Binary Partition Tree (BPT),Change detection,Covariance matrix,Entropy,Filtering,RADARSAT-2 real data,SAR,SAR Polarimetry,SAR polarimetry,Scattering,Segmentation,Speckle,binary partition tree,change detection,change detection method,feature extraction,geophysical image processing,geophysical techniques,image representation,image segmentation,multiscale data representation,polarimetric SAR data representation,polarimetric synthetic aperture radar data process,radar polarimetry,region-based data representation,remote sensing by radar,segmentation,space-time domain,spatial contour,speckle filtering method,synthetic aperture radar,temporal contour,urban areas},
  mendeley-tags = {Covariance matrix,Entropy,Filtering,RADARSAT-2 real data,SAR,SAR polarimetry,Scattering,Speckle,binary partition tree,change detection,change detection method,feature extraction,geophysical image processing,geophysical techniques,image representation,image segmentation,multiscale data representation,polarimetric SAR data representation,polarimetric synthetic aperture radar data process,radar polarimetry,region-based data representation,remote sensing by radar,segmentation,space-time domain,spatial contour,speckle filtering method,synthetic aperture radar,temporal contour,urban areas},
}

@Article{Alonso-Gonzalez2014,
  author        = {Alonso-Gonzalez, Alberto and Lopez-Martinez, Carlos and Salembier, Philippe},
  title         = {{PolSAR Time Series Processing With Binary Partition Trees}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2014-06},
  volume        = {52},
  pages         = {3553--3567},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2013.2273664},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6595582},
  abstract      = {This paper deals with the processing of polarimetric synthetic aperture radar (SAR) time series. Different approaches to deal with the temporal dimension of the data are considered, which are derived from different target characterizations in this dimension. These approaches are the basis for defining two different binary partition tree (BPT) structures that are employed for SAR polarimetry (PolSAR) data processing. Once constructed, the BPT is processed by a tree pruning, producing a set of spatiotemporal homogeneous regions, and estimating the polarimetric response within them. It is demonstrated that the proposed technique preserves the PolSAR information in the spatial and the temporal domains without introducing bias nor distortion. Additionally, the evolution of the data in the temporal dimension is also analyzed, and techniques to obtain BPT-based scene change maps are defined. Finally, the proposed techniques are employed to process two real RADARSAT-2 data sets.},
  keywords      = {BPT structures,BPT-based scene change maps,Binary partition tree (BPT),Covariance matrices,Data models,PolSAR data processing,PolSAR information,PolSAR time series processing,RADARSAT-2 data sets,Radar polarimetry,SAR polarimetry data processing,Speckle,Synthetic aperture radar,Time series analysis,binary partition trees,change detection,covariance matrices,data temporal dimension,radar polarimetry,remote sensing by radar,segmentation,spatiotemporal homogeneous regions,synthetic aperture radar,synthetic aperture radar (SAR) polarimetry,target characterizations,time series,tree pruning},
  mendeley-tags = {BPT structures,BPT-based scene change maps,Binary partition tree (BPT),Data models,PolSAR data processing,PolSAR information,PolSAR time series processing,RADARSAT-2 data sets,SAR polarimetry data processing,Speckle,Time series analysis,binary partition trees,change detection,covariance matrices,data temporal dimension,radar polarimetry,remote sensing by radar,segmentation,spatiotemporal homogeneous regions,synthetic aperture radar,synthetic aperture radar (SAR) polarimetry,target characterizations,time series,tree pruning},
}

@Article{Alvarez2013,
  author       = {Alvarez, Y and Camblor, Ren{\'{e}} and Garcia, C and Laviada, Jaime and Vazquez, C and Ver-Hoeye, S and Hotopan, George and Fernandez, M and Hadarig, Andreea and Arboleya, Ana and Las-Heras, F},
  title        = {{Submillimeter-Wave Frequency Scanning System for Imaging Applications}},
  journaltitle = {IEEE Transactions on Antennas and Propagation},
  date         = {2013},
  volume       = {61},
  pages        = {5689--5696},
  issn         = {0018-926X},
  doi          = {10.1109/TAP.2013.2275747},
  abstract     = {A new submillimeter-wave imaging system based on the frequency scanning concept is presented. Using significantly less information than beam-steering techniques, frequency scanning-based imaging systems are able to provide angular information in range-based radar systems which do not allow mechanical or electronic beam steering. Several strategies have been adopted to overcome the low dynamic range due to the propagation losses and non-specular reflection on the object-under-test. Moreover, the system is not only capable of detecting the placement of the objects, but also their profile. In this sense, an imaging application showing the system capabilities for the detection of objects concealed under clothes is presented. Results using 1-D FSAA allowing profile imaging are shown, proving the validity of the proposed system.},
  file         = {:home/baffelli/Library/Alvarez et al. - 2013 - Submillimeter-Wave Frequency Scanning System for Imaging Applications.pdf:pdf},
  isbn         = {0018-926X VO - 61},
  keywords     = {1-D FSAA,Antennas,Bandwidth,Beam steering,Frequency scanning antenna array (FSAA),Image resolution,Imaging,Radar imaging,Torso,angular information,antenna arrays,frequency scanning-based imaging systems,inverse methods,inverse problems,nonspecular reflection,object-under-test,profile imaging,propagation losses,range-based radar systems,submillimeter wave antennas,submillimeter wave imaging,submillimeter-wave imaging system,submillimetre wave antennas,submillimetre wave imaging},
}

@InProceedings{Anfinsen2007,
  author    = {Anfinsen, Stian Normann and Jenssen, Robert and Eltoft, Torbj{\o}rn},
  title     = {{Spectral clustering of polarimetric SAR data with Wishart-derived distance measures}},
  booktitle = {Proceedings of PolInSAR},
  date      = {2007},
  volume    = {7},
  series    = {Proc. POLinSAR.},
}

@Article{Attema1991,
  author       = {Attema, Evert P W},
  title        = {{The Active Microwave Instrument On-Board the ERS-1 Satellite}},
  journaltitle = {Proceedings of the IEEE},
  date         = {1991},
  volume       = {79},
  pages        = {791--799},
  issn         = {15582256},
  doi          = {10.1109/5.90158},
  abstract     = {The Active Microwave Instrument (AMI), a combination of a {\textless}e1{\textgreater}C {\textless}/e1{\textgreater}-band (5.3 GHz), VV polarization, synthetic aperture radar (SAR) and a wind scatterometer is described. AMI is being carried on the first European Remote Sensing Satellite, ERS-1, which is also described. AMI's primary geophysical data products are ocean surface wind speed and direction, ocean wave length and direction, and high-resolution radar mapping of land, ocean, ice, and coastal zones. The ERS-1 payload also includes a radar altimeter, an along-track scanning infrared radiometer, a microwave sounder, a precision range and range rate measuring equipment, and a laser retroreflector. ERS-1 will be in a polar orbit for global mapping. Prelaunch testing has shown that the quality of the AMI data products meets the mission objectives},
  annotation   = {NULL},
  isbn         = {0018-9219},
}

@InProceedings{Baffelli2015,
  author    = {Baffelli, Simone and Marino, Armando and Frey, Othmar},
  title     = {{Ku}-Band Polarimetric-Interferometric Ground Based Real Aperture Radar: Calibration and First Observations},
  booktitle = {Proceedings of PolInSAR},
  year      = {2015},
  date      = {2015},
}

@Article{Balz2007,
  author       = {Balz, Timo},
  title        = {{Real-Time Sar Simulation for Change Detection}},
  journaltitle = {Symposium A Quarterly Journal In Modern Foreign Literatures},
  date         = {2007},
  file         = {:home/baffelli/Library/Balz - 2007 - Real-Time Sar Simulation for Change Detection.pdf:pdf},
  keywords     = {SAR Real-time Simulation Change Detection Fusion,change detection,fusion,real-time,sar,simulation},
}

@Article{Bamler1999,
  author       = {Bamler, Richard and Hartl, Philipp},
  title        = {{Synthetic aperture radar interferometry}},
  journaltitle = {Inverse Problems},
  date         = {1999},
  volume       = {14},
  pages        = {R1--R54},
  issn         = {0266-5611},
  doi          = {10.1088/0266-5611/14/4/001},
  abstract     = {Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By exploiting the phase of the coherent radar signal, interferometry has transformed radar remote sensing from a largely interpretive science to a quantitative tool, with applications in cartography, geodesy, land cover characterization, and natural hazards. This paper reviews the techniques of interferometry, systems and limitations, and applications in a rapidly growing area of science and engineering},
  file         = {:home/baffelli/Library/Bamler, Hartl - 1999 - Synthetic aperture radar interferometry.pdf:pdf},
  isbn         = {00189219},
}

@InProceedings{Bao1999,
  author        = {Bao, Mingquan},
  title         = {{Backscattering change detection in SAR images using wavelet techniques}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1999},
  volume        = {3},
  isbn          = {0-7803-5207-6},
  pages         = {1561--1563},
  doi           = {10.1109/IGARSS.1999.772019},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=772019},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {3-dimensional algorithm,Change detection algorithms,Filters,Radar detection,Radar scattering,SAR,SAR image correlation,Signal to noise ratio,Speckle,Terrain mapping,Wavelet coefficients,Wavelet domain,autoregressive model,backscatter,backscattering,change detection,geophysical measurement technique,geophysical signal processing,geophysical techniques,image processing,image sequence,image sequences,land surface,radar imaging,radar remote sensing,remote sensing by radar,speckle noise,synthetic aperture radar,temporal change,wavelet,wavelet shrinkage algorithm,wavelet transforms},
  mendeley-tags = {3-dimensional algorithm,Change detection algorithms,Filters,Radar detection,Radar scattering,SAR,SAR image correlation,Signal to noise ratio,Speckle,Terrain mapping,Wavelet coefficients,Wavelet domain,autoregressive model,backscatter,backscattering,change detection,geophysical measurement technique,geophysical signal processing,geophysical techniques,image processing,image sequence,image sequences,land surface,radar imaging,radar remote sensing,remote sensing by radar,speckle noise,synthetic aperture radar,temporal change,wavelet,wavelet shrinkage algorithm,wavelet transforms},
}

@Article{Barber2011,
  author       = {Barber, David},
  title        = {{Bayesian Reasoning and Machine Learning}},
  journaltitle = {Machine Learning},
  date         = {2011},
  pages        = {646},
  issn         = {9780521518147},
  doi          = {10.1017/CBO9780511804779},
  url          = {http://eprints.pascal-network.org/archive/00007920/{\%}5Cnhttp://scholar.google.com/scholar?hl=en{\&}btnG=Search{\&}q=intitle:Bayesian+Reasoning+and+Machine+Learning{\#}0},
  abstract     = {Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.},
  arxivid      = {arXiv:1011.1669v3},
  file         = {:home/baffelli/Library/Barber - 2011 - Bayesian Reasoning and Machine Learning.pdf:pdf},
  isbn         = {9780521518147},
  keywords     = {computational,information theoretic learning with statistics,learning,statistics {\&} optimisation,theory {\&} algorithms},
  pmid         = {16931139},
}

@Article{Barcelona,
  author = {Josep Ruiz Rodon},
  title  = {{Radar phase based near surface meteorological data retrievals}},
  file   = {:home/baffelli/Library/Barcelona - Unknown - Radar phase based near surface meteorological data retrievals.pdf:pdf},
}

@InProceedings{Baronti1994,
  author        = {Baronti, S. and Carla, R. and Sigismondi, S. and Alparone, L.},
  title         = {{Principal component analysis for change detection on polarimetric multitemporal SAR data}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1994-08},
  volume        = {4},
  isbn          = {VO - 4},
  pages         = {2152----2154 vol.4},
  doi           = {10.1109/IGARSS.1994.399678},
  abstract      = {Principal component analysis (PCA) is applied to investigate on changes occurring in multitemporal polarimetric SAR imagery. Correlation instead of covariance matrix is used in the transformation, thus reducing gain variations introduced by the imaging system and giving equal weight to each polarization. The approach is effective when PCA is computed on images recorded simultaneously, as well as when it is applied to the whole set of multitemporal images},
  keywords      = {Covariance matrix,Data analysis,Eigenvalues and eigenfunctions,Image coding,Infrared detectors,Noise reduction,PCA,SAR imagery,SAR imaging,Signal to noise ratio,Spaceborne radar,Speckle,change detection,correlation,geophysical measurement technique,geophysical signal processing,geophysical signal processing geophysical techniqu,geophysical techniques,image processing,image sequences,land surface terrain mapping,multitemporal SAR data,polarization,principal component analysis,radar applications,radar imaging,radar polarimetry,radar remote sensing,remote sensing by radar,synthetic aperture radar},
  mendeley-tags = {Covariance matrix,Data analysis,Eigenvalues and eigenfunctions,Image coding,Infrared detectors,Noise reduction,PCA,SAR imagery,SAR imaging,Signal to noise ratio,Spaceborne radar,Speckle,change detection,correlation,geophysical measurement technique,geophysical signal processing,geophysical techniques,image processing,image sequences,land surface terrain mapping,multitemporal SAR data,polarization,principal component analysis,radar applications,radar imaging,radar polarimetry,radar remote sensing,remote sensing by radar,synthetic aperture radar},
}

@Article{Bazi2005,
  author        = {Bazi, Yakoub and Bruzzone, Lorenzo and Melgani, Farid},
  title         = {{An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2005-04},
  volume        = {43},
  pages         = {874--887},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2004.842441},
  abstract      = {In this paper, we present a novel automatic and$\backslash$n$\backslash$nunsupervised change-detection approach specifically oriented to$\backslash$n$\backslash$nthe analysis of multitemporal single-channel single-polarization$\backslash$n$\backslash$nsynthetic aperture radar (SAR) images. This approach is based$\backslash$n$\backslash$non a closed-loop process made up of three main steps: 1) a novel$\backslash$n$\backslash$npreprocessing based on a controlled adaptive iterative filtering;$\backslash$n$\backslash$n2) a comparison between multitemporal images carried out according$\backslash$n$\backslash$nto a standard log-ratio operator; and 3) a novel approach$\backslash$n$\backslash$nto the automatic analysis of the log-ratio image for generating the$\backslash$n$\backslash$nchange-detection map. The first step aims at reducing the speckle$\backslash$n$\backslash$nnoise in a controlled way in order to maximize the discrimination$\backslash$n$\backslash$ncapability between changed and unchanged classes. In the second$\backslash$n$\backslash$nstep, the two filtered multitemporal images are compared to$\backslash$n$\backslash$ngenerate a log-ratio image that contains explicit information on$\backslash$n$\backslash$nchanged areas. The third step produces the change-detection map$\backslash$n$\backslash$naccording to a thresholding procedure based on a reformulation of$\backslash$n$\backslash$nthe Kittler�Illingworth (KI) threshold selection criterion. In particular,$\backslash$n$\backslash$nthe modified KI criterion is derived under the generalized$\backslash$n$\backslash$nGaussian assumption for modeling the distributions of changed$\backslash$n$\backslash$nand unchanged classes. This parametric model was chosen because$\backslash$n$\backslash$nit is capable of better fitting the conditional densities of classes$\backslash$n$\backslash$nin the log-ratio image. In order to control the filtering step and,$\backslash$n$\backslash$naccordingly, the effects of the filtering process on change-detection$\backslash$n$\backslash$naccuracy, we propose to identify automatically the optimal$\backslash$n$\backslash$nnumber of despeckling filter iterations [Step 1)] by analyzing the$\backslash$n$\backslash$nbehavior of the modified KI criterion. This results in a completely$\backslash$n$\backslash$nautomatic and self-consistent change-detection approach that$\backslash$n$\backslash$navoids the use of empirical methods for the selection of the best$\backslash$n$\backslash$nnumber of filtering iterations. Experiments carried out on two$\backslash$n$\backslash$nsets of multitemporal images (characterized by different levels$\backslash$n$\backslash$nof speckle noise) acquired by the European Remote Sensing 2$\backslash$n$\backslash$nsatellite SAR sensor confirm the effectiveness of the proposed unsupervised$\backslash$n$\backslash$napproach, which results in change-detection accuracies$\backslash$n$\backslash$nvery similar to those that can be achieved by a manual supervised$\backslash$n$\backslash$nthresholding.},
  isbn          = {0196-2892},
  keywords      = {Adaptive control,Automatic control,Automatic generation control,Change detection,European Remote Sensing 2 satellite SAR sensor,Filtering,Gaussian processes,Image analysis,Image generation,Kittler-Illingworth threshold selection,Programmable control,Radar detection,Spaceborne radar,Speckle,automatic change detection,change detection,change-detection map,closed-loop process,controlled adaptive iterative filtering,data acquisition,data preprocessing,despeckling filter iterations,generalized Gaussian (GG) distribution,generalized Gaussian assumption,generalized Gaussian model,geophysical signal processing,geophysical techniques,image acquisition,image denoising,log-ratio image,log-ratio operator,multitemporal SAR images,multitemporal single-channel single-polarization s,multitemporal synthetic aperture radar (SAR) imag,multitemporal synthetic aperture radar (SAR) image,radar imaging,remote sensing by radar,self-consistent change-detection,speckle noise reduction,supervised thresholding,synthetic aperture radar,threshold selection,threshold selection.,thresholding procedure,unsupervised change-detection},
  mendeley-tags = {Adaptive control,Automatic control,Automatic generation control,European Remote Sensing 2 satellite SAR sensor,Filtering,Gaussian processes,Image analysis,Image generation,Kittler-Illingworth threshold selection,Programmable control,Radar detection,Spaceborne radar,Speckle,automatic change detection,change detection,change-detection map,closed-loop process,controlled adaptive iterative filtering,data acquisition,data preprocessing,despeckling filter iterations,generalized Gaussian (GG) distribution,generalized Gaussian assumption,generalized Gaussian model,geophysical signal processing,geophysical techniques,image acquisition,image denoising,log-ratio image,log-ratio operator,multitemporal SAR images,multitemporal single-channel single-polarization s,multitemporal synthetic aperture radar (SAR) image,radar imaging,remote sensing by radar,self-consistent change-detection,speckle noise reduction,supervised thresholding,synthetic aperture radar,threshold selection,thresholding procedure,unsupervised change-detection},
}

@InProceedings{Beasley1990,
  author    = {P.D.L. Beasley and A.G. Stove and B.J. Reits and B. As},
  title     = {Solving the problems of a single antenna frequency modulated {CW} radar},
  booktitle = {{IEEE} International Conference on Radar},
  date      = {1990},
  publisher = {{IEEE}},
  pages     = {391--395},
  doi       = {10.1109/RADAR.1990.201197},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=201197},
  abstract  = {A reflected power canceller (RPC) using modern p-i-n diode$\backslash$ntechnology which enables a frequency modulated continuous wave (FMCW)$\backslash$nradar to operate using a single antenna for transmission and reception$\backslash$nis described. Results are presented which demonstrate that such a$\backslash$ncanceller solves the problems for many CW-type radars over large RF$\backslash$nbandwidths (i.e. {\&}gt;2 GHz at {\textless}e1{\textgreater}X{\textless}/e1{\textgreater}-band). The RPC has been$\backslash$nsuccessfully installed into the Bofors/Signal PILOT FMCW tactical$\backslash$nnavigation radar. Results from sea trials are presented},
  file      = {:home/baffelli/Library/Beasley et al. - 1990 - Solving the problems of a single antenna frequency modulated CW radar.pdf:pdf},
}

@Article{Bennett1996,
  author       = {J.C. Bennett and K. Morrison},
  title        = {Development of a ground-based, polarimetric synthetic aperture radar},
  journaltitle = {Proceedings of the {IEEE} Aerospace Applications Conference},
  date         = {1996},
  volume       = {4},
  pages        = {139--146 vol.4},
  doi          = {10.1109/AERO.1996.499408},
  abstract     = {A description of an indoor SAR measurement facility is given and a series of results is presented to demonstrate the imaging properties of the system. The aim of the work is to understand better the microwave backscatter characteristics of vegetation and soils. Based around a vector network analyser, the system uses synthetic pulse techniques to obtain high resolution images. The principles of the technique are presented, together with a description of the imaging algorithm used. Calibration procedures are implemented successfully and the images provide useful quantitative RCS information. The polarimetric capability of the system is demonstrated for both metallic and vegetation targets. The system is a precursor to an outdoor polarimetric ground-based synthetic aperture radar (GB-SAR), designed to be easily and rapidly deployable at widely separated measurement sites},
  booktitle    = {1996 {IEEE} Aerospace Applications Conference. Proceedings},
  file         = {:home/baffelli/Library/Bennett, Morrison - 1996 - Development of a ground-based, polarimetric synthetic aperture radar.pdf:pdf},
  isbn         = {0-7803-3196-6},
  keywords     = {RCS information,backscatter,calibration,calibration procedures,ground-based radar,imaging algorithm,imaging properties,indoor SAR measurement facility,microwave backscatter characteristics,microwave imaging,network analysers,polarimetric synthetic aperture radar,radar cross-sections,radar imaging,radar polarimetry,soils,synthetic aperture radar,synthetic pulse techniques,vector network analyser,vegetation},
  publisher    = {{IEEE}},
}

@InProceedings{Bennett2000,
  author    = {J.C. Bennett and K. Morrison and A.M. Race and G. Cookmartin and S. Quegan},
  title     = {The {UK} {NERC} fully portable polarimetric ground-based synthetic aperture radar ({GB}-{SAR})},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date      = {2000},
  publisher = {{IEEE}},
  isbn      = {0780363590},
  pages     = {2313--2315},
  doi       = {10.1109/IGARSS.2000.858393},
  file      = {:home/baffelli/Library/Bennett et al. - 2000 - The UK NERC fully portable polarimetric ground-based synthetic aperture radar (GB-SAR).pdf:pdf},
}

@Article{Mora2002,
  author       = {P. Berardino and G. Fornaro and R. Lanari and E. Sansosti},
  title        = {A new algorithm for surface deformation monitoring based on small baseline differential {SAR} interferograms},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2002},
  date         = {2002-11},
  volume       = {40},
  month        = {nov},
  pages        = {2375--2383},
  issn         = {0196-2892},
  doi          = {10.1109/TGRS.2002.803792},
  url          = {http://ieeexplore.ieee.org/document/1166596/},
  abstract     = {This paper presents a new solution for detecting and following the temporal evolution of small scale deformation phenomena; in particular our approach extends the capability of the SBAS technique, presented in P. Berardino et al. (2001), which is mainly focused on investigating large scale deformations with spatial resolutions of about 100 m{\&}times;100 m. The proposed technique relies on small baseline differential SAR (DIFSAR) interferograms only, but it is implemented by using two different sets of data generated at low (multi-look data) and high spatial resolution (single-look data), respectively. The former are used to identify and estimate, via the SBAS technique or O. Mora et al. (2001, 2002), possible atmospheric phase artifacts and large scale deformation patterns; the latter to detect, on the high resolution residual phase components, structures highly coherent in time (buildings, rocks, lava structures, etc.), identified jointly to their heights and displacements. In particular the estimation of the temporal evolution of these local deformations is easily implemented by applying the SVD technique. The presented algorithm has been tested with data acquired by the European Remote Sensing (ERS) satellites relative to the Campania area (Italy).},
  file         = {:home/baffelli/Library/Mora et al. - 2002 - A new algorithm for monitoring localized deformation phenomena based on small baseline differential SAR interferogr.pdf:pdf},
  isbn         = {0-7803-7536-X},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Berthier2005,
  author       = {E. Berthier and H. Vadon and D. Baratoux and Y. Arnaud and C. Vincent and K.L. Feigl and F. R{\'{e}}my and B. Legr{\'{e}}sy},
  title        = {Surface motion of mountain glaciers derived from satellite optical imagery},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {2005},
  date         = {2005},
  volume       = {95},
  month        = {mar},
  pages        = {14--28},
  issn         = {00344257},
  doi          = {10.1016/j.rse.2004.11.005},
  abstract     = {A complete and detailed map of the ice-velocity field on mountain glaciers is obtained by cross-correlating SPOT5 optical images. This approach offers an alternative to SAR interferometry, because no present or planned RADAR satellite mission provides data with a temporal separation short enough to derive the displacements of glaciers. The methodology presented in this study does not require ground control points (GCPs). The key step is a precise relative orientation of the two images obtained by adjusting the stereo model of one "slave"' image assuming that the other "master" image is well georeferenced. It is performed with numerous precisely-located homologous points extracted automatically. The strong ablation occurring during summer time on the glaciers requires a correction to obtain unbiased displacements. The accuracy of our measurement is assessed based on a comparison with nearly simultaneous differential GPS surveys performed on two glaciers of the Mont Blanc area (Alps). If the images have similar incidence angles and correlate well, the accuracy is on the order of 0.5 m, or 1/5 of the pixel size. Similar results are also obtained without GCPs. An acceleration event, observed in early August for the Mer de Glace glacier, is interpreted in term of an increase in basal sliding. Our methodology, applied to SPOT5 images, can potentially be used to derive the displacements of the Earth's surface caused by landslides, earthquakes, and volcanoes. {\textcopyright} 2004 Elsevier Inc. All rights reserved.},
  file         = {:home/baffelli/Library/Berthier et al. - 2005 - Surface motion of mountain glaciers derived from satellite optical imagery.pdf:pdf},
  isbn         = {0034-4257},
  keywords     = {Cross-correlation,Mountain glaciers,SPOT5,Satellite optical images,Surface displacement},
  publisher    = {Elsevier {BV}},
}

@Article{Bevis1992,
  author       = {Michael Bevis and Steven Businger and Thomas A. Herring and Christian Rocken and Richard A. Anthes and Randolph H. Ware},
  title        = {{GPS} meteorology: Remote sensing of atmospheric water vapor using the global positioning system},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research},
  year         = {1992},
  date         = {1992},
  volume       = {97},
  pages        = {15787},
  issn         = {0148-0227},
  doi          = {10.1029/92JD01517},
  abstract     = {We present a new approach to remote sensing of water vapor based on the global positioning system (GPS). Geodesists and geophysicists have devised methods for estimating the extent to which signals propagating from GPS satellites to ground-based GPS receivers are delayed by atmospheric water vapor. This delay is parameterized in terms of a time-varying zenith wet delay (ZWD) which is retrieved by stochastic filtering of the GPS data. Given surface temperature and pressure readings at the GPS receiver, the retrieved ZWD can be transformed with very little additional uncertainty into an estimate of the integrated water vapor (IWV) overlying that receiver. Networks of continuously operating GPS receivers are being constructed by geodesists, geophysicists, government and military agencies, and others in order to implement a wide range of positioning capabilities. These emerging GPS networks offer the possibility of observing the horizontal distribution of IWV or, equivalently, precipitable water with unprecedented coverage and a temporal resolution of the order of 10 min. These measurements could be utilized in operational weather forecasting and in fundamental research into atmospheric storm systems, the hydrologic cycle, atmospheric chemistry, and global climate change. Specially designed, dense GPS networks could be used to sense the vertical distribution of water vapor in their immediate vicinity. Data from ground-based GPS networks could be analyzed in concert with observations of GPS satellite occultations by GPS receivers in low Earth orbit to characterize the atmosphere at planetary scale.},
  file         = {:home/baffelli/Library/Bevis et al. - 1992 - GPS meteorology Remote sensing of atmospheric water vapor using the global positioning system.pdf:pdf},
  isbn         = {0148-0227},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Bezvesilniy2011,
  author    = {Bezvesilniy, O O and Gorovyi, I M and Vynogradov, V V and Vavriv, D M},
  title     = {{Multi-Look Radiometric Correction of SAR Images}},
  journal   = {Radio Physics and Radio Astronomy},
  year      = {2012},
  date      = {2011},
  volume    = {3},
  pages     = {169--177},
  doi       = {10.1615/radiophysicsradioastronomy.v3.i2.90},
  file      = {:home/baffelli/Library/Bezvesilniy et al. - 2011 - Multi-Look Radiometric Correction of SAR Images.pdf:pdf},
  keywords  = {airborne sar,multi-look processing,radiometric correction,radiometric errors,sar,synthetic aperture radar},
  publisher = {Begell House},
}

@Article{Bhattacharya2009,
  author       = {Bhattacharya, C.},
  title        = {{Efficient interpolation for range-cell migration correction of RADARSAT-1 data}},
  journaltitle = {Progress in Electromagnetics Research Symposium},
  date         = {2009},
  volume       = {1},
  pages        = {376--381},
  issn         = {15599450},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84898946882{\&}partnerID=tZOtx3y1},
  abstract     = {RADARSAT-1 antenna is not yaw-steered, and its antenna radiation in azimuth has a squint of -1:6°. This causes phase of the range-compressed data to migrate over a large number of range-cells. Range-walk in the Doppler spectrum is compensated by interpolation in the range direction and re-indexing of data. Our objective here is to demonstrate efficient solution for digital interpolation of RADARSAT-1 data in the range-Doppler domain. We implement data re-indexing by two-dimensional memory mapping for each phase of polyphase interpolation. This makes correction for range-cell migration highly efficient, and parallel in terms of computation load. Results of accurate focusing in azimuth for the range-compressed point target response are presented in the paper.},
  file         = {:home/baffelli/Library/Bhattacharya - 2009 - Efficient interpolation for range-cell migration correction of RADARSAT-1 data.pdf:pdf},
  isbn         = {9781618390554},
}

@Article{Biggs2007,
  author       = {Juliet Biggs and Tim Wright and Zhong Lu and Barry Parsons},
  title        = {Multi-interferogram method for measuring interseismic deformation: {Denali} Fault, {Alaska}},
  journal      = {Geophysical Journal International},
  journaltitle = {Geophysical Journal International},
  year         = {2007},
  date         = {2007},
  volume       = {170},
  month        = {sep},
  pages        = {1165--1179},
  issn         = {0956540X},
  doi          = {10.1111/j.1365-246X.2007.03415.x},
  abstract     = {Studies of interseismic strain accumulation are crucial to our understanding of continental deformation, the earthquake cycle and seismic hazard. By mapping small amounts of ground deformation over large spatial areas, InSAR has the potential to produce continental-scale maps of strain accumulation on active faults. However, most InSAR studies to date have focused on areas where the coherence is relatively good (e.g. California, Tibet and Turkey) and most analysis techniques (stacking, small baseline subset algorithm, permanent scatterers, etc.) only include information from pixels which are coherent throughout the time-span of the study. In some areas, such as Alaska, where the deformation rate is small and coherence very variable, it is necessary to include information from pixels which are coherent in some but not all interferograms. We use a three-stage iterative algorithm based on distributed scatterer interferometry. We validate our method using synthetic data created using realistic parameters from a test site on the Denali Fault, Alaska, and present a preliminary result of 10.5 ± 5.0 mmyr−1 for the slip rate on the Denali Fault based on a single track of radar data from ERS1/2.},
  file         = {:home/baffelli/Library/Biggs et al. - 2007 - Multi-interferogram method for measuring interseismic deformation Denali Fault, Alaska.pdf:pdf},
  isbn         = {0956-540X},
  keywords     = {Continental deformation,Fault slip,Satellite geodesy},
  publisher    = {Oxford University Press ({OUP})},
}

@InCollection{Bivand2013,
  author    = {Bivand, Roger S and Pebesma, Edzer J and G{\'{o}}mez-Rubio, Virgilio},
  title     = {Applied Spatial Data Analysis with {R}},
  booktitle = {Use R},
  year      = {2008},
  date      = {2013},
  volume    = {1},
  publisher = {Springer New York},
  isbn      = {0387781706},
  pages     = {378},
  doi       = {10.1007/978-0-387-78171-6},
  file      = {:home/baffelli/Library/Bivand, Pebesma, G{'{o}}mez-Rubio - 2013 - Applied Spatial Data Analysis with R.pdf:pdf},
  issn      = {9780387938363},
  pmid      = {22057480},
}

@Article{Blanco-Sanchez2008,
  author       = {Blanco-S{\'{a}}nchez, Pablo and Mallorqu{\'{i}}, Jordi J. and Duque, Sergi and Monells, Daniel},
  title        = {{The coherent pixels technique (CPT): An advanced DInSAR technique for nonlinear deformation monitoring}},
  journaltitle = {Pure and Applied Geophysics},
  date         = {2008},
  volume       = {165},
  pages        = {1167--1193},
  issn         = {00334553},
  doi          = {10.1007/s00024-008-0352-6},
  abstract     = {This paper shows the potential applicability of orbital Synthetic Aperture Radar (SAR) Differential Interferometry (DInSAR) with multiple images for terrain deformation episodes monitoring. This paper is focused on the Coherent Pixels Technique (CPT) developed at the Remote Sensing Laboratory (RSLab) of the Universitat Politecnica de Catalunya (UPC). CPT is able to extract from a stack of differential interferograms the deformation evolution over vast areas during wide spans of time. The former is achieved thanks to the coverage provided by current SAR satellites, like ESA's ERS or ENVISAT, while the latter due to the large archive of images acquired since 1992. An interferogram is formed by the complex product of two SAR images (one complex conjugate) and its phase contains information relative to topography, terrain deformation and atmospheric conditions among others. The goal of differential interferometric processing is to retrieve and separate the different contributions. The processing scheme is composed of three main steps: firstly, the generation of the best interferogram set among all the available images of the zone under study; secondly, the selection of the pixels with reliable phase within the employed interferograms and, thirdly, their phase analysis to calculate, as the main result, their deformation time series within the observation period. In this paper, the Coherent Pixels Technique (CPT) is presented in detail as well as the result of its application in different scenarios. Results reveal its practical utility for detecting and reproducing deformation episodes, providing a valuable tool to the scientific community for the understanding of considerable geological process and to monitor the impact of underground human activity.},
  file         = {:home/baffelli/Library/Blanco-S{'{a}}nchez et al. - 2008 - The coherent pixels technique (CPT) An advanced DInSAR technique for nonlinear deformation monitoring.pdf:pdf},
  isbn         = {0002400803526},
  keywords     = {Deformation monitoring,Differential interferometry,Orbital SAR},
}

@Book{Blaunstein2006,
  author    = {Nathan Blaunstein and Christos Christodoulou},
  title     = {Radio Propagation and Adaptive Antennas for Wireless Communication Links},
  year      = {2006},
  date      = {2006-11},
  volume    = {8},
  series    = {Wiley Series in Microwave and Optical Engineering},
  publisher = {John Wiley {\&} Sons, Inc.},
  isbn      = {9780470069998},
  chapter   = {6},
  doi       = {10.1002/0470069996},
  booktitle = {Radio Propagation and Adaptive Antennas for Wireless Communication Links: Terrestrial, Atmospheric and Ionospheric},
  file      = {:home/baffelli/Library/Blaunstein, Christodoulou - 2006 - Radio Propagation and Adaptive Antennas for Wireless Communication Links.pdf:pdf},
  month     = {nov},
}

@Article{Carroll2012,
  author       = {Nikolay Bliznyuk and Raymond J. Carroll and Marc G. Genton and Yuedong Wang},
  title        = {Variogram estimation in the presence of trend},
  journal      = {Statistics and Its Interface},
  journaltitle = {Statistics and Its Interface},
  year         = {2012},
  date         = {2012-12},
  volume       = {5},
  pages        = {159--168},
  issn         = {19387989},
  doi          = {10.4310/SII.2012.v5.n2.a2},
  url          = {http://www.ncbi.nlm.nih.gov/pubmed/PMC3378336 http://www.ncbi.nlm.nih.gov/pubmed/378336 http://www.intlpress.com/site/pub/pages/journals/items/sii/content/vols/0005/0002/a002/},
  file         = {:home/baffelli/Library/Bliznyuk et al. - 2012 - Variogram estimation in the presence of trend.pdf:pdf},
  keywords     = {and phrases,bias,covariance function,dependence,nonlinear regression,nonparametric regression,spatio-temporal,time series},
  publisher    = {International Press of Boston},
}

@Article{Boerner2007,
  author       = {Boerner, Wolfgang-Martin and Luneburg, E. and Danklmayer, Andreas},
  title        = {{Principal Component Analysis (PCA) in the Context of Radar Polarimetry}},
  journaltitle = {PIERS Online},
  date         = {2007},
  volume       = {3},
  pages        = {633--636},
  issn         = {1931-7360},
  doi          = {10.2529/PIERS061006085232},
  url          = {http://piers.mit.edu/piersonline/piers.php?year=2007{\&}volume=3{\&}number=5{\&}page=633},
  file         = {:home/baffelli/Library/Boerner, Luneburg, Danklmayer - 2007 - Principal Component Analysis (PCA) in the Context of Radar Polarimetry.pdf:pdf},
}

@InProceedings{Boncori2007,
  author       = {J.P. Merryman Boncori and J.J. Mohr},
  title        = {Statistical description of tropospheric delay for {InSAR}: Overview and a new model},
  booktitle    = {2007 {IEEE} International Geoscience and Remote Sensing Symposium},
  year         = {2007},
  date         = {2007},
  publisher    = {{IEEE}},
  isbn         = {1424412129},
  pages        = {4483--4486},
  doi          = {10.1109/IGARSS.2007.4423851},
  file         = {:home/baffelli/Library/Boncori, Mohr - 2007 - Statistical description of tropospheric delay for InSAR Overview and a new model.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {Atmospheric propagation delay,SAR interferometry,Statistical modelling},
}

@Article{Borden2004a,
  author    = {Borden, Brett and Cheney, Margaret},
  title     = {{Synthetic-aperture imaging from high-Doppler-resolution measurements}},
  journal   = {Inverse Problems},
  year      = {2004},
  date      = {2004},
  volume    = {21},
  month     = {nov},
  pages     = {1--11},
  doi       = {10.1088/0266-5611/21/1/001},
  abstract  = {We develop the theory of radar imaging from data measured by a moving antenna emitting a single-frequency waveform. We show that, under a linearized (Born) scattering model, the signal at a given Doppler shift is due to a superposition of returns from stationary scatterers on a cone whose axis is the flight velocity vector. This cone reduces to a hyperbola when the scatterers are known to lie on a planar surface. In this case, reconstruction of the scatterer locations can be accomplished by a tomographic inversion in which the scattering density function is reconstructed from its integrals over hyperbolas. We give an approximate reconstruction formula and analyse the resolution of the resulting image. We provide a numerical shortcut and show results of numerical tests in a simple case.},
  file      = {:home/baffelli/Library/Borden, Cheney - 2004 - Synthetic-aperture imaging from high-Doppler-resolution measurements.pdf:pdf},
  publisher = {{IOP} Publishing},
}

@Article{Broek2005,
  author = {Broek, Bert Van Den and Dekker, Rob},
  title  = {{Target Discrimination in Polarimetric ISAR Data using Robust Feature Vectors}},
  date   = {2005},
  file   = {:home/baffelli/Library/Broek, Dekker - 2005 - Target Discrimination in Polarimetric ISAR Data using Robust Feature Vectors.pdf:pdf},
}

@Article{Bruderer2007,
  author       = {Bruderer, Bruno},
  title        = {{Adapting a Military Radar for Ornithological Research - The Case of the "Superfledermaus"}},
  journaltitle = {Applying radar technology to migratory bird conservation and management: Strengthening and expanding a collaborative},
  date         = {2007},
  pages        = {32--37},
  url          = {http://www.arlis.org/docs/vol1/212383927.pdf},
  file         = {:home/baffelli/Library/Bruderer - 2007 - Adapting a Military Radar for Ornithological Research - The Case of the Superfledermaus.pdf:pdf},
}

@Article{Buades2005,
  author        = {Buades, A. and Coll, B.},
  title         = {{A non-local algorithm for image denoising}},
  journaltitle  = {Computer Vision and Pattern},
  date          = {2005-06},
  volume        = {2},
  pages         = {60--65},
  issn          = {1063-6919},
  doi           = {10.1109/CVPR.2005.38},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1467423{\%}5Cnhttp://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=1467423},
  abstract      = {We propose a new measure, the method noise, to evalu-ate and compare the performance of digital image denois-ing methods. We first compute and analyze this method noise for a wide class of denoising algorithms, namely the local smoothing filters. Second, we propose a new algo-rithm, the non local means (NL-means), based on a non lo-cal averaging of all pixels in the image. Finally, we present some experiments comparing the NL-means algorithm and the local smoothing filters.},
  isbn          = {0-7695-2372-2},
  keywords      = {Algorithm design and analysis,Digital images,Filtering,NL-means algorithm,Noise measurement,Noise reduction,Pixel,White noise,Wiener filter,digital image denoising method,image denoising,image resolution,local smoothing filters,nonlocal algorithm,smoothing methods},
  mendeley-tags = {Algorithm design and analysis,Digital images,Filtering,NL-means algorithm,Noise measurement,Noise reduction,Pixel,White noise,Wiener filter,digital image denoising method,image denoising,image resolution,local smoothing filters,nonlocal algorithm,smoothing methods},
}

@Misc{BundesamtfurRaumentwicklungARE2011,
  author      = {{Bundesamt f{\"{u}}r Raumentwicklung ARE} and {Bundesamt f{\"{u}}r Umwelt BAFU} and {Bundesamt f{\"{u}}r Statistik BFS}},
  title       = {{Landschaftstypologie Schweiz. Teil 2, Beschreibung der Landschaftstypen}},
  date        = {2011},
  url         = {http://www.are.admin.ch/themen/raumplanung/00244/04456/index.html?lang=de www.are.admin.ch},
  file        = {:home/baffelli/Library/Bundesamt f{"{u}}r Raumentwicklung ARE, Bundesamt f{"{u}}r Umwelt BAFU, Bundesamt f{"{u}}r Statistik BFS - 2011 - Landschaftstypologie Schweiz. Teil.pdf:pdf},
  institution = {Bundesamt f{\"{u}}r Raumentwicklung ARE},
}

@Article{Bussey,
  Title                    = {{Mini-RF : Imaging Radars for Exploring the Lunar Poles}},
  Author                   = {Bussey, Ben and Spudis, Paul and Raney, Keith and Winters, Helene},
  Pages                    = {1--16},

  File                     = {:home/baffelli/Library/Bussey et al. - Unknown - Mini-RF Imaging Radars for Exploring the Lunar Poles.pdf:pdf}
}

@TechReport{Butt2014,
  author      = {Butt, Jemil},
  title       = {{D-BAUG Annual Report 2014}},
  institution = {ETH Z{\"{u}}rich},
  date        = {2014},
  pages       = {76},
}

@Article{Byberg2012,
  author   = {Byberg, Geir Arild},
  title    = {{Synthetic Aperture Radar: A Real-Time Processor for ESAs Wavemill Mission}},
  date     = {2012},
  url      = {https://www.duo.uio.no/handle/10852/34137},
  abstract = {In 2004, the European Space Agency proposed a new Synthetic Aperture Radar mission, Wavemill, which would use new techniques to measure ocean height and ocean velocity down to 10 cm/s. Due to the high sampling frequency and the amount of data that would be produced, on-board processing would be necessary to more efficiently use the communication link, a link that would become a bottleneck if nothing was conducted on the data. An FPGA was recommended for performing the on-board processing. This thesis focuses on the implementation of a proposed SAR processor that will be used to process the raw SAR data inWavemill. The SAR processor was synthesized for a Xilinx Virtex-6 FPGA and simulation verified the design for the range compression component. The synthesis showed that implementation of the proposed real-time SAR processor was possible. The synthesis also showed that the SAR processor would function with a clock frequency of minimum 240 MHz.},
  file     = {:home/baffelli/Library/Byberg - 2012 - Synthetic Aperture Radar A Real-Time Processor for ESAs Wavemill Mission.pdf:pdf},
}

@Article{Caduff2014,
  author       = {Rafael Caduff and Andrew Kos and Fritz Schlunegger and Brian W. McArdell and Andreas Wiesmann},
  title        = {Terrestrial Radar Interferometric Measurement of Hillslope Deformation and Atmospheric Disturbances in the {Illgraben} Debris-Flow Catchment, {Switzerland}},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {{IEEE} Geoscience and Remote Sensing Letters},
  year         = {2014},
  date         = {2014-02},
  volume       = {11},
  month        = {feb},
  pages        = {434--438},
  doi          = {10.1109/lgrs.2013.2264564},
  file         = {:home/baffelli/Library/Caduff et al. - 2014 - Terrestrial Radar Interferometric Measurement of Hillslope Deformation and Atmospheric Disturbances in the Illgra.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Caduff2015,
  author       = {Rafael Caduff and Fritz Schlunegger and Andrew Kos and Andreas Wiesmann},
  title        = {A review of terrestrial radar interferometry for measuring surface change in the geosciences},
  journal      = {Earth Surface Processes and Landforms},
  journaltitle = {Earth Surface Processes and Landforms},
  year         = {2014},
  date         = {2015-02},
  volume       = {40},
  month        = {oct},
  pages        = {208--228},
  issn         = {01979337},
  doi          = {10.1002/esp.3656},
  abstract     = {This paper presents a review of the current state of the art in the use of terrestrial radar interferometry for the detection of surface changes related to mass movement. Different hardware-types and acquisition concepts are described, which use either real or synthetic aperture for radar image formation. We present approaches for data processing procedures, paying special attention to the separation of high resolution displacement information from atmospheric phase variations. Recent case studies are used to illustrate applications in terrestrial radar interferometry for change detection. Applications range from detection and quantification of very slow moving (millimeters to centimeters per year) displacements in rock walls from repeat monitoring, to rapid processes resulting in fast displacements (50m/yr) acquired during single measurement campaigns with durations of only a few hours. Fast and episodic acting processes such as rockfall and snow avalanches can be assessed qualitatively in the spatial domain by mapping decorrelation caused by those processes. A concluding guide to best practice outlines the necessary preconditions that have to be fulfilled for successful application of the technique, as well as in areas characterized by rapid decorrelation. Empirical data from a Ku-band sensor show the range of temporal decorrelation of different surfaces after more than two years for rock-surfaces and after a few seconds to minutes in vegetated areas during windy conditions. The examples show that the displacement field can be measured for landslides in dense grassland, ice surfaces on flowing glaciers and snowpack creep. Copyright (c) 2014 John Wiley {\&} Sons, Ltd.},
  file         = {:home/baffelli/Library/Caduff et al. - 2015 - A review of terrestrial radar interferometry for measuring surface change in the geosciences.pdf:pdf},
  isbn         = {01979337},
  keywords     = {Mass movements,Surface deformation,Terrestrial radar interferometry},
  publisher    = {Wiley},
}

@InCollection{Caduff2017,
  author    = {Rafael Caduff and Tazio Strozzi},
  title     = {Terrestrial Radar Interferometry Monitoring During a Landslide Emergency 2016, {Ghirone}, {Switzerland}},
  booktitle = {Advancing Culture of Living with Landslides},
  year      = {2017},
  date      = {2017},
  publisher = {Springer International Publishing},
  isbn      = {978-3-319-53487-9},
  pages     = {301--309},
  doi       = {10.1007/978-3-319-53487-9_34},
  url       = {https://doi.org/10.1007/978-3-319-53487-9{\_}34},
  abstract  = {In early spring 2016 an exceptionally high rock-fall activity in a slope above the Village of Ghirone, Blenio-Valley Ticino, Switzerland was observed. Constant rock-fall activity was induced by toppling movement of the very thin-layered metamorphic rock. At this time, there was no information on the actual extent and the deformation rates of the landslide instability. Due to the rock-fall and failure related risk, no instrumentation on-site was possible. Local authorities then decided setting up a monitoring campaign using terrestrial radar interferometry that does not need installations in the target area. A campaign was started in the morning of 22 March 2016. Shortly after the beginning of the measurements, the extent of the active area could be determined, showing a total affected area of 5300 m2. The displacement velocity was in the range of 0.02--0.05 m/h, showing an increasing trend. Using inverse velocity extrapolations, a failure forecast could be done pointing to a potential failure event in the late afternoon of the same day. At 16:45 UTC+1 a major part of the slope failed. It was only 1/3 of the expected volume. Landslide activity continued and a second major failure was recorded in the night. The emergency campaign ended on 24 March 2016 after the deformation was decreasing to a level without imminent threat to the village. A refined post-processing of the radar data showed that the simplified real-time processing approach was suitable for the situation. Additionally, information on the 2d direction of the landslide movement could be obtained using intensity image pixel tracking technique. Finally, maps of volume differences could be created using the interferometric baseline, showing a difference of 33,900 m3 between 22 March and a later campaign performed on 31 May 2016.},
}

@Article{Caduff2013a,
  author       = {Caduff, Rafael and Strozzi, Tazio and Wiesmann, Andreas},
  title        = {{Erfolgreicher Einsatz terrestrischer Radar-Interferometrie zur fl{\"{a}}chenhaften Vermesung von ausserordentlichen Hangrutschungsbewegungen im Gebiet Hintergraben (OW)}},
  journaltitle = {Swiss bulletin f{\"{u}}r angewandte Geologie},
  date         = {2013},
  volume       = {18},
  doi          = {10.5169/seals-391152},
  file         = {:home/baffelli/Library/Caduff, Strozzi, Wiesmann - 2013 - Erfolgreicher Einsatz terrestrischer Radar-Interferometrie zur fl{"{a}}chenhaften Vermesung von ausserord.pdf:pdf},
  keywords     = {deformation measurement,landslide displacement,radar interferometry,terrestrial radar},
}

@Article{Caekenberghe2009,
  author = {Caekenberghe, V A N},
  title  = {{Antenna}},
  date   = {2009},
  volume = {1},
  file   = {:home/baffelli/Library/Caekenberghe - 2009 - Antenna.pdf:pdf},
}

@Article{Carincotte2006,
  author        = {Carincotte, C. and Derrode, S. and Bourennane, S.},
  title         = {{Unsupervised change detection on SAR images using fuzzy hidden Markov chains}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2006-02},
  volume        = {44},
  pages         = {432--441},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2005.861007},
  url           = {http://ieeexplore.ieee.org.www.library.gatech.edu:2048/ielx5/36/33388/01580728.pdf?tp={\&}arnumber=1580728{\&}isnumber=33388{\%}5Cnhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1580728},
  abstract      = {This work deals with unsupervised change detection in temporal sets of synthetic aperture radar (SAR) images. We focus on one of the most widely used change detector in the SAR context, the so-called log-ratio. In order to deal with the classification issue, we propose to use a new fuzzy version of hidden Markov chains (HMCs), and thus to address fuzzy change detection with a statistical approach. The main characteristic of the proposed model is to simultaneously use Dirac and Lebesgue measures at the class chain level. This allows the coexistence of hard pixels (obtained with the classical HMC segmentation) and fuzzy pixels (obtained with the fuzzy measure) in the same image. The quality assessment of the proposed method is achieved with several bidate sets of simulated images, and comparisons with classical HMC are also provided. Experimental results on real European Remote Sensing 2 Precision Image (ERS-2 PRI) images confirm the effectiveness of the proposed approach.},
  isbn          = {0196-2892},
  keywords      = {Detectors,Dirac measure,ERS-2 PRI images,European Remote Sensing 2 Precision Image,Lebesgue measure,Monitoring,Pixel,Radar detection,SAR images,Sensor systems,Vegetation mapping,change detection,fuzzy change detection,fuzzy hidden Markov chain (HMC),fuzzy hidden Markov chains,fuzzy pixels,fuzzy set theory,geophysical signal processing,geophysical techniques,hidden Markov models,image classification,image segmentation,iterative conditional estimation,iterative conditional estimation (ICE),log-ratio detector,maximal posterior mode (MPM) classification,maximal posterior mode classification,maximum likelihood estimation,radar imaging,remote sensing by radar,statistical analysis,synthetic aperture radar,synthetic aperture radar (SAR) images,unsupervised change detection},
  mendeley-tags = {Detectors,Dirac measure,ERS-2 PRI images,European Remote Sensing 2 Precision Image,Lebesgue measure,Monitoring,Pixel,Radar detection,SAR images,Sensor systems,Vegetation mapping,change detection,fuzzy change detection,fuzzy hidden Markov chain (HMC),fuzzy hidden Markov chains,fuzzy pixels,fuzzy set theory,geophysical signal processing,geophysical techniques,hidden Markov models,image classification,image segmentation,iterative conditional estimation,iterative conditional estimation (ICE),log-ratio detector,maximal posterior mode (MPM) classification,maximal posterior mode classification,maximum likelihood estimation,radar imaging,remote sensing by radar,statistical analysis,synthetic aperture radar,synthetic aperture radar (SAR) images,unsupervised change detection},
}

@Article{Carnec1996,
  author       = {Claudie Carnec and Didier Massonnet and Christine King},
  title        = {Two examples of the use of {SAR} interferometry on displacement fields of small spatial extent},
  journal      = {Geophysical Research Letters},
  journaltitle = {Geophysical Research Letters},
  year         = {1996},
  date         = {1996},
  volume       = {23},
  month        = {dec},
  pages        = {3579},
  issn         = {0094-8276},
  doi          = {10.1029/96GL03042},
  abstract     = {Interferometric combination of pairs of SAR images acquired by the European ERS-1 satellite maps deformation fields associated with two phenomena, both of small spatial extension and located in SE France: the one is rapid terrain deformation caused by a landslide near the city of Saint Etienne de Tinee, and the other is slower subsidence caused by underground coal mining near Gardanne. Unlike interferometric measurement of wide-field deformation, atmospheric propagation heterogeneity is not an accuracy-limiting factor. Although the radar data confirm prior knowledge concerning the landslide, such an application of SAR interferometry appears difficult under normal conditions of observation using current spaceborne radar systems. The study of soil subsidence, however, can be generalized and improves prior knowledge of the displacement field, which has here been modeled assuming elastic deformation in a half-space from several sources. The two examples help to understand the limits of the interferometric technique.},
  file         = {:home/baffelli/Library/Carnec, Massonnet, King - 1996 - Two examples of the use of SAR interferometry on displacement fields of small spatial extent.pdf:pdf},
  isbn         = {0094-8276},
  keywords     = {http://dx.doi.org/10.1029/96GL03042, doi:10.1029/9},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Catani2005,
  author       = {Filippo Catani and Paolo Farina and Sandro Moretti and Giovanni Nico and Tazio Strozzi},
  title        = {On the application of {SAR} interferometry to geomorphological studies: estimation of landform attributes and mass movements},
  journal      = {Geomorphology},
  journaltitle = {Geomorphology},
  year         = {2005},
  date         = {2005},
  volume       = {66},
  month        = {mar},
  pages        = {119--131},
  issn         = {0169555X},
  doi          = {10.1016/j.geomorph.2004.08.012},
  abstract     = {This paper presents two examples of application of Synthetic Aperture Radar (SAR) interferometry (InSAR) to typical geomorphological problems. The principles of InSAR are introduced, taking care to clarify the limits and the potential of this technique for geomorphological studies. The application of InSAR to the quantification of landform attributes such as the slope and to the estimation of landform variations is investigated. Two case studies are presented. A first case study focuses on the problem of measuring landform attributes by interferometric SAR data. The interferometric result is compared with the corresponding one obtained by a Digital Elevation Model (DEM). In the second case study, the use of InSAR for the estimation of landform variations caused by a landslide is detailed. {\textcopyright} 2004 Elsevier B.V. All rights reserved.},
  file         = {:home/baffelli/Library/Catani et al. - 2005 - On the application of SAR interferometry to geomorphological studies Estimation of landform attributes and mass m.pdf:pdf},
  isbn         = {0169-555X},
  keywords     = {Digital Elevation Model (DEM),Landslides,Synthetic Aperture Radar (SAR) interferometry,Terrain analysis},
  publisher    = {Elsevier {BV}},
}

@InProceedings{Caves1994,
  author        = {Caves, R.G. and Quegan, S.},
  title         = {{Segmentation based change detection in ERS-1 SAR images}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1994-08},
  volume        = {4},
  isbn          = {0-7803-1497-2},
  pages         = {2149--2151},
  doi           = {10.1109/IGARSS.1994.399677},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=399677},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Buildings,Change detection algorithms,ERS-1,Geoscience,Image edge detection,Layout,RWSEG,Radiometry,Robustness,SAR imaging,Spaceborne radar,agriculture,algorithm,change detection,geomorphology,geophysical measurement technique,geophysical signal processing,geophysical techniques,hydrological techniques,hydrology,image segmentation,image sequences,lakes,land surface terrain mapping,radar applications,radar imaging,radar remote sensing,remote sensing by radar,salt lake,salt playa,spaceborne radar imaging,synthetic aperture radar},
  mendeley-tags = {Buildings,Change detection algorithms,ERS-1,Geoscience,Image edge detection,Layout,RWSEG,Radiometry,Robustness,SAR imaging,Spaceborne radar,agriculture,algorithm,change detection,geomorphology,geophysical measurement technique,geophysical signal processing,geophysical techniques,hydrological techniques,hydrology,image segmentation,image sequences,lakes,land surface terrain mapping,radar applications,radar imaging,radar remote sensing,remote sensing by radar,salt lake,salt playa,spaceborne radar imaging,synthetic aperture radar},
}

@InProceedings{Cha2012,
  author        = {Cha, M. and Phillips, R. and Wolfe, P.J.},
  title         = {{Test statistics for synthetic aperture radar coherent change detection}},
  booktitle     = {2012 IEEE Statistical Signal Processing Workshop (SSP)},
  date          = {2012-08},
  pages         = {856--859},
  doi           = {10.1109/SSP.2012.6319841},
  keywords      = {Charge coupled devices,Coherence,Coherence estimation,Radar detection,Sociology,coherence estimator,coherent change detection,coherent change detection images,complex Gaussian data,correlation,gauge,interferometric SAR processing,paired synthetic aperture radar images,radar imaging,remote sensing,statistical testing,synthetic aperture radar,synthetic aperture radar coherent change detection,test statistics},
  mendeley-tags = {Charge coupled devices,Coherence,Coherence estimation,Radar detection,Sociology,coherence estimator,coherent change detection,coherent change detection images,complex Gaussian data,correlation,gauge,interferometric SAR processing,paired synthetic aperture radar images,radar imaging,remote sensing,statistical testing,synthetic aperture radar,synthetic aperture radar coherent change detection,test statistics},
}

@Article{Chang2011,
  author       = {Chang, Yl and Chiang, Cy and Chen, Ks},
  title        = {{SAR image simulation with application to target recognition}},
  journaltitle = {Progress In Electromagnetics Research},
  date         = {2011},
  volume       = {119},
  pages        = {35--57},
  issn         = {1559-8985},
  doi          = {10.2528/PIER11061507},
  url          = {http://jpier.org/PIER/pier.php?paper=11061507},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Chang, Chiang, Chen - 2011 - SAR image simulation with application to target recognition.pdf:pdf},
}

@Article{Chen2011,
  author        = {Jiong Chen and Yilun Chen and Wentao An and Yi Cui and Jian Yang},
  title         = {Nonlocal Filtering for Polarimetric {SAR} Data: A Pretest Approach},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2011},
  date          = {2011-05},
  volume        = {49},
  month         = {may},
  pages         = {1744--1754},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2010.2087763},
  abstract      = {A pretest approach based on the complex Wishart distribution in polarimetric$\backslash$nsynthetic aperture radar (POLSAR) speckle filtering is proposed in$\backslash$nthis paper. The main principle is to select homogeneous pixels in$\backslash$na large-scale area in the filtering process, which is called pretesting.$\backslash$nTo preserve details and fine structures while despeckling, the homogeneous$\backslash$npixels are selected by comparing their 3 × 3 neighboring windows.$\backslash$nA test statistic based on the complex Wishart distribution is used$\backslash$nto decide the selection of homogeneous pixels. Speckle filtering$\backslash$nis processed by summing up the homogeneous pixels with weights according$\backslash$nto the values of their test statistics. To accelerate the pretest$\backslash$nfilter, we further propose a refined algorithm, which eliminates$\backslash$nredundant operations without deteriorating the performance. We demonstrate$\backslash$nthe performance of the proposed algorithm by using both simulated$\backslash$nand real airborne POLSAR data.},
  keywords      = {Computational modeling,Covariance matrix,Filtering,Image edge detection,POLSAR speckle filtering,Pixel,Scattering,Speckle,airborne radar,complex Wishart distribution,filtering theory,homogeneous pixels,nonlocal filtering,polarimetric SAR data,polarimetric synthetic aperture radar,polarimetric synthetic aperture radar (POLSAR),pretest,pretest approach,radar resolution,speckle filtering,synthetic aperture radar},
  mendeley-tags = {Computational modeling,Covariance matrix,Filtering,Image edge detection,POLSAR speckle filtering,Pixel,Scattering,Speckle,airborne radar,complex Wishart distribution,filtering theory,homogeneous pixels,nonlocal filtering,polarimetric SAR data,polarimetric synthetic aperture radar,polarimetric synthetic aperture radar (POLSAR),pretest,pretest approach,radar resolution,speckle filtering,synthetic aperture radar},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Thesis{Cherukumilli2012,
  author      = {Cherukumilli, Satya Srinivasu},
  title       = {{GBIR} crosstalk reduction of fully polarimetric data from {Blue Springs Dam}},
  type        = {Master Thesis},
  institution = {University of Missouri – Columbia},
  year        = {2012},
  date        = {2012},
  url         = {http://hdl.handle.net/10355/15939},
  file        = {:home/baffelli/Library/Cherukumilli - 2012 - GBIR crosstalk reduction of fully polarimetric data from Blue Springs Dam.pdf:pdf},
  keywords    = {Thesis,crosstalk behavior,ground-based real-aperture RADAR,phase measurement},
}

@InCollection{Chiles2012,
  author    = {Chil{\`{e}}s, Jean-Paul and Delfiner, Pierre},
  title     = {Intrinsic Model of Order k},
  booktitle = {Geostatistics: Modeling Spatial Uncertainty},
  date      = {2012},
  isbn      = {9780470316993},
  pages     = {231--291},
  doi       = {10.1002/9780470316993.ch4},
  abstract  = {The prelims comprise:$\backslash$n$\backslash$n* IRF-0 and IRF-$\kappa$$\backslash$n* A Second Look at the Model of Universal Kriging$\backslash$n* Allowable Linear Combinations of Order $\kappa$$\backslash$n* Intrinsic Random Functions of Order $\kappa$$\backslash$n* Generalized Covariance Functions$\backslash$n* Estimation in the IRF Model$\backslash$n* Generalized Variogram$\backslash$n* Automatic Structure Identification in the General Case},
  file      = {:home/baffelli/Library/Chil{`{e}}s, Delfiner - 2012 - Intrinsic Model of Orderk.pdf:pdf},
  keywords  = {brownian motion,centered covariance,geostatistics,intrinsic random function,linear combination},
}

@InCollection{Chiles2012a,
  author    = {Chil{\`{e}}s, Jean-Paul and Delfiner, Pierre},
  title     = {{Intrinsic Model of Orderk}},
  booktitle = {Geostatistics: Modeling Spatial Uncertainty},
  date      = {2012},
  isbn      = {9780470316993},
  pages     = {231--291},
  doi       = {10.1002/9780470316993.ch4},
  abstract  = {The prelims comprise:$\backslash$n$\backslash$n* IRF-0 and IRF-$\kappa$$\backslash$n* A Second Look at the Model of Universal Kriging$\backslash$n* Allowable Linear Combinations of Order $\kappa$$\backslash$n* Intrinsic Random Functions of Order $\kappa$$\backslash$n* Generalized Covariance Functions$\backslash$n* Estimation in the IRF Model$\backslash$n* Generalized Variogram$\backslash$n* Automatic Structure Identification in the General Case},
  file      = {:home/baffelli/Library/Chil{`{e}}s, Delfiner - 2012 - Intrinsic Model of Orderk.pdf:pdf},
  keywords  = {brownian motion,centered covariance,geostatistics,intrinsic random function,linear combination},
}

@Book{Cloude2009a,
  author    = {Shane Cloude},
  title     = {Polarisation: Applications in Remote Sensing},
  year      = {2009},
  date      = {2009-10},
  publisher = {Oxford University Press},
  isbn      = {9780199569731},
  doi       = {10.1093/acprof:oso/9780199569731.001.0001},
  month     = {oct},
}

@Article{Cloude2005,
  author       = {Cloude, S.R.},
  title        = {{PoL-InSAR training course}},
  journaltitle = {Training Courses for PolSARpro v3.0},
  date         = {2005},
  pages        = {1--44},
  url          = {https://earth.esa.int/polsarpro/Manuals/1{\_}Pol-InSAR{\_}Training{\_}Course.pdf},
  file         = {:home/baffelli/Library/Cloude - 2005 - PoL-InSAR training course.pdf:pdf},
}

@Article{Cloude2003,
  author       = {S.R. Cloude and K.P. Papathanassiou},
  title        = {Three-stage inversion process for polarimetric {SAR} interferometry},
  journal      = {{IEE} Proceedings - Radar, Sonar and Navigation},
  journaltitle = {IEE Proceedings - Radar, Sonar and Navigation},
  year         = {2003},
  date         = {2003},
  volume       = {150},
  pages        = {125},
  issn         = {13502395},
  doi          = {10.1049/ip-rsn:20030449},
  url          = {http://digital-library.theiet.org/content/journals/10.1049/ip-rsn{\_}20030449},
  file         = {:home/baffelli/Library/Cloude, Papathanassiou - 2003 - Three-stage inversion process for polarimetric SAR interferometry.pdf:pdf},
  publisher    = {Institution of Engineering and Technology ({IET})},
}

@Article{cloude_polarimetric_1998,
  author       = {S.R. Cloude and K.P. Papathanassiou},
  title        = {Polarimetric {SAR} interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1998},
  date         = {1998-09},
  volume       = {36},
  pages        = {1551--1565},
  issn         = {01962892},
  doi          = {10.1109/36.718859},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=964971},
  abstract     = {The objective of this paper is to examine the applica- tion of single-baseline polarimetric SAR interferometry to the re- mote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable for the estimation of forest parameters frominterfer- ometric observables is introduced, discussed and validated. Based on this model, an inversion algorithm which allows the estimation of forest parameters such as tree height, average extinction, and underlying topography from single-baseline fully polarimetric in- terferometric data is addressed. The performance of the inversion algorithm is demonstrated using fully polarimetric single baseline experimental data acquired by DLR's E-SAR system at L-band.},
  file         = {:home/baffelli/Library/Cloude et al. - 1998 - Polarimetric SAR interferometry.pdf:pdf;:home/baffelli/Library/Papathanassiou, Cloude - 2001 - Single-baseline polarimetric SAR interferometry(2).pdf:pdf},
  isbn         = {9283711300},
  keywords     = {Coherence,Forest parameter inversion,InSAR,Interferometry,L-band,Polarimetric interferometry,Radar scattering,SAR,SAR interferometry,Stochastic processes,Terrain mapping,Vectors,coherence,coherence optimization problem,elevated forest canopy,forest structure,general formulation,geophysical measurement technique,geophysical techniques,interferogram,interferometric SAR,interferometric coherence,lakes,land surface,linear combinations,maximization,model,polarimetric SAR interferometry,polarimetric basis transformation,polarimetric interferometry,polarization,radar imaging,radar polarimetry,radar remote sensing,radar theory,remote sensing by radar,scalar interferometry,stochastic scattering model,strong polarization dependency,synthetic aperture radar,synthetic aperture radar (SAR),synthetic aperture radar (SAR) interferometry,tree height,vector wave interferometry},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Cloude1997,
  author       = {S.R. Cloude and E. Pottier},
  title        = {An entropy based classification scheme for land applications of polarimetric {SAR}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1997},
  date         = {1997},
  volume       = {35},
  pages        = {68--78},
  issn         = {{\textless}null{\textgreater}},
  doi          = {10.1109/36.551935},
  abstract     = {In this paper we outline a new scheme for parameterizing polarimetric scattering problems, which has application in the quantitative analysis of polarimetric SAR data. The method relies on an eigenvalue analysis of the coherency matrix and employs a three-level Bernoulli statistical model to generate estimates of the average target scattering matrix parameters from the data. The scattering entropy is a key parameter is determining the randomness in this model and is seen as a funda- mental parameter in assessing the importance of polarimetry in remote sensing problems. We show application of the method to some important classical random media scattering problems and apply it to POLSAR data from the NASA/JPL AIRSAR data base.},
  file         = {:home/baffelli/Library/Cloude, Pottier - 1997 - An entropy based classification scheme for land applications of polarimetric SAR.pdf:pdf},
  isbn         = {0196-2892},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{cloude_review_1996,
  author       = {S.R. Cloude and E. Pottier},
  title        = {A review of target decomposition theorems in radar polarimetry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1996},
  date         = {1996},
  volume       = {34},
  month        = {mar},
  pages        = {498--518},
  issn         = {0196-2892},
  doi          = {10.1109/36.485127},
  url          = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=485127},
  abstract     = {In this paper, we provide a review of the different approaches used for target decomposition theory in radar polarimetry. We classify three main types of theorem; those based on the Mueller matrix and Stokes vector, those using an eigenvector analysis of the covariance or coherency matrix, and those employing coherent decomposition of the scattering matrix. We unify the formulation of these different approaches using transformation theory and an eigenvector analysis. We show how special forms of these decompositions apply for the important case of backscatter from terrain with generic symmetries},
  file         = {:home/baffelli/Library/Cloude, Pottier - 1996 - A review of target decomposition theorems in radar polarimetry.pdf:pdf},
  isbn         = {0196-2892 VO - 34},
  keywords     = {Clouds,Covariance matrix,Eigenvalues and eigenfunctions,Light scattering,Matrix decomposition,Mueller matrix,Particle scattering,Radar scattering,Rayleigh scattering,S-matrix theory,Speckle,Stokes vector,backscatter,coherency matrix,coherent decomposition,covariance matrices,eigenvector analysis,geophysical signal processing,radar cross-sections,radar imaging,radar polarimetry,radar remote sensing,remote sensing by radar,reviews,scattering matrix,target decomposition theorems,terrain,transformation theory},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Coefficients,
  author = {Coefficients, Fresnel},
  title  = {{Supplementary Information 1.}},
  pages  = {1--4},
  file   = {:home/baffelli/Library/Coefficients - Unknown - Supplementary Information 1.pdf:pdf},
}

@InProceedings{Conradsen2001,
  author        = {Conradsen, Knut and Nielsen, Allan Aasbjerg and Schou, Jesper and Skriver, Henning},
  title         = {{Change Detection in Polarimetric SAR Data and the Complex Wishart Distribution}},
  date          = {2001},
  volume        = {00},
  isbn          = {0780370333},
  pages         = {7031--7033},
  doi           = {10.1109/IGARSS.2001.978111},
  journal       = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Covariance matrix,Denmark,Detectors,EMISAR L-band data,Foulum,Hermitian positive definite matrix,L-band,Probability,Radar detection,Statistical distributions,Testing,agricultural fields,agriculture,asymptotic probability,backscattered signal,change detection,complex Wishart distribution,covariance matrices,geophysical signal processing,image recognition,image representation,multi-look fully polarimetric synthetic aperture r,polarimetric SAR data,polarimetric synthetic aperture radar,radar imaging,radar polarimetry,remote sensing by radar,statistical analysis,synthetic aperture radar},
  mendeley-tags = {Covariance matrix,Denmark,Detectors,EMISAR L-band data,Foulum,Hermitian positive definite matrix,L-band,Probability,Radar detection,Statistical distributions,Testing,agricultural fields,agriculture,asymptotic probability,backscattered signal,change detection,complex Wishart distribution,covariance matrices,geophysical signal processing,image recognition,image representation,multi-look fully polarimetric synthetic aperture r,polarimetric SAR data,polarimetric synthetic aperture radar,radar imaging,radar polarimetry,remote sensing by radar,statistical analysis,synthetic aperture radar},
}

@Article{Conradsen2003,
  author        = {Conradsen, Knut and Nielsen, Aasbjerg and Schou, Jesper and Skriver, Henning},
  title         = {{A test statistic in the complex wishart distribution and its application to change detection in polarimetric SAR data}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2003-01},
  volume        = {41},
  pages         = {4--19},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2002.808066},
  abstract      = {When working with multilook fully polarimetric synthetic aperture radar (SAR) data, an appropriate way of representing the backscattered signal consists of the so-called covariance matrix. For each pixel, this is a 3{\&}times;3 Hermitian positive definite matrix that follows a complex Wishart distribution. Based on this distribution, a test statistic for equality of two such matrices and an associated asymptotic probability for obtaining a smaller value of the test statistic are derived and applied successfully to change detection in polarimetric SAR data. In a case study, EMISAR L-band data from April 17, 1998 and May 20, 1998 covering agricultural fields near Foulum, Denmark are used. Multilook full covariance matrix data, azimuthal symmetric data, covariance matrix diagonal-only data, and horizontal-horizontal (HH), vertical-vertical (VV), or horizontal-vertical (HV) data alone can be used. If applied to HH, VV, or HV data alone, the derived test statistic reduces to the well-known gamma likelihood-ratio test statistic. The derived test statistic and the associated significance value can be applied as a line or edge detector in fully polarimetric SAR data also.},
  isbn          = {0196-2892},
  keywords      = {Covariance matrix,Covariance matrix test statistic,Denmark,Detectors,EMISAR,Foulum,Hermitian positive definite matrix,L -band,L-band,Probability,Radar applications,Radar detection,Radar polarimetry,Radar scattering,Remote sensing change detection,Statistical distributions,Terrain mapping,Testing,Vegetation mapping,agricultural fields,backscattered signal,change detection,complex Wishart distribution,geophysical measurement technique,geophysical signal processing,geophysical techniques,land surface,polarimetric SAR,polarimetric synthetic aperture radar,radar imaging,radar polarimetry,radar remote sensing,radar theory,remote sensing by radar,statistical analysis,synthetic aperture radar,test statistic},
  mendeley-tags = {Covariance matrix,Denmark,Detectors,EMISAR,Foulum,Hermitian positive definite matrix,L -band,L-band,Probability,Radar detection,Radar scattering,Statistical distributions,Terrain mapping,Testing,Vegetation mapping,agricultural fields,backscattered signal,change detection,complex Wishart distribution,geophysical measurement technique,geophysical signal processing,geophysical techniques,land surface,polarimetric SAR,polarimetric synthetic aperture radar,radar imaging,radar polarimetry,radar remote sensing,radar theory,remote sensing by radar,statistical analysis,synthetic aperture radar,test statistic},
}

@InProceedings{Corr1998,
  author        = {Corr, D.G. and Rodrigues, A.},
  title         = {{Coherent change detection of vehicle movements}},
  date          = {1998-07},
  volume        = {5},
  isbn          = {0-7803-4403-0},
  pages         = {2451--2453 vol.5},
  doi           = {10.1109/IGARSS.1998.702243},
  abstract      = {The detection of the overland movement of large vehicles has been$\backslash$ninvestigated using coherent change detection techniques applied to$\backslash$nsynthetic aperture radar data. Satellite data with a one day repeat was$\backslash$nused. Initial results indicate that vehicle movements are detectable by$\backslash$ndistinctive low coherence values},
  journal       = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Crops,Intelligent vehicles,Land vehicles,Pixel,Radar detection,Road vehicles,SAR,Satellites,Soil,Vehicle detection,Wind,coherent change detection,grassland,land surface vehicle,large vehicles,low coherence value,measurement technique,military radar,military systems,off the road vehicle,overland movement,radar imaging,radar remote sensing,remote sensing by radar,road vehicle movement,search radar,surveillance,synthetic aperture radar,vehicles},
  mendeley-tags = {Crops,Intelligent vehicles,Land vehicles,Pixel,Radar detection,Road vehicles,SAR,Satellites,Soil,Vehicle detection,Wind,coherent change detection,grassland,land surface vehicle,large vehicles,low coherence value,measurement technique,military radar,military systems,off the road vehicle,overland movement,radar imaging,radar remote sensing,remote sensing by radar,road vehicle movement,search radar,surveillance,synthetic aperture radar,vehicles},
}

@Article{Coupe2009,
  author       = {Coup{\'{e}}, Pierrick and Hellier, Pierre and Kervrann, Charles and Barillot, Christian},
  title        = {{Nonlocal means-based speckle filtering for ultrasound images}},
  journaltitle = {IEEE Transactions on Image Processing},
  date         = {2009},
  volume       = {18},
  pages        = {2221--2229},
  issn         = {10577149},
  doi          = {10.1109/TIP.2009.2024064},
  url          = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=4982678},
  abstract     = {In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the nonlocal (NL)-means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image.},
  isbn         = {1941-0042 (Electronic)$\backslash$r1057-7149 (Linking)},
  keywords     = {Additives,Distance measurement,Image restoration,No Index Terms Provided,Noise,Pixel,Probability density function,Speckle},
  pmid         = {19482578},
}

@Article{Cressie1993,
  author       = {Cressie, Noel A.C.},
  title        = {{Geostatistics}},
  journaltitle = {Statistics for Spatial Data},
  date         = {1993},
  pages        = {29--104},
  file         = {:home/baffelli/Library/Cressie - 1993 - Geostatistics.pdf:pdf},
}

@Article{Cressie1993a,
  author       = {Cressie, Noel A.C.},
  title        = {Spatial Prediction and {Kriging}},
  journaltitle = {Statistics for Spatial Data},
  date         = {1993},
  pages        = {105--209},
  doi          = {10.1002/9781119115151.ch3},
  abstract     = {This chapter contains sections titled:$\backslash$n$\backslash$n$\backslash$n*$\backslash$nScale of Variation$\backslash$n$\backslash$n$\backslash$n*$\backslash$nOrdinary Kriging$\backslash$n$\backslash$n$\backslash$n*$\backslash$nRobust Kriging$\backslash$n$\backslash$n$\backslash$n*$\backslash$nUniversal Kriging$\backslash$n$\backslash$n$\backslash$n*$\backslash$nMedian-Polish Kriging$\backslash$n$\backslash$n$\backslash$n*$\backslash$nGeostatistical Data, Simulated and Real},
  file         = {:home/baffelli/Library/Cressie - 1993 - 03 Spatial Prediction and Kriging.pdf:pdf},
  isbn         = {0-471-00255-0},
}

@Article{Crosetto2011,
  author       = {Crosetto, Michele and Monserrat, Oriol and Cuevas, Mar{\'{i}}a and Crippa, Bruno},
  title        = {{Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement}},
  journaltitle = {Remote Sensing},
  date         = {2011},
  volume       = {3},
  pages        = {305--318},
  issn         = {2072-4292},
  doi          = {10.3390/rs3020305},
  url          = {http://www.mdpi.com/2072-4292/3/2/305/},
  file         = {:home/baffelli/Library/Crosetto et al. - 2011 - Spaceborne Differential SAR Interferometry Data Analysis Tools for Deformation Measurement.pdf:pdf},
}

@Article{Crosetto2016,
  author       = {Michele Crosetto and Oriol Monserrat and Mar{\'{\i}}a Cuevas-Gonz{\'{a}}lez and N{\'{u}}ria Devanth{\'{e}}ry and Bruno Crippa},
  title        = {Persistent Scatterer Interferometry: A review},
  journal      = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  journaltitle = {ISPRS Journal of Photogrammetry and Remote Sensing},
  year         = {2016},
  date         = {2016},
  volume       = {115},
  month        = {may},
  pages        = {78--89},
  issn         = {09242716},
  doi          = {10.1016/j.isprsjprs.2015.10.011},
  abstract     = {Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth's surface over time. Specifically, PSI is a radar-based technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.},
  file         = {:home/baffelli/Library/Crosetto et al. - 2016 - Persistent Scatterer Interferometry A review.pdf:pdf},
  keywords     = {Deformation,Monitoring,Radar,Remote sensing,SAR},
  publisher    = {International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)},
}

@Article{DalbanCanassy2012,
  author       = {Pierre Dalban Canassy and J{\'{e}}r{\^{o}}me Faillettaz and Fabian Walter and Matthias Huss},
  title        = {Seismic activity and surface motion of a steep temperate glacier: a study on {Triftgletscher}, {Switzerland}},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {2012},
  date         = {2012},
  volume       = {58},
  pages        = {513--528},
  issn         = {00221430},
  doi          = {10.3189/2012JoG11J104},
  abstract     = {The tongue of Triftgletscher, Switzerland, is particularly susceptible to major break-off events due to its steep slope. In order to detect precursors of such an event, we monitored the local seismic activity and detected 2426 icequakes with sources located in an area ranging between 2050 and 2350 m a.s.l. Events triggered by cracks and icefalls were recorded, but no precise distinction between the two sources was possible using duration or frequency criteria. Clusters of seismic activity were located and confirmed by visual observations. We performed a surface motion analysis and found that surface motion was driven significantly by runoff changes at a timescale of 2–3 days. By means of a statistical analysis, a power-law behaviour of the released seismic energy distribution was discerned at certain times during the period investigated. Variations in power-law exponent values indicated that low- and high-energy events predominantly occurred during phases of enhanced and reduced surface motion, respectively. Substantial releases of seismic energy likely to signal the glacier recoupling were detected during phases of decreasing runoff. Clues to potential seismic precursors of break-off events are discussed.},
  file         = {:home/baffelli/Library/Dalban Canassy et al. - 2012 - Seismic activity and surface motion of a steep temperate glacier A study on Triftgletscher, Switzerland.pdf:pdf},
  publisher    = {Cambridge University Press ({CUP})},
}

@Article{Dallmann2015,
  author  = {Dallmann, T and Heberling, D},
  title   = {{On the Connection between Jones Matrix and Sinclair Matrix}},
  journal = {Progress In Electromagnetics Research Symposium Proceedings},
  date    = {2015},
  pages   = {258--262},
  file    = {:home/baffelli/Library/Dallmann, Heberling - 2015 - On the Connection between Jones Matrix and Sinclair Matrix.pdf:pdf},
}

@Article{D-baug2017,
  author = {D-baug, Workshop},
  title  = {{Monitoring and Model- ling for Real-Time Con- trol and Intervention}},
  date   = {2017},
  pages  = {1--35},
  file   = {:home/baffelli/Library/D-baug - 2017 - Monitoring and Model- ling for Real-Time Con- trol and Intervention › ›.pdf:pdf},
}

@InProceedings{DeCesare1997,
  author    = {{De Cesare}, L. and Myers, D. E. and Posa, D.},
  title     = {Spatial-Temporal Modeling {SO2} in Milan District},
  booktitle = {Proceedings of the International Geostatistical Congress},
  year      = {1996},
  date      = {1997},
  isbn      = {0792344952},
  pages     = {1031--1042},
  url       = {http://books.google.com/books?id=PbwjK4PyFd4C{\&}pgis=1},
  abstract  = {The papers in this volume provide a comprehensive account of the current methods and work in geostatistics, including recent theoretical developments and applications. Topics featured include: stochastic simulations, space-time modelling, and Bayesian framework.},
  file      = {:home/baffelli/Library/De Cesare, Myers, Posa - 1997 - Spatial-Temporal Modeling SO2 in Milan District.pdf:pdf},
}

@Article{Dejean2008,
  author       = {Dejean, L and Pastor, Dominique and Quellec, JM and Chabah, Myriam and Bon, Nicolas},
  title        = {{The clutter SIRP and Gaussian models: a brief overview and a comparison}},
  journaltitle = {Radar Clutter Modelling, 2008 IET Seminar on},
  date         = {2008},
  pages        = {41--47},
  doi          = {10.1049/ic:20080148},
  url          = {http://digital-library.theiet.org/content/conferences/10.1049/ic{\_}20080148},
  file         = {:home/baffelli/Library/Dejean et al. - 2008 - The clutter SIRP and Gaussian models a brief overview and a comparison.pdf:pdf},
  isbn         = {9780863419010},
}

@InProceedings{Deledalle2010,
  author       = {Deledalle, C.-A. and Tupin, Florence and Denis, Lo{\"{i}}c},
  title        = {{A non-local approach for SAR and interferometric SAR denoising}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2010},
  publisher    = {IEEE},
  isbn         = {9781424495665},
  pages        = {714--717},
  doi          = {10.1109/IGARSS.2010.5654217},
  abstract     = {Recently, non-local approaches have proved very pow- erful for image$\backslash$ndenoising. Unlike local filters, the non- local (NL) means introduced$\backslash$nin [1] decrease the noise while preserving well the resolution. In$\backslash$nthe proposed paper, we suggest the use of a non-local approach to$\backslash$nestimate single-look SAR reflectivity images or to construct SAR$\backslash$ninterferograms. SAR interferogram con- struction refers to the joint$\backslash$nestimation of the reflectivity, phase difference and coherence image$\backslash$nfrom a pair of two co-registered single-look complex SAR images.$\backslash$nThe weighted maximum likelihood is introduced as a gener- alization$\backslash$nof the weighted average performed in the NL means. We propose to$\backslash$nset the weights according to the probability of similarity which$\backslash$nprovides an extension of the Euclidean distance used in the NL means.$\backslash$nExperi- ments and results are presented to show the efficiency of$\backslash$nthe proposed approach.},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@InProceedings{Deledalle2010a,
  author        = {Charles-Alban Deledalle and Florence Tupin and Loic Denis},
  title         = {Polarimetric {SAR} estimation based on non-local means},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year          = {2010},
  date          = {2010-07},
  publisher     = {{IEEE}},
  month         = {jul},
  isbn          = {978-1-4244-9565-8},
  pages         = {2515--2518},
  doi           = {10.1109/IGARSS.2010.5653936},
  abstract      = {During the past few years, the non-local (NL)means have proved their$\backslash$nefficiency for image denoising. This approach assumes there exist$\backslash$nenough redundant patterns in images to be used for noise reduction.$\backslash$nWe suggest that the same assumption can be done for polarimetric$\backslash$nsynthetic aperture radar (PolSAR) images. In its original version,$\backslash$nthe NLmeans deal with additive white Gaussian noise, but several$\backslash$nextensions have been proposed for non-Gaussian noise. This paper$\backslash$napplies the methodology proposed in ato PolSAR data. The proposed$\backslash$nfilter seems to deal well with the statistical properties of speckle$\backslash$nnoise and themulti-dimensional nature of such data. Results are given$\backslash$non synthetic and L-Band E-SAR data to validate the proposed method.},
  issn          = {2153-6996},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {AWGN,Covariance matrix,Entropy,Estimation,Image color a,Image color analysis,L-Band E-SAR data,NL means,Noise,Noise measurement,Noise reduction,Non local means,Pixel,PolSAR images,Speckle,additive white Gaussian noise,estimation theory,image denoising,maximum likelihood,nonGaussian noise,nonlocal means,polarimetric SAR estimation,polarimetric synthetic aperture radar (POLSAR),polarimetric synthetic aperture radar images,radar imaging,redundant patterns,speckle noise,statistical analysis,statistical property,synthetic aperture radar},
  mendeley-tags = {AWGN,Covariance matrix,Entropy,Estimation,Image color analysis,L-Band E-SAR data,NL means,Noise,Noise measurement,Noise reduction,Non local means,Pixel,PolSAR images,Speckle,additive white Gaussian noise,estimation theory,image denoising,maximum likelihood,nonGaussian noise,nonlocal means,polarimetric SAR estimation,polarimetric synthetic aperture radar (POLSAR),polarimetric synthetic aperture radar images,radar imaging,redundant patterns,speckle noise,statistical analysis,statistical property,synthetic aperture radar},
}

@Article{Dematteis2017,
  author       = {Niccol{\`{o}} Dematteis and Guido Luzi and Daniele Giordan and Francesco Zucca and Paolo Allasia},
  title        = {Monitoring Alpine glacier surface deformations with {GB}-{SAR}},
  journal      = {Remote Sensing Letters},
  journaltitle = {Remote Sensing Letters},
  year         = {2017},
  date         = {2017},
  volume       = {8},
  month        = {jun},
  pages        = {947--956},
  issn         = {2150-704X},
  doi          = {10.1080/2150704X.2017.1335905},
  file         = {:home/baffelli/Library/Dematteis et al. - 2017 - Monitoring Alpine glacier surface deformations with GB-SAR.pdf:pdf},
  publisher    = {Informa {UK} Limited},
}

@Article{Dixon2012,
  author       = {Timothy H. Dixon and Denis Voytenko and Chad Lembke and Santiago de la Pe{\~{n}}a and Ian Howat and Noel Gourmelen and Charles Werner and Björn Oddsson},
  title        = {Emerging technology monitors ice-sea interface at outlet glaciers},
  journal      = {Eos, Transactions American Geophysical Union},
  journaltitle = {Eos},
  year         = {2012},
  date         = {2012},
  volume       = {93},
  month        = {nov},
  pages        = {497--498},
  issn         = {00963941},
  doi          = {10.1029/2012EO480001},
  abstract     = {Recent melting in Greenland and Antarctica has led to concerns about the long-term stability of these ice sheets and their potential contributions to future sea level rise. Marine-terminating outlet glaciers play a key role in the dynamics of these ice sheets; recent mass losses are likely related to increased influx of warmer water to the base of outlet glaciers, as evidenced by the fact that changes in ocean currents, calving front retreats, glacial thinning, mass redistribution based on satellite gravity data, and accelerating coastal uplift are roughly concurrent [e.g., Holland et al., 2008; Wouters et al., 2008; Jiang et al., 2010; Straneo et al., 2012; Bevis et al., 2012]. However, collecting quantitative measurements within the dynamic environment of marine outlet glaciers is challenging. Oceanographic measurements are limited in iceberg-laden fjords. Measuring ice flow speeds near the calving front is similarly challenging; satellite methods lack temporal resolution (satellite revisit times are several days or longer), while GPS gives limited spatial resolution, a problem for assessing changes near the highly variable calving front.},
  file         = {:home/baffelli/Library/Dixon et al. - 2012 - Emerging technology monitors ice-sea interface at outlet glaciers.pdf:pdf},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Documents2008,
  author       = {Documents, Reference and Personnel, Key},
  title        = {{Reference Documents}},
  journaltitle = {Business},
  date         = {2008},
  pages        = {7--8},
  doi          = {10.1787/9789264101630-5-en},
  file         = {:home/baffelli/Library/Documents, Personnel - 2008 - Reference Documents.pdf:pdf},
  isbn         = {9789264101623},
}

@Article{Dogan2014,
  author        = {Dogan, Ozan and Perissin, Daniele},
  title         = {{Detection of Multitransition Abrupt Changes in Multitemporal SAR Images}},
  journaltitle  = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  date          = {2014},
  volume        = {7},
  pages         = {3239--3247},
  issn          = {1939-1404},
  doi           = {10.1109/JSTARS.2013.2295357},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6704799},
  keywords      = {Analysis of variance (ANOVA),change detection,synthetic aperture radar (SAR),time-series analysis},
  mendeley-tags = {Analysis of variance (ANOVA),change detection,synthetic aperture radar (SAR),time-series analysis},
}

@Article{Doin2011,
  author       = {Doin, Marie-Pierre and Lodge, Felicity and Guillaso, St{\'{e}}phane and Jolivet, Romain and Lasserre, C{\'{e}}cile and Ducret, Gabriel and Grandin, Raphael and Pathier, Erwan and Pinel, Virginie},
  title        = {{Presentation of the small baseline NSBAS processing chain on a case example: the Etna deformation monitoring from 2003 to 2010 using Envisat data}},
  journaltitle = {Proceedings of the ESA 'Fringe 2011 Workshop', Frascati, Italy, (19-23 September 2011)},
  date         = {2011},
  volume       = {2011},
  pages        = {19--23},
  url          = {http://www.geologie.ens.fr/{~}grandin/upload/Doin{\_}2012{\_}NSBAS.pdf{\%}5Cnhttp://www.gps.caltech.edu/{~}jolivetr/jolivetr/Publications{\_}files/Proceedings{\_}of{\_}the{\_}Fringe{\_}symposium{\_}2011{\_}Doin.pdf},
  abstract     = {We assemble a processing chain that handles InSAR computation from raw data to time series analysis. A large part of the chain (from raw data to geocoded un- wrapped interferograms) is based on ROI PAC modules (Rosen et al., 2004), with original routines rearranged and combined with new routines to process in series and in a common radar geometry all SAR images and interferograms. A new feature of the software is the range-dependent spectral filtering to improve coherence in interferograms with long spatial baselines. Additional components include a module to estimate and remove digital elevation model errors before unwrapping, a mod- ule to mitigate the effects of the atmospheric phase delay and remove residual orbit errors, and a module to con- struct the phase change time series from small baseline interferograms (Berardino et al. 2002). This paper de- scribes the main elements of the processing chain and presents an example of application of the software using a data set from the ENVISAT mission covering the Etna volcano.},
  file         = {:home/baffelli/Library/Doin et al. - 2011 - Presentation of the small baseline NSBAS processing chain on a case example the Etna deformation monitoring from 20.pdf:pdf},
  keywords     = {etna,in the next sections,insar,large areas and in,natural settings,of the chain and,refer to,sbas,sient ground motion of,small amplitude,synthethize the various features,taking place over,time series analysis,we},
}

@Article{Emardson2003,
  author       = {T. R. Emardson and M. Simons and F. H. Webb},
  title        = {Neutral atmospheric delay in interferometric synthetic aperture radar applications: Statistical description and mitigation},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {2003},
  date         = {2003},
  volume       = {108},
  month        = {may},
  pages        = {2231},
  issn         = {0148-0227},
  doi          = {10.1029/2002jb001781},
  abstract     = {Variations in the refractive index of the atmosphere cause variations in satellite-based interferometric synthetic aperture radar (InSAR) observations. We can mitigate tropospheric effects by averaging N-independent interferograms. Because the neutral atmosphere is uncorrelated at timescales longer than 1 day, using this technique statistically reduces the variance, $\sigma$2, of the noise by a factor of N. Using zenith neutral atmospheric delays from Global Positioning System (GPS) data from the Southern California Integrated GPS Network, we find that the average variance depends on the distance between observations, L, and height difference, H, as $\sigma$ = c L$\alpha$ + kH with estimated values for c, $\alpha$, and k of about 2.5, 0.5, and 4.8, respectively, where $\sigma$ is in mm and L and H are in km. We expect that the value of $\alpha$ is largely site-independent but the value of c will depend on the water vapor variability of the area of interest. This model is valid over a range of L between approximately 10 and 800 km. Height differences between 0 and 3 km have been used in this analysis. For distances of 100 and 10 km with negligible height differences, $\sigma$ is estimated to be approximately 25 and 8 mm, respectively. For a given orbit revisit time and image archive duration, we calculate the number and duration (assumed constant) of interferograms required to achieve a desired sensitivity to deformation rate at a given length scale. Assuming neutral atmosphere is the dominant source of noise, a 30° look angle, and an image revisit time of 7 days, detection of a deformation rate of 1 mm yr−1 over distances of 10 km requires about 2.2 years of continuous observations. Given our results, we suggest a data covariance structure to use when using InSAR data to constrain geophysical models.},
  file         = {:home/baffelli/Library/Emardson, Simons, Webb - 2003 - Neutral atmospheric delay in interferometric synthetic aperture radar applications Statistical descripti.pdf:pdf},
  isbn         = {2156-2202},
  keywords     = {1208 Geodesy and Gravity: Crustal movements—intrap,1243 Space geodetic surveys,1244 Standards and absolute measurements,1294 Instruments and techniques,InSAR,crustal deformation,radar interferometry,troposphere},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Enjiu2013,
  author       = {Enjiu, Rodrigo Kenji and Perotoni, Marcelo Bender},
  title        = {Slotted waveguide antenna design using {3D EM} simulation},
  journaltitle = {Microwave Journal},
  year         = {2013},
  date         = {2013},
  issn         = {01926225},
  file         = {:home/baffelli/Library/Enjiu, Perotoni - 2013 - Slotted waveguide antenna design using 3D EM simulation.pdf:pdf},
  keywords     = {3D em simulation,antenna,slotted waveguide anten},
}

@InProceedings{Erten2011,
  author        = {Erten, Esra and Chesnokova, Olga and Rossi, Cristian and Hajnsek, Irena},
  title         = {{A polarimetric temporal scene parameter and its application to change detection}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {2011-07},
  isbn          = {9781457710056},
  pages         = {1091--1094},
  doi           = {10.1109/IGARSS.2011.6049386},
  abstract      = {The contribution of Polarimetric Synthetic Aperture Radar (PolSAR) images compared with the single-channel SAR in terms of temporal scene characterization has been found and described to add valuable information in the literature. In this paper, a new PolSAR change detector which makes use of Kullback-Leibler divergence is described. Kullback-Leibler divergence (KL-divergence) measures the amount of information in common between coherent temporal multi-channel polarimetric SAR acquisitions. Although in this paper KL-divergence measure has analytically been derived for temporal polarimetric SAR images based on complex Wishart process in time, since the mathematical formulation is general, it can be implemented into any kind of multivariate remote sensing data such as multi-spectral optical and interferometric images. KL-divergence measure is also simplified to give an explicit expressions for temporal single channel SAR images. The new results are simple, easy to be used, and superior in providing detailed structure.},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Detectors,Entropy,Information theory,KL-divergence,Kullback-Leibler divergence,POLSAR,PolSAR,PolSAR change detector,backscatter,change detection,coherent temporal multichannel polarimetric SAR ac,complex Wishart process,information theory,interferometric image,measurement,multivariate remote sensing data,polarimetric synthetic aperture radar images,polarimetric temporal scene parameter,radar imaging,remote sensing,synthetic aperture radar,temporal polarimetric SAR image,temporal single channel SAR image},
  mendeley-tags = {Detectors,Entropy,Information theory,KL-divergence,Kullback-Leibler divergence,POLSAR,PolSAR change detector,backscatter,change detection,coherent temporal multichannel polarimetric SAR ac,complex Wishart process,interferometric image,measurement,multivariate remote sensing data,polarimetric synthetic aperture radar images,polarimetric temporal scene parameter,radar imaging,remote sensing,synthetic aperture radar,temporal polarimetric SAR image,temporal single channel SAR image},
}

@Article{Erten2012,
  author        = {Erten, Esra and Reigber, Andreas and Ferro-Famil, Laurent and Hellwich, Olaf},
  title         = {{A new coherent similarity measure for temporal multichannel scene characterization}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2012-07},
  volume        = {50},
  pages         = {2839--2851},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2011.2174155},
  abstract      = {This paper proposes a new method for a measure of coherent similarity between temporal multichannel synthetic aperture radar (SAR) images and its implementation to change detection application. The method is based on mutual infor- mation (MI) from information theory. The MI measures the amount of information in common between coherent temporal multichannel SAR acquisitions. In order to develop an algo- rithm for all kinds of SAR images, such as interferometric SAR, polarimetric–interferometric SAR (PolInSAR), and partial PolIn- SAR, first, the joint density function of temporal multichannel images based on their second-order statistics has been derived. Then, the derived joint density function is used to calculate an analytical expression for the MI between temporal images, which is assumed to be maximal if the temporal images are identical. Although, in this paper, a new coherent similarity measure has analytically been derived for temporal polarimetric SAR images based on complexWishart process in time, since the mathematical formulation is general, it can equally well be implemented into any kind of multivariate remote sensing data, such as multispec- tral optical and interferometric images after small continuation. This derived quantity has been implemented for change detection application whose aim is to characterize the temporal behavior of the acquisitions. A comparison between the proposed and the other well-known change detection methods by means of scene characterization is shown, describing the advantages due to the fact that the proposed change detector involves almost every facet of applied change detection.},
  keywords      = {Change detection algorithms,Covariance matrix,Density functional theory,Estimation,Information theory,Joints,Parameter estimation,PolInSAR,Vectors,change detection application,coherent similarity measure,coherent temporal multichannel SAR acquisitions,complex Wishart process,correlation,geophysical image processing,interferometric SAR,interferometric images,joint density function,multispectral optical images,multivariate remote sensing data,mutual information,parameter estimation,partial PolInSAR,polarimetric synthetic aperture radar,polarimetric-interferometric SAR,radar imaging,radar interferometry,radar polarimetry,remote sensing by radar,second order statistics,statistical analysis,synthetic aperture radar,synthetic aperture radar images,temporal multichannel SAR images,temporal multichannel scene characterization,temporal polarimetric SAR images},
  mendeley-tags = {Change detection algorithms,Covariance matrix,Density functional theory,Estimation,Information theory,Joints,Parameter estimation,PolInSAR,Vectors,change detection application,coherent similarity measure,coherent temporal multichannel SAR acquisitions,complex Wishart process,correlation,geophysical image processing,interferometric SAR,interferometric images,joint density function,multispectral optical images,multivariate remote sensing data,mutual information,partial PolInSAR,polarimetric synthetic aperture radar,polarimetric-interferometric SAR,radar imaging,radar interferometry,radar polarimetry,remote sensing by radar,second order statistics,statistical analysis,synthetic aperture radar,synthetic aperture radar images,temporal multichannel SAR images,temporal multichannel scene characterization,temporal polarimetric SAR images},
}

@InProceedings{Even2010,
  author    = {Even, Markus and Schunert, Alexander and Schulz, Karsten and Soergel, Uwe},
  title     = {{Atmospheric phase screen-estimation for PSInSAR applied to TerraSAR-X high resolution spotlight-data}},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date      = {2010-07},
  publisher = {IEEE},
  isbn      = {978-1-4244-9565-8},
  pages     = {2928--2931},
  doi       = {10.1109/IGARSS.2010.5649096},
  url       = {http://ieeexplore.ieee.org/document/5649096/},
  file      = {:home/baffelli/Library/Stein - 1986 - A simple model for spatial-temporal processes.pdf:pdf},
}

@Article{Fabregas2012,
  author       = {Fabregas, Xavier and Iglesias, Rub{\'{e}}n and Aguasca, Albert},
  title        = {A new approach for atmospheric phase screen compensation in ground-based {SAR} over areas with steep topography},
  journaltitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date         = {2012},
  pages        = {12--15},
  issn         = {21974403},
  file         = {:home/baffelli/Library/Fabregas, Iglesias, Aguasca - 2012 - A new approach for atmospheric phase screen compensation in ground-based SAR over areas with steep.pdf:pdf},
  isbn         = {3800734044},
}

@InProceedings{Fabrizio,
  author    = {Fabrizio, G. A. and Gershman, A. B. and Turley, M. D.},
  title     = {{Non-stationary interference cancellation in HF surface wave radar}},
  booktitle = {Proceedings of the International Conference on Radar},
  year      = {2003},
  publisher = {IEEE},
  isbn      = {0-7803-7870-9},
  pages     = {672--677},
  doi       = {10.1109/RADAR.2003.1278823},
  url       = {http://ieeexplore.ieee.org/document/1278823/},
}

@InProceedings{Fabrizio2007,
  author    = {Fabrizio, Giuseppe and Holdsworth, David and Farina, Alfonso},
  title     = {{Experimental HF radar trial of real-time STAP}},
  booktitle = {2007 International Waveform Diversity and Design Conference, WDD},
  date      = {2007},
  isbn      = {1424412765},
  pages     = {316--320},
  doi       = {10.1109/WDDC.2007.4339434},
  abstract  = {An alternative multi-static HF radar architecture, known as the Forward-Based Receiver Augmentation (FBRA) system, has been developed and tested by the Defence Science and Technology Organization [1]. The experimental system has performed beyond expectations in a number of trials involving targets of interest. This is not only due to the impressive hardware capabilities, but also the advanced signal processing for clutter and interference mitigation, particularly STAP which was shown to be indispensable for the successful operation of the system. This paper describes the real-time STAP algorithm in the FBRA system, and demonstrates its experimental detection performance on a cooperative aircraft target with flight path "ground truth" data available from on-board GPS logging equipment.},
}

@InProceedings{Fabrizio2007a,
  author    = {Fabrizio, Giuseppe and Holdsworth, David and Farina, Alfonso},
  title     = {{Experimental HF radar trial of real-time STAP}},
  booktitle = {2007 International Waveform Diversity and Design Conference, WDD},
  date      = {2007},
  isbn      = {1424412765},
  pages     = {316--320},
  doi       = {10.1109/WDDC.2007.4339434},
  abstract  = {An alternative multi-static HF radar architecture, known as the Forward-Based Receiver Augmentation (FBRA) system, has been developed and tested by the Defence Science and Technology Organization [1]. The experimental system has performed beyond expectations in a number of trials involving targets of interest. This is not only due to the impressive hardware capabilities, but also the advanced signal processing for clutter and interference mitigation, particularly STAP which was shown to be indispensable for the successful operation of the system. This paper describes the real-time STAP algorithm in the FBRA system, and demonstrates its experimental detection performance on a cooperative aircraft target with flight path "ground truth" data available from on-board GPS logging equipment.},
}

@Article{Faillettaz2015,
  author       = {J{\'{e}}rome Faillettaz and Martin Funk and Christian Vincent},
  title        = {Avalanching glacier instabilities: Review on processes and early warning perspectives},
  journal      = {Reviews of Geophysics},
  journaltitle = {Reviews of Geophysics},
  year         = {2015},
  date         = {2015},
  volume       = {53},
  month        = {may},
  pages        = {203--224},
  issn         = {87551209},
  doi          = {10.1002/2014rg000466},
  abstract     = {Avalanching glacier instabilities are gravity-driven rupture phenomena that might cause major disasters, especially when they are at the origin of a chain of processes. Reliably forecasting such events combined with a timely evacuation of endangered inhabited areas often constitute the most efficient action. Recently, considerable efforts in monitoring, analyzing, and modeling such phenomena have led to significant advances in destabilization process understanding, improving early warning perspectives. The purpose of this paper is to review the recent progress in this domain. Three different types of instabilities can be identified depending on the thermal properties of the ice/bed interface. If cold (1), the maturation of the rupture is associated with a typical time evolution of surface velocities and passive seismic activity. A prediction of the final break off is possible using these precursory signs. For the two other types, water plays a key role in the development of the instability. If the ice/bed interface is partly temperate (2), the presence of meltwater may reduce the basal resistance, which promotes the instability. No clear and easily detectable precursory signs are known in this case, and the only way to infer any potential instability is to monitor the temporal evolution of the thermal regime. The last type of instability (3) concerns steep temperate glacier tongues switching for several days/weeks during the melting season into a so-called “active phase” followed in rare cases by a major break-off event. Although the prediction of such events is still far from being achievable, critical conditions promoting the final instability can be identified.},
  file         = {:home/baffelli/Library/Faillettaz, Funk, Vincent - 2015 - Avalanching glacier instabilities Review on processes and early warning perspectives.pdf:pdf},
  keywords     = {10.1002/2014RG000466 and glacier hazards,early warning,glacier monitoring,ice avalanche,icequakes},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Faillettaz2015a,
  author       = {Faillettaz, J{\'{e}}rome and Funk, Martin and Vincent, Christian},
  title        = {{Avalanching glacier instabilities: Review on processes and early warning perspectives}},
  journaltitle = {Reviews of Geophysics},
  date         = {2015-06},
  language     = {en},
  volume       = {53},
  pages        = {203--224},
  issn         = {87551209},
  doi          = {10.1002/2014RG000466},
  file         = {:home/baffelli/Library/Faillettaz, Funk, Vincent - 2015 - Avalanching glacier instabilities Review on processes and early warning perspectives.html:html},
  keywords     = {10.1002/2014RG000466 and glacier hazards,early warning,glacier monitoring,ice avalanche,icequakes},
  shorttitle   = {Avalanching glacier instabilities},
}

@Article{Faillettaz2008,
  author       = {J{\'{e}}rome Faillettaz and Antoine Pralong and Martin Funk and Nicholas Deichmann},
  title        = {Evidence of log-periodic oscillations and increasing icequake activity during the breaking-off of large ice masses},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {2008},
  date         = {2008-12},
  language     = {en},
  volume       = {54},
  pages        = {725--737},
  issn         = {00221430},
  doi          = {10.3189/002214308786570845},
  url          = {http://openurl.ingenta.com/content/xref?genre=article{\&}issn=0022-1430{\&}volume=54{\&}issue=187{\&}spage=725 http://www.ingentaconnect.com/content/igsoc/jog/2008/00000054/00000187/art00016},
  abstract     = {In 1973, surface velocities were measured for the first time on an unstable hanging glacier to predict its collapse. The observed velocities have been shown to increase as a power-law function of time up to infinity at the theoretical time of failure (known as 'finite time singularity'). This is the characteristic signature of critical phenomena and has been observed in the case of various other naturally occurring ruptures such as earthquakes, landslides and snow avalanches. Recent velocity measurements performed on Weisshorn and M{\"{o}}nch hanging glaciers, Switzerland, confirmed this behaviour, while log-periodic oscillations superimposed on this general acceleration were also detected. Despite different rupture mechanisms in both cases, the log frequency of the oscillations is shown to be the same. The seismic activity was recorded near the unstable Weisshorn hanging glacier, simultaneously with the velocity measurements. Results show dramatically increasing icequake activity 3 days before the final collapse. Combined motion-seismic monitoring seems to be a promising way to accurately predict the breaking-off of hanging glaciers. Such a combined analysis is also useful for capturing the physical mechanisms of rupture in natural heterogeneous materials.},
  file         = {:home/baffelli/Library/Faillettaz et al. - 2008 - Evidence of log-periodic oscillations and increasing icequake activity during the breaking-off of large ice m.pdf:pdf},
  isbn         = {0022-1430},
  publisher    = {Cambridge University Press ({CUP})},
}

@Article{Fawcett2006,
  author        = {Fawcett, Tom},
  title         = {{An introduction to ROC analysis}},
  journaltitle  = {Pattern Recognition Letters},
  date          = {2006-06},
  volume        = {27},
  pages         = {861--874},
  issn          = {01678655},
  doi           = {10.1016/j.patrec.2005.10.010},
  abstract      = {Receiver operating characteristics (ROC) graphs are useful for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been used increasingly in machine learning and data mining research. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research. ?? 2005 Elsevier B.V. All rights reserved.},
  isbn          = {226},
  keywords      = {Classifier evaluation,Evaluation metrics,ROC analysis},
  mendeley-tags = {Classifier evaluation,Evaluation metrics,ROC analysis},
  pmid          = {9820922},
}

@Article{Feigl1998,
  author    = {Didier Massonnet and Kurt L. Feigl},
  title     = {Radar interferometry and its application to changes in the {Earth}'s surface},
  journal   = {Reviews of Geophysics},
  year      = {1998},
  date      = {1998},
  volume    = {36},
  number    = {4},
  month     = {nov},
  pages     = {441--500},
  doi       = {10.1029/97rg03139},
  file      = {:home/baffelli/Library/Feigl - 1998 - Radar interferometry and its application to changes in the Earth's surface.pdf:pdf},
  keywords  = {http://dx.doi.org/10.1029/97RG03139, doi:10.1029/9},
  publisher = {American Geophysical Union ({AGU})},
}

@Article{Ferretti2011,
  author       = {Alessandro Ferretti and Alfio Fumagalli and Fabrizio Novali and Claudio Prati and Fabio Rocca and Alessio Rucci},
  title        = {A New Algorithm for Processing Interferometric Data-Stacks: {Squee}{SAR}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2011},
  date         = {2011},
  volume       = {49},
  month        = {sep},
  pages        = {3460--3470},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2011.2124465},
  abstract     = {Permanent Scatterer SAR Interferometry (PSInSAR) aims to identify coherent radar targets exhibiting high phase stability over the entire observation time period. These targets often correspond to point-wise, man-made objects widely available over a city, but less present in non-urban areas. To overcome the limits of PSInSAR, analysis of interferometric data-stacks should aim at extracting geophysical parameters not only from point-wise deterministic objects (i.e., PS), but also from distributed scatterers (DS). Rather than developing hybrid processing chains where two or more algorithms are applied to the same data-stack, and results are then combined, in this paper we introduce a new approach, SqueeSAR, to jointly process PS and DS, taking into account their different statistical behavior. As it will be shown, PS and DS can be jointly processed without the need for significant changes to the traditional PSInSAR processing chain and without the need to unwrap hundreds of interferograms, provided that the coherence matrix associated with each DS is properly {\&}{\#}x201C;squeezed{\&}{\#}x201D; to provide a vector of optimum (wrapped) phase values. Results on real SAR data, acquired over an Alpine area, challenging for any InSAR analysis, confirm the effectiveness of this new approach.},
  file         = {:home/baffelli/Library/Ferretti et al. - 2011 - A new algorithm for processing interferometric data-stacks SqueeSAR.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Coherence matrix,InSAR,distributed scatterers (DS),permanent scatterers,space-adaptive filtering},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Book{Ferretti2007b,
  author = {Ferretti, Alessandro and Monti-Guarnieri, Andrea and Prati, Claudio},
  title  = {{InSAR Principles-Guidelines for SAR Interferometry Processing and Interpretation}},
  date   = {2007},
  volume = {19},
  isbn   = {9290922338},
  pages  = {48},
  url    = {http://www.esa.int/esapub/tm/tm19/TM-19{\_}ptA.pdf{\%}5Cnhttp://adsabs.harvard.edu/abs/2007ESATM..19.....F},
  file   = {:home/baffelli/Library/Ferretti, Monti-Guarnieri, Prati - 2007 - InSAR Principles-Guidelines for SAR Interferometry Processing and Interpretation.pdf:pdf},
}

@Article{Ferretti2007,
  author       = {Ferretti, Alessandro and Monti-guarnieri, Andrea and Prati, Claudio and Rocca, Fabio and Fletcher, K},
  title        = {{InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part B}},
  journaltitle = {Esa},
  date         = {2007},
  pages        = {71},
  url          = {papers://29803081-7a18-4199-a903-38c6fcf8334a/Paper/p12443},
  file         = {:home/baffelli/Library/Fletcher - 2007 - InSAR Principles Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part C(2).pdf:pdf;:home/baffelli/Library/Ferretti et al. - 2007 - InSAR Principles Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part B.pdf:pdf;:home/baffelli/Library/Ferretti et al. - 2007 - InSAR Principles Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part B.pdf:pdf},
  isbn         = {92-9092-233-8},
}

@Article{Ferretti2001,
  author        = {A. Ferretti and C. Prati and F. Rocca},
  title         = {Permanent scatterers in {SAR} interferometry},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2001},
  date          = {2001},
  volume        = {39},
  pages         = {8--20},
  issn          = {01962892},
  doi           = {10.1109/36.898661},
  abstract      = {Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used},
  file          = {:home/baffelli/Library/Ferretti, Prati, Rocca - 2001 - Permanent scatterers in SAR interferometry.pdf:pdf},
  isbn          = {01962892},
  keywords      = {Decorrelation,Image reconstruction,Image resolution,InSAR,Interferometry,Monitoring,Motion detection,Motion estimation,SAR interferometry,Scattering,Surface reconstruction,Surface topography,Terrain mapping,atmospheric disturbance,atmospheric phase screen,decorrelation,differential interferometry,geodesy,geometrical decorrelation,geophysical measurement technique,geophysical techniques,image resolution,land surface topography,permanent scatterer,radar remote sensing,remote sensing by radar,stable natural reflector,surface deformation monitoring,synthetic aperture radar,terrain mapping,topographic profile reconstruction,topography (Earth)},
  mendeley-tags = {Image reconstruction,InSAR,Interferometry,Monitoring,Motion detection,Motion estimation,SAR interferometry,Scattering,Surface reconstruction,Surface topography,Terrain mapping,atmospheric disturbance,atmospheric phase screen,decorrelation,differential interferometry,geodesy,geometrical decorrelation,geophysical measurement technique,geophysical techniques,image resolution,land surface topography,permanent scatterer,radar remote sensing,remote sensing by radar,stable natural reflector,surface deformation monitoring,synthetic aperture radar,topographic profile reconstruction,topography (Earth)},
  pmid          = {6754614},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Ferretti2000,
  author       = {A. Ferretti and C. Prati and F. Rocca},
  title        = {Nonlinear subsidence rate estimation using permanent scatterers in differential {SAR} interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2000},
  date         = {2000},
  volume       = {38},
  pages        = {2202--2212},
  issn         = {0196-2892},
  doi          = {10.1109/36.868878},
  abstract     = {Discrete and temporarily stable natural reflectors or permanent$\backslash$nscatterers (PS) can be identified from long temporal series of$\backslash$ninterferometric SAR images even with baselines larger than the so-called$\backslash$ncritical baseline. This subset of image pixels can be exploited$\backslash$nsuccessfully for high accuracy differential measurements. The authors$\backslash$ndiscuss the use of PS in urban areas, like Pomona, CA, showing$\backslash$nsubsidence and absidence effects. A new approach to the estimation of$\backslash$nthe atmospheric phase contributions, and the local displacement field is$\backslash$nproposed based on simple statistical assumptions. New solutions are$\backslash$npresented in order to cope with nonlinear motion of the targets},
  file         = {:home/baffelli/Library/Ferretti, Prati, Rocca - 2000 - Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry.pdf:pdf},
  isbn         = {0196-2892},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Ferretti1997,
  author       = {Ferretti, A. and Prati, C. and Rocca, F. and {Monti Guarnieri}, A.},
  title        = {{Multibaseline SAR interferometry for automatic DEM reconstruction}},
  journaltitle = {European Space Agency, (Special Publication) ESA SP},
  date         = {1997},
  pages        = {1809--1820},
  issn         = {03796566},
  file         = {:home/baffelli/Library/Ferretti et al. - 1997 - Multibaseline SAR interferometry for automatic DEM reconstruction.pdf:pdf},
  keywords     = {Atmospheric Effects,Coherence Estimation,DEM reconstruction,Phase Unwrapping,SAR-Interferometry},
}

@Article{Ferro-famil2008,
  author        = {Ferro-famil, Laurent and Neumann, Maxim},
  title         = {{Recent Advances in the Derivation of POL-inSAR Statistics : Study and Applications .}},
  journaltitle  = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date          = {2008},
  pages         = {1--4},
  abstract      = {This paper introduces recent developments in the derivation of POL-inSAR$\backslash$ndata statistics. Maximum likelihood procedures are provided to test widely$\backslash$nencountered assumptions on the structure of POL-inSAR data sets acquired$\backslash$nover natural environments. These hypothesis concern the evolution of the$\backslash$nPOLSAR information between two interferometric acquisitions, the equality$\backslash$nof the optimal POL-inSAR projection vectors and the presence of reflection$\backslash$nsymmetry. In each of these particular cases, maximum likelihood tests and$\backslash$nestimates of POL-inSAR quantities are derived. The proposed approach is$\backslash$nthen tested over SAR data acquired by the DLR ESAR sensor at L band.},
  keywords      = {Coherence,Optimized production technology,Symmetric matrices,maximum likelihood estimation,remote sensing},
  mendeley-tags = {Coherence,Optimized production technology,Symmetric matrices,maximum likelihood estimation,remote sensing},
}

@Article{Fielding1998,
  author       = {Fielding, Eric J and Blom, Ronald G and Goldstein, Richard M},
  title        = {{Rapid subsidence over oil fields measured by SAR interferometry}},
  journaltitle = {Geophysical Research Letters},
  date         = {1998-09},
  volume       = {25},
  pages        = {3215--3218},
  issn         = {00948276},
  doi          = {10.1029/98GL52260},
  file         = {:home/baffelli/Library/Fielding, Blom, Goldstein - 1998 - Rapid subsidence over oil fields measured by SAR interferometry.pdf:pdf},
  keywords     = {doi:10.1029/98GL52260,http://dx.doi.org/10.1029/98GL52260},
}

@Article{Fletcher2007,
  author       = {Fletcher, K},
  title        = {{InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part C}},
  journaltitle = {Esa},
  date         = {2007},
  url          = {papers://29803081-7a18-4199-a903-38c6fcf8334a/Paper/p12443},
  file         = {:home/baffelli/Library/Fletcher - 2007 - InSAR Principles Guidelines for SAR Interferometry Processing and Interpretation (TM-19), Part C(2).pdf:pdf},
  isbn         = {92-9092-233-8},
}

@Article{Flotron1977,
  author       = {Andr{\'{e}} Flotron},
  title        = {Movement Studies on a Hanging Glacier in Relation with an Ice Avalanche},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {1977},
  date         = {1977-01},
  volume       = {19},
  pages        = {671--672},
  issn         = {0022-1430},
  doi          = {10.1017/s0022143000029592},
  url          = {https://www.cambridge.org/core/product/identifier/S0022143000029592/type/journal{\_}article},
  abstract     = {In 1972 the state of a hanging glacier on the Weisshorn gave cause for alarm, as part of it seemed to be accelerating and a repetition of an earlier avalanche of ice seemed possible (see R{\"{o}}thlisberger, previous abstract). For this reason movement surveys were undertaken. The various surveying methods applied on the Weisshorn are outlined and the accuracy of the measurements is given. By least-square analysis different types of curves have been fitted to the data for velocity versus time. The best fit obtained so-far has been with hyperbolae. The confidence of extrapolations from such curves is discussed in relation to forecasts. By evaluating repeated photographs taken by an automatic camera from a single position, using a stereo plotter, the flow pattern has been established at the surface, part of the front, and one of the lateral faces of the ice mass. Changes with time caused by the deformation of the ice mass, the formation of crevasses and the crumbling away of the ice at the edge have been observed.},
  file         = {:home/baffelli/Library/Flotron - 1977 - Movement Studies on a Hanging Glacier in Relation with an Ice Avalanche.pdf:pdf},
  publisher    = {Cambridge University Press ({CUP})},
}

@Article{Fomby1984a,
  author       = {Fomby, Thomas B. and Johnson, Stanley R. and Hill, R. Carter},
  title        = {{Feasible Generalized Least Squares Estimation}},
  journaltitle = {Advanced Econometric Methods},
  date         = {1984},
  pages        = {147--169},
  doi          = {10.1007/978-1-4419-8746-4_8},
  url          = {http://link.springer.com/10.1007/978-1-4419-8746-4{\_}8},
  file         = {:home/baffelli/Library/Fomby, Johnson, Hill - 1984 - Feasible Generalized Least Squares Estimation.pdf:pdf},
}

@Article{Fore2015,
  author        = {Alexander G. Fore and Bruce D. Chapman and Brian P. Hawkins and Scott Hensley and Cathleen E. Jones and Thierry R. Michel and Ronald J. Muellerschoen},
  title         = {{UAVSAR} Polarimetric Calibration},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2015},
  date          = {2015-06},
  volume        = {53},
  month         = {jun},
  pages         = {3481--3491},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2014.2377637},
  abstract      = {Uninhabited aerial vehicle synthetic aperture radar (UAVSAR) is a reconfigurable polarimetric L-band SAR that operates in quad-polarization mode and is specifically designed to acquire airborne repeat-track SAR data for interferometric measurements. In this paper, we present details of the UAVSAR radar performance, the radiometric calibration, and the polarimetric calibration. For the radiometric calibration, we employ an array of trihedral corner reflectors, as well as distributed targets. We show that UAVSAR is a well-calibrated SAR system for polarimetric applications, with absolute radiometric calibration bias better than 1 dB, residual root-mean-square (RMS) errors of {\~{}}0.7 dB, and RMS phase errors {\~{}}5.3{\&}{\#}x00B0;. For the polarimetric calibration, we have evaluated the methods of Quegan and Ainsworth et al. for crosstalk calibration and find that the method of Quegan gives crosstalk estimates that depend on target type, whereas the method of Ainsworth et al. gives more stable crosstalk estimates. We find that both methods estimate leakage of the copolarizations into the cross-polarizations to be on the order of -30 dB.},
  file          = {:home/baffelli/Library/Fore et al. - 2015 - UAVSAR polarimetric calibration.pdf:pdf},
  isbn          = {0196-2892 VO - 53},
  keywords      = {Airborne radar,Azimuth,Calibration,Crosstalk,Image resolution,Radar measurements,Radiometry,Synthetic aperture radar,UAVSAR polarimetric calibration,UAVSAR radar performance,airborne radar,airborne repeat-track SAR data,calibration,image resolution,interferometric measurements,polarimetric SAR,quadpolarization mode,radar cross-sections,radar imaging,radar measurements,radar polarimetry,radar remote sensing,radiometric calibration,reconfigurable polarimetric L-band SAR,remote sensing by radar,residual RMS errors,root-mean-square,stable crosstalk estimates,synthetic aperture radar,synthetic aperture radar (SAR),uninhabited aerial vehicle synthetic aperture rada},
  mendeley-tags = {Azimuth,Crosstalk,Radar measurements,Radiometry,UAVSAR polarimetric calibration,UAVSAR radar performance,airborne radar,airborne repeat-track SAR data,calibration,image resolution,interferometric measurements,polarimetric SAR,quadpolarization mode,radar cross-sections,radar imaging,radar polarimetry,radar remote sensing,radiometric calibration,reconfigurable polarimetric L-band SAR,remote sensing by radar,residual RMS errors,root-mean-square,stable crosstalk estimates,synthetic aperture radar,synthetic aperture radar (SAR),uninhabited aerial vehicle synthetic aperture rada},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{5758811,
  author    = {H. Oriot and X. Dupuis and O. Ruault Du Plessis},
  title     = {Coherent change detection in urban environment},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  year      = {2010},
  month     = {June},
  pages     = {1-3},
  keywords  = {Coherence;Image color analysis;Buildings;Urban areas;Cranes;Decorrelation;Radar polarimetry},
}

@Article{Freeman1992,
  author       = {Freeman, Anthony and Vanzyl, J J and Klein, Jeffrey D and Zebker, Howard A and Shen, Yuhsyen},
  title        = {{Calibration of Stokes and Scattering Matrix Format Polarimetric Sar Data}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {1992},
  volume       = {30},
  pages        = {531--539},
  issn         = {01962892},
  doi          = {10.1109/36.142931},
  abstract     = {Several different approaches to calibration of polarimetric radar image data have appeared recently in the literature. In particular, several papers by JPL authors have offered different perspectives on the polarimetric radar calibration problem. In this paper, we compare two of these approaches and demonstrate their functional equivalence. We show how one of the algorithms can be adapted to calibrate both scattering matrix and Stokes matrix format polarimetric radar data. Klein [1] has presented an approach for calibrating polarimetric SAR data in scattering matrix format, which relies on backscatter reciprocity and the lack of correlation between like- and cross-pol backscatter found in many natural targets. van Zyl [21 has presented an approach to the calibration of Stokes matrix (compressed) format polarimetric radar data, which is based on the assumption of reciprocity between the radar receive (R) and transmit (T) matrix representations. Both these approaches require one or more trihedral corner reflectors within the imaged scene. Freeman et al. [3] have presented an approach based on using three polarimetric active radar calibrators (PARC's) within the imaged scene. In general, techniques such as that described in [31, using three known (man-made) targets located at a single point will not be successful in calibrating all types of polarimetric radar data, because of the possibility of large variations in cross-talk amplitude and phase across the image swath. In this paper, we show that the assumptions about the backscatter and the polarimetric radar system for the two approaches described in Klein's and van Zyl's papers are equivalent. We demonstrate that, to first order in the radar system cross talk (i.e., neglecting terms of second order and above) an exact solution to the Stokes matrix format data calibration problem exists. We call this the first-order solution, for convenience. Next, we show that van Zyl's approach can give this first-order solution for appropriately symmetrized polarimetric radar data. Then we show how, if the data is properly symmetrized, van Zyl's approach can be used to calibrate both scattering matrix and Stokes matrix format data. These conclusions should be generally applicable to polarimetric imaging radar system data. The method is illustrated on NASA/JPL DC-8 SAR data and the results of calibrating in either scattering matrix or Stokes matrix format are shown to be in excellent agreement.},
  keywords     = {phase calibration,radar images},
}

@Article{Frey2009,
  author        = {Frey, Othmar and Magnard, Christophe and R{\"{u}}egg, Maurice and Meier, Erich},
  title         = {{Focusing of airborne synthetic aperture radar data from highly nonlinear elight tracks}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2009-06},
  volume        = {47},
  pages         = {1844--1858},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2008.2007591},
  abstract      = {Standard focusing of data from synthetic aperture radar (SAR) assumes a straight recording track of the sensor platform. Small nonlinearities of airborne platform tracks are corrected for during a motion-compensation step while maintaining the assumption of a linear flight path. This paper describes the processing of SAR data acquired from nonlinear tracks, typical of sensors mounted on small aircraft or drones flying at low altitude. Such aircraft do not fly along straight tracks, but the trajectory depends on topography, influences of weather and wind, or the shape of areas of interest such as rivers or traffic routes. Two potential approaches for processing SAR data from such highly nonlinear flight tracks are proposed, namely, a patchwise frequency-domain processing and mosaicking technique and a time-domain back-projection-based technique. Both are evaluated with the help of experimental data featuring tracks with altitude changes, a double bend, a 90deg curve, and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared, impulse response functions of a point target are analyzed, and the coherence is evaluated. The experimental data were acquired by the German Aerospace Center's E-SAR L-band system.},
  keywords      = {Corridor mapping,Digital elevation model (DEM),E-SAR L-band system,SAR processing,airborne SAR data focusing,airborne platform track nonlinearities,airborne radar,curvilinear synthetic aperture radar,extended chirp scaling (ECS),geocoding,geophysical signal processing,georeferencing,highly nonlinear flight tracks,integrated focusing and geocoding,linear flight path assumption,mapping,mosaicking,mosaicking technique,motion compensation,motion compensation step,nonlinear flight tracks,patchwise frequency domain processing,radar signal processing,remote sensing by radar,sensor platform recording track,synthetic aperture radar,synthetic aperture radar (SAR),time domain backprojection based technique,time-domain back-projection (TDBP)},
  mendeley-tags = {Corridor mapping,Digital elevation model (DEM),E-SAR L-band system,SAR processing,airborne SAR data focusing,airborne platform track nonlinearities,airborne radar,curvilinear synthetic aperture radar,extended chirp scaling (ECS),geocoding,geophysical signal processing,georeferencing,highly nonlinear flight tracks,integrated focusing and geocoding,linear flight path assumption,mapping,mosaicking,mosaicking technique,motion compensation,motion compensation step,nonlinear flight tracks,patchwise frequency domain processing,radar signal processing,remote sensing by radar,sensor platform recording track,synthetic aperture radar,synthetic aperture radar (SAR),time domain backprojection based technique,time-domain back-projection (TDBP)},
}

@InProceedings{Frey2005,
  author    = {Othmar Frey and Erich H. Meier and Daniel R. Nüesch},
  title     = {Processing {SAR} data of rugged terrain by time-domain back-projection},
  booktitle = {{SAR} Image Analysis, Modeling, and Techniques {VII}},
  year      = {2005},
  date      = {2005-10},
  volume    = {5980},
  publisher = {{SPIE}},
  month     = {oct},
  pages     = {598007--598007--9},
  doi       = {10.1117/12.627647},
  url       = {http://proceedings.spiedigitallibrary.org/data/Conferences/SPIEP/30165/598007{\_}1.pdf http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=879695},
  file      = {:home/baffelli/Library/Frey, Meier, N{"{u}}esch - 2005 - titleProcessing SAR data of rugged terrain by time-domain back-projectiontitle.pdf:pdf},
  issn      = {0277786X},
  keywords  = {antenna gain pattern correction,asar,back-projection,digital elevation model,envisat,geocod-,ing,radiometric correction,sar processing,topography},
}

@Article{Frey2016,
  author       = {Frey, Othmar and Werner, Charles L and Caduff, Rafael and Wiesmann, Andreas},
  title        = {A time series of {SAR} tomographic profiles of a snowpack},
  journaltitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  year         = {2016},
  date         = {2016},
  pages        = {726--730},
  file         = {:home/baffelli/Library/Frey et al. - 2016 - A time series of SAR tomographic profiles of a snowpack.pdf:pdf},
  isbn         = {9783800742288},
}

@InProceedings{Frey2015,
  author    = {Othmar Frey and Charles L. Werner and Andreas Wiesmann},
  title     = {Tomographic profiling of the structure of a snow pack at {X-}/{Ku-}Band using {SnowScat} in {SAR} mode},
  booktitle = {Proceedings of the European Radar Conference},
  year      = {2015},
  date      = {2015-09},
  volume    = {1},
  publisher = {{IEEE}},
  month     = {sep},
  isbn      = {9782874870415},
  pages     = {1--4},
  doi       = {10.1109/EuRAD.2015.7346227},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7346227},
  file      = {:home/baffelli/Library/Frey, Werner, Wiesmann - 2015 - Tomographic profiling of the structure of a snow pack at X-Ku-Band using SnowScat in SAR mode.pdf:pdf},
  keywords  = {[Electronic Manuscript]},
}

@Article{Fruneau2000,
  author       = {Fruneau, B{\'{e}}n{\'{e}}dicte and Sarti, Francesco},
  title        = {{Detection of ground subsidence in the city of Paris using radar interferometry: Isolation of deformation from atmospheric artifacts using correlation}},
  journaltitle = {Geophysical Research Letters},
  date         = {2000-12},
  volume       = {27},
  pages        = {3981--3984},
  issn         = {00948276},
  doi          = {10.1029/2000GL008489},
  file         = {:home/baffelli/Library/Fruneau, Sarti - 2000 - Detection of ground subsidence in the city of Paris using radar interferometry Isolation of deformation from atm.pdf:pdf},
}

@Book{Fujiwara2007,
  author    = {Fujiwara, Hiroyuki},
  title     = {{Spectroscopic Ellipsometry}},
  date      = {2007-01},
  publisher = {John Wiley {\&} Sons, Ltd},
  isbn      = {9780470060193},
  pages     = {388},
  doi       = {10.1002/9780470060193},
  abstract  = {Ellipsometry is a powerful tool used for the characterization of thin films and multi-layer semiconductor structures. This book deals with fundamental principles and applications of spectroscopic ellipsometry (SE). Beginning with an overview of SE technologies the text moves on to focus on the data analysis of results obtained from SE, Fundamental data analyses, principles and physical backgrounds and the various materials used in different fields from LSI industry to biotechnology are described. The final chapter describes the latest developments of real-time monitoring and process control which have attracted significant attention in various scientific and industrial fields.},
  arxivid   = {arXiv:1011.1669v3},
  issn      = {1098-6596},
  pmid      = {25246403},
}

@TechReport{Funk2015,
  author      = {Funk, Martin and Butt, Jemil},
  title       = {{Ergebnisse der Messungen mit dem GAMMA portablen Radarinterferometer (GPRI) im Einzugsgebiet des Bisbaches oberhalb Randa (Mattertal, Wallis) im Sommer 2014}},
  institution = {ETH Z{\"{u}}rich},
  date        = {2015-03},
}

@Article{Gorski2008,
  author       = {G{\'{o}}rski, Tomasz and Fabrizio, Giuseppe and {Le Caillec}, Jean Marc and Kawalec, Adam and Thomas, Nicolas},
  title        = {{Effect of integration time on detection performance of MTI and STAP algorithms in HF radar}},
  journaltitle = {Proceedings of the 2008 International Conference on Radar, Radar 2008},
  date         = {2008},
  pages        = {160--164},
  doi          = {10.1109/RADAR.2008.4653910},
  file         = {:home/baffelli/Library/G{'{o}}rski et al. - 2008 - Effect of integration time on detection performance of MTI and STAP algorithms in HF radar.pdf:pdf},
  isbn         = {9781424423224},
  keywords     = {[Electronic Manuscript]},
}

@Article{Gabriel1989,
  author       = {Andrew K. Gabriel and Richard M. Goldstein and Howard A. Zebker},
  title        = {Mapping small elevation changes over large areas: differential radar interferometry},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research},
  year         = {1989},
  date         = {1989},
  volume       = {94},
  pages        = {9183},
  issn         = {0148-0227},
  doi          = {10.1029/JB094iB07p09183},
  abstract     = {A technique is described, based on synthetic aperture radar (SAR) interferometry, which uses SAR images for measuring very small (1 cm or less) surface motions with good resolution (10 m) over swaths of up to 50 km. The method was applied to a Seasat data set of an imaging site in Imperial Valley, California, where motion effects were observed that were identified with movements due to the expansion of water-absorbing clays. The technique can be used for accurate measurements of many geophysical phenomena, including swelling and buckling in fault zones, residual displacements from seismic events, and prevolcanic swelling.},
  file         = {:home/baffelli/Library/Gabriel, Goldstein, Zebker - 1989 - Mapping Small Elevation Changes Over Large Areas Differential Radar Interferometry.pdf:pdf},
  isbn         = {01480227},
  keywords     = {doi:10.1029/JB094iB07p09183,http://dx.doi.org/10.1029/JB094iB07p09183},
  publisher    = {American Geophysical Union ({AGU})},
}

@InProceedings{Gail1993,
  author        = {Gail, W.B.},
  title         = {{A simplified calibration technique for polarimetric radars}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1993},
  isbn          = {0-7803-1240-6},
  pages         = {377--379},
  doi           = {10.1109/IGARSS.1993.322577},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=322577},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Covariance matrix,Faraday rotation,Layout,Nonlinear equations,Radar scattering,Rotation measurement,SAR,Spaceborne radar,airborne,airborne radar,calibration,channel imbalance,cross-talk,geophysical measurement technique,geophysical techniques,land surface imaging,polarimetric radar,polarimetry,radar imaging,radar polarimetry,radar remote sensing,remote sensing,remote sensing by radar,scattering element statistical analysis,spaceborne,synthetic aperture radar},
  mendeley-tags = {Covariance matrix,Faraday rotation,Layout,Nonlinear equations,Radar scattering,Rotation measurement,SAR,Spaceborne radar,airborne,airborne radar,calibration,channel imbalance,cross-talk,geophysical measurement technique,geophysical techniques,land surface imaging,polarimetric radar,polarimetry,radar imaging,radar polarimetry,radar remote sensing,remote sensing,remote sensing by radar,scattering element statistical analysis,spaceborne,synthetic aperture radar},
}

@Article{Galletti2014,
  author    = {Galletti, Michele and Zrnic, Dusan S and Gekat, Frank and Goelz, Peter},
  title     = {{Eigenvalue Signal Processing for Weather Radar Polarimetry : Removing the Bias Induced by Antenna Coherent Cross-Channel Coupling}},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2014},
  date      = {2014},
  volume    = {52},
  month     = {dec},
  pages     = {7695--7707},
  doi       = {10.1109/tgrs.2014.2316821},
  file      = {:home/baffelli/Library/Galletti et al. - 2014 - Eigenvalue Signal Processing for Weather Radar Polarimetry Removing the Bias Induced by Antenna Coherent Cross.pdf:pdf;:home/baffelli/Library/Galletti et al. - 2014 - Eigenvalue Signal Processing for Weather Radar Polarimetry Removing the Bias Induced by Antenna Coherent Cro(2).pdf:pdf},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Galloway2007,
  author       = {Devin L. Galloway and Jörn Hoffmann},
  title        = {The application of satellite differential {SAR} interferometry-derived ground displacements in hydrogeology},
  journal      = {Hydrogeology Journal},
  journaltitle = {Hydrogeology Journal},
  year         = {2006},
  date         = {2007},
  volume       = {15},
  month        = {nov},
  pages        = {133--154},
  issn         = {14312174},
  doi          = {10.1007/s10040-006-0121-5},
  abstract     = {The application of satellite differential synthetic aperture radar (SAR) interferometry, principally coherent (InSAR) and to a lesser extent, persistent-scatterer (PSI) techniques to hydrogeologic studies has improved capabilities to map, monitor, analyze, and simulate groundwater flow, aquifer-system compaction and land subsidence. A number of investigations over the previous decade show how the spatially detailed images of ground displacements measured with InSAR have advanced hydrogeologic understanding, especially when a time series of images is used in conjunction with histories of changes in water levels and management practices. Important advances include: (1) identifying structural or lithostratigraphic boundaries (e.g. faults or transitional facies) of groundwater flow and deformation; (2) defining the material and hydraulic heterogeneity of deforming aquifer-systems; (3) estimating system properties (e.g. storage coefficients and hydraulic conductivities); and (4) constraining numerical models of groundwater flow, aquifer-system compaction, and land subsidence. As a component of an integrated approach to hydrogeologic monitoring and characterization of unconsolidated alluvial groundwater basins differential SAR interferometry contributes unique information that can facilitate improved management of groundwater resources. Future satellite SAR missions specifically designed for differential interferometry will enhance these contributions.},
  isbn         = {1431-2174},
  keywords     = {Aquifer-system compaction,Groundwater flow,InSAR,Remote sensing,Subsidence},
  publisher    = {Springer Nature},
}

@Article{Galloway1998,
  author       = {Galloway, D. L. and Hudnut, K. W. and Ingebritsen, S. E. and Phillips, S. P. and Peltzer, G. and Rogez, F. and Rosen, P. a.},
  title        = {Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, {Antelope Valley}, {Mojave Desert}, {California}},
  journaltitle = {Water Resources Research},
  date         = {1998-10},
  volume       = {34},
  pages        = {2573},
  issn         = {0043-1397},
  doi          = {10.1029/98WR01285},
  abstract     = {Interferometric synthetic aperture radar (InSAR) has great potential to detect and quantify land subsidence caused by aquifer system compaction. InSAR maps with high spatial detail and resolution of range displacement (+/-10 mm in change of land surface elevation) were developed for a groundwater basin (similar to 10(3) km(2)) in Antelope Valley, California, using radar data collected from the ERS-1. satellite. These data allow comprehensive comparison between recent (1993-1995) subsidence patterns and those detected historically (1926-1992) by more traditional methods. The changed subsidence patterns are generally compatible with recent shifts in land and water use. The InSAR-detected patterns are generally consistent with predictions based on a coupled model of groundwater flow and aquifer system compaction. The minor inconsistencies may reflect our imperfect knowledge of the distribution and properties of compressible sediments. When used in conjunction with coincident measurements of groundwater levels and other geologic information, InSAR data may be useful for constraining parameter estimates in simulations of aquifer system compaction.},
  file         = {:home/baffelli/Library/Galloway et al. - 1998 - Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, Ante.pdf:pdf},
  isbn         = {0043-1397},
}

@Article{Gao2010,
  author       = {Gao, Gui},
  title        = {{Statistical modeling of SAR images: A survey}},
  journaltitle = {Sensors},
  date         = {2010},
  volume       = {10},
  pages        = {775--795},
  issn         = {14248220},
  doi          = {10.3390/s100100775},
  abstract     = {Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Gao - 2010 - Statistical modeling of SAR images A survey.pdf:pdf},
  keywords     = {Parameter estimation,Probability density function (PDF),Statistical models,Synthetic aperture radar (SAR) images,The product model},
  pmid         = {22315568},
}

@Article{Gatelli1994,
  author       = {F. Gatelli and A. Monti Guamieri and F. Parizzi and P. Pasquali and C. Prati and F. Rocca},
  title        = {The wavenumber shift in {SAR} interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1994},
  date         = {1994},
  volume       = {32},
  month        = {jul},
  pages        = {855--865},
  issn         = {0196-2892},
  doi          = {10.1109/36.298013},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=298013},
  abstract     = {SAR surveys from separate passes show relative shifts of the ground wavenumber spectra that depend on the local slope and the off-nadir angle. The authors discuss the exploitation of this spectral shift for different applications: 1) generation of {\&}ldquo;low noise{\&}rdquo; interferograms benefiting phase unwrapping, 2) generation of quick-look interferograms, 3) decorrelation reduction by means of tunable SAR systems (TINSAR), 4) range resolution enhancement, and 5) the combination of SAR data gathered by different platforms (airborne and satellite) for a {\&}ldquo;long-time coherence{\&}rdquo; study},
  isbn         = {0196-2892},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Geaga2012,
  author    = {Geaga, Jorge V.},
  title     = {{Features for landcover classification of fully polarimetric SAR data}},
  year      = {2012},
  date      = {2012},
  volume    = {8361},
  month     = {may},
  pages     = {836108--836108--14},
  issn      = {0277786X},
  doi       = {10.1117/12.917226},
  url       = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1355056},
  booktitle = {Radar Sensor Technology {XVI}},
  file      = {:home/baffelli/Library/Geaga - 2012 - Features for landcover classification of fully polarimetric SAR data.pdf:pdf},
  isbn      = {9780819490391},
  publisher = {{SPIE}},
}

@InProceedings{Geibig2016,
  author    = {Geibig, Thomas and Shoykhetbrod, Alex and Hommes, Alexander and Herschel, Reinhold and Pohl, Nils},
  title     = {{Compact 3D imaging radar based on FMCW driven frequency-scanning antennas}},
  booktitle = {Proceddins of the {IEEE} Conference on Radar},
  date      = {2016-05},
  publisher = {IEEE},
  isbn      = {978-1-5090-0863-6},
  pages     = {1--5},
  doi       = {10.1109/RADAR.2016.7485168},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7485168},
  file      = {:home/baffelli/Library/Geibig et al. - 2016 - Compact 3D imaging radar based on FMCW driven frequency-scanning antennas.pdf:pdf},
}

@Article{Genton2007,
  author       = {Marc G. Genton},
  title        = {Separable approximations of space-time covariance matrices},
  journal      = {Environmetrics},
  journaltitle = {Environmetrics},
  year         = {2007},
  date         = {2007-11},
  volume       = {18},
  pages        = {681--695},
  issn         = {11804009},
  doi          = {10.1002/env.854},
  abstract     = {"Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space-time random effects in zero-inflated Poisson (ZIP) and 'hurdle' models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space-time ZIP and hurdle models in a Bayesian hierarchical model. Space-time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space-time ZIP and hurdle models.},
  file         = {:home/baffelli/Library/Genton - 2007 - Separable approximations of space-time covariance matrices.pdf:pdf},
  isbn         = {1180-4009},
  keywords     = {Bernoulli,Poisson,hurdle model,linex loss function,spatial statistics,time series},
  pmid         = {19829763},
  publisher    = {Wiley},
}

@InProceedings{Geudtner1996,
  author        = {Geudtner, D. and Winter, R. and Vachon, P.W.},
  title         = {{Flood monitoring using ERS-1 SAR interferometry coherence maps}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1996-05},
  volume        = {2},
  isbn          = {0-7803-3068-4},
  pages         = {966--968},
  doi           = {10.1109/IGARSS.1996.516536},
  url           = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=516536{\%}5Cnhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=516536},
  abstract      = {The potential of satellite repeat-pass SAR interferometry (InSAR) for flood monitoring is discussed. Using ESR-1 SAR images covering the 1993/94 flood event in the river Rhine, Germany, it is shown that, by evaluating the scene coherence, a reliable mapping of flood extent is feasible, even in cases of rough water surfaces where the analysis of conventional SAR intensity and multi-temporal images may fail},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {AD 1993,AD 1994,ERS-1 SAR interferometry coherence map,Failure analysis,Floods,Germany,Image analysis,InSAR,Layout,Monitoring,Rhine,Rough surfaces,SAR,Satellites,Spaceborne radar,Surface roughness,Synthetic aperture radar interferometry,flood,hydrological techniques,hydrology,measurement technique,radar remote sensing,remote sensing by radar,repeat-pass SAR interferometry,river flooding,rivers,scene coherence,synthetic aperture radar},
  mendeley-tags = {AD 1993,AD 1994,ERS-1 SAR interferometry coherence map,Failure analysis,Floods,Germany,Image analysis,InSAR,Layout,Monitoring,Rhine,Rough surfaces,Satellites,Spaceborne radar,Surface roughness,Synthetic aperture radar interferometry,flood,hydrological techniques,hydrology,measurement technique,radar remote sensing,remote sensing by radar,repeat-pass SAR interferometry,river flooding,rivers,scene coherence,synthetic aperture radar},
}

@Article{Goldstein1993,
  author       = {R. M. Goldstein and H. Engelhardt and B. Kamb and R. M. Frolich},
  title        = {Satellite radar interferometry for monitoring ice sheet motion: application to an {Antarctic} ice stream.},
  journal      = {Science},
  journaltitle = {Science},
  year         = {1993},
  date         = {1993},
  volume       = {262},
  number       = {5139},
  month        = {dec},
  pages        = {1525--1530},
  doi          = {10.1126/science.262.5139.1525},
  file         = {:home/baffelli/Library/Goldstein et al. - 1993 - Satellite radar interferometry for monitoring ice sheet motion application to an antarctic ice stream.pdf:pdf},
  pmid         = {17829380},
  publisher    = {American Association for the Advancement of Science ({AAAS})},
}

@Article{Gong2016,
  author       = {Gong, Wenyu and Thiele, Antje and Hinz, Stefan and Meyer, Franz J. and Hooper, Andrew and Agram, Piyush S.},
  title        = {{Comparison of small baseline interferometric SAR processors for estimating ground deformation}},
  journaltitle = {Remote Sensing},
  date         = {2016},
  volume       = {8},
  issn         = {20724292},
  doi          = {10.3390/rs8040330},
  abstract     = {The small Baseline Synthetic Aperture Radar (SAR) Interferometry (SBI) technique has been widely and successfully applied in various ground deformation monitoring applications. Over the last decade, a variety of SBI algorithms have been developed based on the same fundamental concepts. Recently developed SBI toolboxes provide an open environment for researchers to apply different SBI methods for various purposes. However, there has been no thorough discussion that compares the particular characteristics of different SBI methods and their corresponding performance in ground deformation reconstruction. Thus, two SBI toolboxes that implement a total of four SBI algorithms were selected for comparison. This study discusses and summarizes the main differences, pros and cons of these four SBI implementations, which could help users to choose a suitable SBI method for their specific application. The study focuses on exploring the suitability of each SBI module under various data set conditions, including small/large number of interferograms, the presence or absence of larger time gaps, urban/vegetation ground coverage, and temporally regular/irregular ground displacement with multiple spatial scales. Within this paper we discuss the corresponding theoretical background of each SBI method. We present a performance analysis of these SBI modules based on two real data sets characterized by different environmental and surface deformation conditions. The study shows that all four SBI processors are capable of generating similar ground deformation results when the data set has sufficient temporal sampling and a stable ground backscatter mechanism like urban area. Strengths and limitations of different SBI processors were analyzed based on data set configuration and environmental conditions and are summarized in this paper to guide future users of SBI techniques.},
  file         = {:home/baffelli/Library/Gong et al. - 2016 - Comparison of small baseline interferometric SAR processors for estimating ground deformation.pdf:pdf},
  keywords     = {Deformation monitoring,Interferometry,Synthetic aperture radar,Time series},
}

@Article{Gonzalez2011,
  author       = {Gonz\'{a}lez, Pablo J. and Fern\'{a}ndez, Jos{\'{e}}},
  title        = {Error estimation in multitemporal {InSAR} deformation time series, with application to {Lanzarote}, {Canary Islands}},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  date         = {2011},
  volume       = {116},
  pages        = {1--17},
  issn         = {21699356},
  doi          = {10.1029/2011JB008412},
  abstract     = {Interferometric Synthetic Aperture Radar (InSAR) is a reliable technique for measuring crustal deformation. However, despite its long application in geophysical problems, its error estimation has been largely overlooked. Currently, the largest problem with InSAR is still the atmospheric propagation errors, which is why multitemporal interferometric techniques have been successfully developed using a series of interferograms. However, none of the standard multitemporal interferometric techniques, namely PS or SB (Persistent Scatterers and Small Baselines, respectively) provide an estimate of their precision. Here, we present a method to compute reliable estimates of the precision of the deformation time series. We implement it for the SB multitemporal interferometric technique (a favorable technique for natural terrains, the most usual target of geophysical applications). We describe the method that uses a properly weighted scheme that allows us to compute estimates for all interferogram pixels, enhanced by a Montecarlo resampling technique that properly propagates the interferogram errors (variance-covariances) into the unknown parameters (estimated errors for the displacements). We apply the multitemporal error estimation method to Lanzarote Island (Canary Islands), where no active magmatic activity has been reported in the last decades. We detect deformation around Timanfaya volcano (lengthening of line-of-sight ∼ subsidence), where the last eruption in 1730–1736 occurred. Deformation closely follows the surface temperature anomalies indicating that magma crystallization (cooling and contraction) of the 300-year shallow magmatic body under Timanfaya volcano is still ongoing.},
  file         = {:home/baffelli/Library/Gonz{'{a}}lez, Fernndez - 2011 - Error estimation in multitemporal InSAR deformation time series, with application to Lanzarote, Canary Isla.pdf:pdf},
  isbn         = {2156-2202},
}

@Article{Grabowski2012,
  author       = {Grabowski, Michal},
  title        = {Non-Resonant Slotted Waveguide Antenna Design Method},
  journaltitle = {High Frequency Electronics Journal},
  date         = {2012},
  pages        = {32--46},
  file         = {:home/baffelli/Library/Grabowski - 2012 - Non-Resonant Slotted Waveguide Antenna Design Method.pdf:pdf},
}

@Article{Graler2016,
  author       = {Graler, Benedikt and Pebesma, Edzer and Heuvelink, Gerard},
  title        = {{Spatio-Temporal Interpolation using gstat}},
  journaltitle = {Wp},
  date         = {2016},
  volume       = {8},
  pages        = {1--20},
  issn         = {20734859},
  doi          = {10.1007/978-3-319-17885-1},
  abstract     = {We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatio-temporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the extension of gstat facilitates and eases spatio-temporal geostatistical modelling and prediction for R users.},
  arxivid      = {arXiv:1011.1669v3},
  file         = {:home/baffelli/Library/Graler, Pebesma, Heuvelink - 2016 - Spatio-Temporal Interpolation using gstat.pdf:pdf},
  isbn         = {978-3-319-17884-4},
  pmid         = {25246403},
}

@InCollection{Granet2007,
  author    = {Granet, Christophe and James, Graeme L and {Ross Forsyth}, A.},
  title     = {{Aperture Antennas: Waveguides and Horns}},
  booktitle = {Modern Antenna Handbook},
  date      = {2007},
  publisher = {John Wiley {\&} Sons, Ltd},
  isbn      = {9780470294154},
  pages     = {97--156},
  doi       = {10.1002/9780470294154.ch3},
  file      = {:home/baffelli/Library/Granet, James, Ross Forsyth - 2007 - Aperture Antennas Waveguides and Horns.pdf:pdf},
  keywords  = {Aperture antennas - waveguides and horns,Radiation pattern specification,Swarf control in antenna component machining},
}

@Article{Gray2001,
  author       = {A.L. Gray and N. Short and K.E. Mattar and K.C. Jezek},
  title        = {Velocities and Flux of the {Filchner} Ice Shelf and its Tributaries Determined from Speckle Tracking Interferometry},
  journal      = {Canadian Journal of Remote Sensing},
  journaltitle = {Canadian Journal of Remote Sensing},
  year         = {2001},
  date         = {2001},
  volume       = {27},
  month        = {jun},
  pages        = {193--206},
  issn         = {07038992},
  doi          = {10.1080/07038992.2001.10854936},
  abstract     = {Velocities of the Filchner Ice Shelf and its tributary glaciers are derived using a variation of satellite radar interferometry known as speckle tracking. The method requires a coherent pair of SAR passes, a digital elevation model and, for floating ice, an estimate of the height if difference due to the tide. Speckle tracking interferometry has the advantage that ice speed and direction can be estimated from one interferometric pair and, with adequate coherence, it is suitable for areas of high velocity and long repeat cycles. Fluxes are estimated using the ice velocities together with ice thickness data derived from a hydrostatic equilibrium model. They are given for gates downstream from the grounding lines of the input tributary glaciers, and for a gate close to the ice shelf edge. The calculations show that the flux close to the edge of the Filchner Ice Shelf (similar to 75.3 km(3)/a) is comparable to that estimated further upstream. However the errors in the estimates (similar to 10 km(3)/a) preclude any firm conclusions concerning equilibrium of the ice shelf or bottom surface melt or accretion. Assuming the upstream fluxes reflect the flow across the grounding lines, then the Recovery Glacier is the largest contributor to the ice shelf with 48{\%} and the Slessor Glacier is the second largest with 33{\%}. Support Force Glacier and Foundation Ice Stream both contribute similar to7{\%}. Ice Shelf accumulation accounts for the remaining 5{\%}.},
  file         = {:home/baffelli/Library/Gray et al. - 2001 - Velocities and flux of the Filchner Ice Shelf and its tributaries determined from speckle tracking interferometry.pdf:pdf},
  isbn         = {0703-8992},
  publisher    = {Informa {UK} Limited},
}

@Article{Gu,
  author = {Gu, Chengfei and Chang, Wenge and Li, Xiangyang},
  title  = {{Parallel Imaging Based on Multicore DSP for FMCW SAR}},
  volume = {2},
  pages  = {2--6},
  file   = {:home/baffelli/Library/Gu, Chang, Li - Unknown - Parallel Imaging Based on Multicore DSP for FMCW SAR.pdf:pdf},
}

@InProceedings{Guarnieri2010,
  author    = {Guarnieri, A Monti and Iannini, L and Giudici, D},
  title     = {On the exploitation of meteo information for atmospheric phase screen compensation in {GB-SAR} interferometry},
  booktitle = {ESA Living Planet Symposium},
  date      = {2010},
  file      = {:home/baffelli/Library/Guarnieri, Iannini, Giudici - 2010 - On the Exploitation of Meteo Information for Atmospheric Phase Screen Compensation in Gb-Sar Interf.pdf:pdf},
  keywords  = {5 m range resolution,and images the scene,aps effects on the,atmospheric phase,brief overview of the,cm,ground-based radar,in section 2 a,ku-band interferometry,screen,with a 0},
}

@Article{Guo2009,
  author       = {Guo, Liang and Xing, Mendao and Liang, Yi and Tang, Yu},
  title        = {{Modified frequency scaling algorithm for synthetic aperture imaging ladar imaging through the turbulence}},
  journaltitle = {Chinese Journal of Electronics},
  date         = {2009},
  volume       = {18},
  pages        = {187--191},
  issn         = {10224653},
  abstract     = {In strip-mode synthetic aperture imaging radar, the spatial resolution in range is given by a frequency-swept waveform, whereas the resolution in the orthogonal direction is derived from the record of phase as the beam footprint executes linear motion over the object. The combination of the laser and SAR processing techniques should pave the way for a higher resolution air borne or space borne remote sensor. Regarding the ladar transmitting FMCW signal, the motion during the transmission of a sweep and the reception of the corresponding echo wore expected to be one of the major problems. The given modified frequency scaling algorithm is taking the continuous motion into account, which can compensate for the Doppler shift induced by the continuous motion efficiently. And then, simulation of Phase screen (PS) distorted by atmospheric turbulence following the von Karman spectrum by using Fourier Transform is implemented in order to simulate turbulence. Finally, the computer simulation shows the validity of the modified algorithm and if in the turbulence the synthetic aperture length does not exceed the similar coherence length of the atmosphere for SAIL, we can ignore the effect of the turbulence.},
  file         = {:home/baffelli/Library/Guo et al. - 2009 - Modified frequency scaling algorithm for synthetic aperture imaging ladar imaging through the turbulence.pdf:pdf},
  isbn         = {1022-4653},
  keywords     = {Coherence length of atmosphere,Frequency modulation continuous wave (FMCW),Frequency scaling algorithm,Ladar,Phase screens,Synthetic aperture},
}

@Article{Gupta1987,
  author       = {Gupta, Vijay K. and Waymire, Ed},
  title        = {On {Taylor's} hypothesis and dissipation in rainfall},
  journaltitle = {Journal of Geophysical Research},
  year         = {1987},
  date         = {1987},
  volume       = {92},
  pages        = {9657},
  doi          = {10.1029/JD092iD08p09657},
  file         = {:home/baffelli/Library/Gupta, Waymire - 1987 - On Taylor's hypothesis and dissipation in rainfall.pdf:pdf},
}

@PhdThesis{Hajnsek2001,
  author      = {Hajnsek, Irena},
  title       = {Inversion of surface parameters using polarimetric {SAR}},
  institution = {Friedrich-Schiller-Universität Jena},
  year        = {2001},
  date        = {2001},
  type        = {PhD},
  month       = {apr},
  isbn        = {0196-2892},
  url         = {https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00001090/diss_hajnsek.pdf},
  abstract    = {The classical point measurement methods for, soil moisture content and surface roughness, are described. The ground data acquisition as well as the SAR data acquisition campaign were performed with the E-SAR of the German Aerospace Center at Oberpfaffenhofen (DLR-OP- IHR) over two test sites in Germany, the Elbe-Auen and the Weiherbach region. The basic principles of SAR and radar polarimetry are introduced in order to provide the conceptual framework for the inversion of surface parameters from fully polarimetric SAR data, which includes the critical assessment of various novel polarimetric concepts. The prevalent methods for estimating the surface parameters from polarimetric SAR data are critically reviewed. The small perturbation model and two semi-empirical models are forming the basis of a comparative analysis. These two semi-empirical models were chosen in order to provide an overview of the evolution of ideas and techniques in the area of quantitative surface parameter estimation utilising partially polarimetric SAR image data takes. Further, the potential of polarimetric techniques recently developed in different application areas are investigated with regard to their suitability to improve the performance of the introduced inversion algorithms. First, the potential for applying the polarimetric decomposition techniques was addressed in order to repress the disturbing influence of secondary scattering processes, resulting from rough surface scatter. Then, the potential to estimate terrain slopes from fully polarimetric data utilising polarimetric techniques only is investigated and discussed as an attractive alternative to the standard method of using a-priori terrain information. A new model for the inversion of surface parameters from polarimetric SAR image data takes, the Extended Bragg Model, is introduced. The main advantages and disadvantages of this alternate model are discussed. Finally, future perspectives on how to extend the model by implementation of recent advances in polarimetric SAR interferometry are presented.},
  file        = {:home/baffelli/Library/Hajnsek - 2001 - Inversion of surface parameters using polarimetric SAR.pdf:pdf},
  keywords    = {Estimation,SAR Polarimetry,Soil Moisture Estimation,Surface Parameters Inversion,Surface Roughness,Synthetic Aperture Radar (SAR)},
}

@Article{Baffelli2018c,
  author       = {Simone Baffelli and Othmar Frey and Irena Hajnsek},
  title        = {Geostatistical Analysis and Mitigation of Atmospheric Phase Screens in {Ku}-Band Terrestrial Radar Interferometric Observations of an Alpine Glacier},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2018},
  date         = {2018},
  note         = {submission {ID} {TGRS-2018-01579}},
  file         = {:home/baffelli/Library/Hajnsek, Baffelli - 2017 - Polarimetric Diversity in Ku-Band Differential Interferometric Observations of an Alpine Glacier Ilona L u Su.pdf:pdf},
}

@Article{Hajnsek2003,
  author       = {I. Hajnsek and E. Pottier and S.R. Cloude},
  title        = {Inversion of surface parameters from polarimetric {SAR}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2003},
  date         = {2003},
  volume       = {41},
  month        = {apr},
  pages        = {727--744},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2003.810702},
  abstract     = {Proposes a new model for the inversion of surface roughness and soil moisture from polarimetric synthetic aperture radar (SAR) data, based on the eigenvalues and eigenvectors of the polarimetric coherency matrix. It demonstrates how three polarimetric parameters, namely the scattering entropy (H), the scattering anisotropy (A), and the alpha angle ({\&}alpha;) may be used in order to decouple surface roughness from moisture content estimation offering the possibility of a straightforward inversion of these two surface parameters. The potential of the proposed inversion algorithm is investigated using fully polarimetric laboratory measurements as well as airborne L-band SAR data and ground measurements from two different test sites in Germany, the Elbe-Auen site and the Weiherbach site.},
  file         = {:home/baffelli/Library/Hajnsek, Pottier, Cloude - 2003 - Inversion of surface parameters from polarimetric SAR.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Inversion,Soil moisture,Surface parameters,Surface roughness,Synthetic aperture radar (SAR) polarimetry},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Hamasaki2005,
  author       = {Hamasaki, Tadashi and Sato, Motoyuki and Ferro-Famil, L. and Pottier, Eric},
  title        = {Natural objects monitoring using polarimetric interferometric ground-based {SAR} ({GB-SAR}) system},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2005},
  volume       = {6},
  publisher    = {IEEE},
  isbn         = {0-7803-9050-4},
  pages        = {4092--4095},
  doi          = {10.1109/IGARSS.2005.1525814},
  url          = {http://www.ietr.fr/Equipes/SAPHIR/publications/pdfs{\_}2005/hamasaki3.pdf http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1525814},
  file         = {:home/baffelli/Library/Hamasaki et al. - 2005 - Natural objects monitoring using polarimetric interferometric ground-based SAR (GB-SAR) system.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Hamer1976,
  author        = {Hamer, J.},
  title         = {{Renin and beta-adenoceptor blockade-the mechanism of the hypotensive effect?}},
  journaltitle  = {British Journal of Clinical Pharmacology},
  date          = {1976-06},
  language      = {eng},
  volume        = {3},
  pages         = {425--427},
  issn          = {0306-5251},
  url           = {http://www.ncbi.nlm.nih.gov/pubmed/9962},
  keywords      = {Adrenergic beta-Antagonists,Blood Pressure,Dose-Response Relationship- Drug,Humans,Hypertension,Renin,Time Factors},
  mendeley-tags = {Adrenergic beta-Antagonists,Blood Pressure,Dose-Response Relationship- Drug,Humans,Hypertension,Renin,Time Factors},
}

@Article{Hammer2009,
  author       = {Hammer, H and Schulz, K},
  title        = {{Coherent simulation of SAR images}},
  journaltitle = {Proceedings of SPIE},
  date         = {2009},
  volume       = {7477},
  pages        = {1--9},
  issn         = {0277786X},
  doi          = {10.1117/12.830380},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-70350437316{\&}partnerID=40{\&}md5=dfcdc02f164f49daa3b0e1452b76a209},
  abstract     = {Simulated SAR images can be used for a wide variety of purposes such as classification, object recognition or the education of SAR image analysts. In this paper, a SAR simulation tool based on an extended raytracing approach is introduced. The approach allows for a coherent simulation of the most important SAR image features. Another aspect is the modeling of material properties necesSARy for the creation of synthetic SAR images that look realistic. Also, the image formation process is described in detail since it has immense impact on the overall appearance of the final image. The different steps of the simulation process and their influence on the appearance of the final simulated image are demonstrated with simulated images of a simple building. Then, examples for the simulation of large scale scenes at high resolution are given. {\textcopyright} 2009 SPIE.},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Hammer, Schulz - 2009 - Coherent simulation of SAR images.pdf:pdf},
  isbn         = {0277786X (ISSN); 9780819477828 (ISBN)},
  keywords     = {Classification ,,Coherent processing,High resolution,Image formation process,Material property,Object recognition,Raytracing,Remote sensing,SAR Images,SAR simulation,Scale-scene,Signal processing,Simulated images,Simulation process,Synthetic apertures},
}

@Article{Hammer2009a,
  author       = {Hammer, H and Schulz, K},
  title        = {{Coherent simulation of SAR images}},
  journaltitle = {Proceedings of SPIE},
  date         = {2009},
  volume       = {7477},
  pages        = {1--9},
  issn         = {0277786X},
  doi          = {10.1117/12.830380},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-70350437316{\&}partnerID=40{\&}md5=dfcdc02f164f49daa3b0e1452b76a209},
  abstract     = {Simulated SAR images can be used for a wide variety of purposes such as classification, object recognition or the education of SAR image analysts. In this paper, a SAR simulation tool based on an extended raytracing approach is introduced. The approach allows for a coherent simulation of the most important SAR image features. Another aspect is the modeling of material properties necesSARy for the creation of synthetic SAR images that look realistic. Also, the image formation process is described in detail since it has immense impact on the overall appearance of the final image. The different steps of the simulation process and their influence on the appearance of the final simulated image are demonstrated with simulated images of a simple building. Then, examples for the simulation of large scale scenes at high resolution are given. {\textcopyright} 2009 SPIE.},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Hammer, Schulz - 2009 - Coherent simulation of SAR images.pdf:pdf},
  isbn         = {0277786X (ISSN); 9780819477828 (ISBN)},
  keywords     = {Classification ,,Coherent processing,High resolution,Image formation process,Material property,Object recognition,Raytracing,Remote sensing,SAR Images,SAR simulation,Scale-scene,Signal processing,Simulated images,Simulation process,Synthetic apertures},
}

@Article{Hansen1939,
  author   = {Hansen, H J and Lindop, R and Majstorovic, D},
  title    = {{Collision Avoidance W-Band FMCW Radars in an Altimeter Application}},
  date     = {1939},
  file     = {:home/baffelli/Library/Hansen, Lindop, Majstorovic - 1939 - Collision Avoidance W-Band FMCW Radars in an Altimeter Application.pdf:pdf},
  keywords = {Unmanned aerial vehicles, Collision avoidance, Alt},
}

@Book{Hanssen2001,
  author    = {Hanssen, Ramon F.},
  title     = {Radar Interferometry},
  year      = {2001},
  date      = {2001-02},
  volume    = {2},
  series    = {Remote Sensing and Digital Image Processing},
  publisher = {Springer Netherlands},
  isbn      = {978-0-7923-6945-5},
  pages     = {46--53},
  doi       = {10.1007/0-306-47633-9},
  url       = {http://www.iub.edu/{~}act/files/publications/2004/04-12{\_}LUCCPathways{\_}Impacts.pdf http://link.springer.com/10.1007/0-306-47633-9 http://www.nature.com/doifinder/10.1038/scientificamerican0297-46},
  file      = {:home/baffelli/Library/Hanssen - 2001 - Radar Interferometry.pdf:pdf},
  issn      = {0036-8733},
}

@TechReport{Hanssen1998,
  author      = {Hanssen, Ramon F.},
  title       = {Atmospheric heterogeneities in {ERS} tandem {SAR} interferometry},
  institution = {Delft University},
  year        = {1998},
  date        = {1998},
  file        = {:home/baffelli/Library/Hanssen - 1998 - Atmospheric heterogeneities in ERS tandem SAR interferometry.pdf:pdf},
}

@Article{Hanssen1999,
  author       = {R. F. Hanssen},
  title        = {High-Resolution Water Vapor Mapping from Interferometric Radar Measurements},
  journal      = {Science},
  journaltitle = {Science},
  year         = {1999},
  date         = {1999},
  volume       = {283},
  month        = {feb},
  pages        = {1297--1299},
  issn         = {1095-9203},
  doi          = {10.1126/science.283.5406.1297},
  url          = {http://www.ncbi.nlm.nih.gov/pubmed/10037594},
  abstract     = {Spaceborne radar interferometric delay measurements were used to infer high-resolution maps of integrated atmospheric water vapor, which can be readily related to meteorological phenomena. Maps of the water vapor distribution associated with a precipitating cloud, a partly precipitating cold front, and horizontal convective rolls reveal quantitative measures that are not observed with conventional methods, and suggest that such radar observations can be used for forecasting and to study atmospheric dynamics.},
  file         = {:home/baffelli/Library/Hanssen et al. - 1999 - High-Resolution Water Vapor Mapping from Interferometric Radar Measurements.pdf:pdf},
  pmid         = {10037594},
  publisher    = {American Association for the Advancement of Science ({AAAS})},
}

@Article{Hartman2008,
  author    = {Hartman, Linda and H{\"{o}}ssjer, Ola},
  title     = {{Fast kriging of large data sets with Gaussian Markov random fields}},
  journal   = {Computational Statistics {\&} Data Analysis},
  year      = {2008},
  date      = {2008},
  volume    = {52},
  month     = {jan},
  pages     = {2331--2349},
  doi       = {10.1016/j.csda.2007.09.018},
  file      = {:home/baffelli/Library/Hartman, H{"{o}}ssjer - 2008 - Fast kriging of large data sets with Gaussian Markov random fields.pdf:pdf},
  keywords  = {bilinear interpolation,markov random field,nonlattice data,spatial interpolation},
  publisher = {Elsevier {BV}},
}

@Article{Hetland2012,
  author       = {Hetland, E. A. and Mus{\'{e}}, P. and Simons, M. and Lin, Y. N. and Agram, P. S. and Dicaprio, C. J.},
  title        = {{Multiscale InSAR Time Series (MInTS) analysis of surface deformation}},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  date         = {2012},
  volume       = {117},
  pages        = {1--17},
  issn         = {21699356},
  doi          = {10.1029/2011JB008731},
  abstract     = {We present a new approach to extracting spatially and temporally continuous ground deformation fields from interferometric synthetic aperture radar (InSAR) data. We focus on unwrapped interferograms from a single viewing geometry, estimating ground deformation along the line-of-sight. Our approach is based on a wavelet decomposition in space and a general parametrization in time. We refer to this approach as MInTS (Multiscale InSAR Time Series). The wavelet decomposition efficiently deals with commonly seen spatial covariances in repeat-pass InSAR measurements, since the coefficients of the wavelets are essentially spatially uncorrelated. Our time-dependent parametrization is capable of capturing both recognized and unrecognized processes, and is not arbitrarily tied to the times of the SAR acquisitions. We estimate deformation in the wavelet-domain, using a cross-validated, regularized least squares inversion. We include a model-resolution-based regularization, in order to more heavily damp the model during periods of sparse SAR acquisitions, compared to during times of dense acquisitions. To illustrate the application of MInTS, we consider a catalog of 92 ERS and Envisat interferograms, spanning 16 years, in the Long Valley caldera, CA, region. MInTS analysis captures the ground deformation with high spatial density over the Long Valley region.},
  file         = {:home/baffelli/Library/Hetland et al. - 2012 - Multiscale InSAR Time Series (MInTS) analysis of surface deformation.pdf:pdf},
  isbn         = {0148-0227},
  keywords     = {InSAR,geodesy,time-dependent deformation},
}

@Article{Hetland2012a,
  author       = {Hetland, E. A. and Mus{\'{e}}, P. and Simons, M. and Lin, Y. N. and Agram, P. S. and Dicaprio, C. J.},
  title        = {{Multiscale InSAR Time Series (MInTS) analysis of surface deformation}},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  date         = {2012},
  volume       = {117},
  pages        = {1--17},
  issn         = {21699356},
  doi          = {10.1029/2011JB008731},
  abstract     = {We present a new approach to extracting spatially and temporally continuous ground deformation fields from interferometric synthetic aperture radar (InSAR) data. We focus on unwrapped interferograms from a single viewing geometry, estimating ground deformation along the line-of-sight. Our approach is based on a wavelet decomposition in space and a general parametrization in time. We refer to this approach as MInTS (Multiscale InSAR Time Series). The wavelet decomposition efficiently deals with commonly seen spatial covariances in repeat-pass InSAR measurements, since the coefficients of the wavelets are essentially spatially uncorrelated. Our time-dependent parametrization is capable of capturing both recognized and unrecognized processes, and is not arbitrarily tied to the times of the SAR acquisitions. We estimate deformation in the wavelet-domain, using a cross-validated, regularized least squares inversion. We include a model-resolution-based regularization, in order to more heavily damp the model during periods of sparse SAR acquisitions, compared to during times of dense acquisitions. To illustrate the application of MInTS, we consider a catalog of 92 ERS and Envisat interferograms, spanning 16 years, in the Long Valley caldera, CA, region. MInTS analysis captures the ground deformation with high spatial density over the Long Valley region.},
  file         = {:home/baffelli/Library/Hetland et al. - 2012 - Multiscale InSAR Time Series (MInTS) analysis of surface deformation(2).pdf:pdf},
  isbn         = {0148-0227},
  keywords     = {InSAR,geodesy,time-dependent deformation},
}

@Article{Hines1953a,
  author       = {Hines, J. N. and Rumsey, V. H. and Walter, C. H.},
  title        = {{Traveling-Wave Slot Antennas}},
  journaltitle = {Proceedings of the IRE},
  date         = {1953},
  volume       = {41},
  pages        = {1624--1631},
  issn         = {00968390},
  doi          = {10.1109/JRPROC.1953.274190},
  abstract     = {The traveling-wave slot antenna is similar to a traveling-wave wire antenna, but it is far more versatile because the phase velocity and rate of radiation of the fields in the antenna can be controlled. Four types of traveling-wave slot antennas have been identified. These are: (a) the conventional transverse electric, TE (no tangential E field parallel to the slot length); (b) transverse magnetic, TM (no tangential H field parallel to the slot length); (c) a hybrid with negligible transverse E, and (d) a hybrid with negligible normal H. Only the hybrid types are capable of producing maximum radiation in the direction of the slot axis (i. e., end-fire radiation). The complex propagation constant which is characteristic of uniform traveling-wave slots has been measured for a variety of waveguide geometries and is presented in the form of graphs. The radiation pattern of a traveling-wave slot can be controlled to give low side lobe or "cosecant squared" type patterns by appropriate variation of slot width with distance z along the axis. An approximate formula for the variation of attenuation {\^{A}}¿ with z required to give a specified pattern can be derived. This in turn gives the required variation of slot width with z. An examination of the principle of superposition shows that the conventional technique of array design is an approximation which has proved inadequate in the design of certain slot arrays.},
  file         = {:home/baffelli/Library/Hines, Rumsey, Walter - 1953 - Traveling-Wave Slot Antennas.pdf:pdf},
}

@Article{Hondt2013,
  author        = {Hondt, Olivier D and Guillaso, St{\'{e}}phane and Hellwich, Olaf},
  title         = {{Iterative Bilateral Filtering of Polarimetric SAR Data}},
  journaltitle  = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  date          = {2013},
  volume        = {6},
  pages         = {1628--1639},
  issn          = {1939-1404},
  doi           = {10.1109/JSTARS.2013.2256881},
  abstract      = {In this paper, we introduce an iterative speckle filtering method for polarimetric SAR (PolSAR) images based on the bilateral filter. To locally adapt to the spatial structure of images, this filter relies on pixel similarities in both spatial and radiometric domains. To deal with polarimetric data, we study the use of similarities based on a statistical distance called Kullback-Leibler divergence as well as two geodesic distances on Riemannian manifolds. To cope with speckle, we propose to progressively refine the result thanks to an iterative scheme. Experiments are run over synthetic and experimental data. First, simulations are generated to study the effects of filtering parameters in terms of polarimetric reconstruction error, edge preservation and smoothing of homogeneous areas. Comparison with other methods shows that our approach compares well to other state of the art methods in the extraction of polarimetric information and shows superior performance for edge restoration and noise smoothing. The filter is then applied to experimental data sets from ESAR and FSAR sensors (DLR) at L-band and S-band, respectively. These last experiments show the ability of the filter to restore structures such as buildings and roads and to preserve boundaries between regions while achieving a high amount of smoothing in homogeneous areas.},
  keywords      = {Covariance matrix,ESAR sensor,FSAR sensor,Kullback-Leibler divergence,L-band radar,Riemannian manifold,S-band radar,filtering theory,geodesic distance,image denoising,iterative bilateral filtering,iterative speckle filtering method,parameter extraction,polarimetric SAR data,polarimetric SAR image,polarimetric reconstruction error,radar imaging,radar polarimetry,statistical analysis,statistical distance,synthetic aperture radar},
  mendeley-tags = {Covariance matrix,ESAR sensor,FSAR sensor,Kullback-Leibler divergence,L-band radar,Riemannian manifold,S-band radar,filtering theory,geodesic distance,image denoising,iterative bilateral filtering,iterative speckle filtering method,parameter extraction,polarimetric SAR data,polarimetric SAR image,polarimetric reconstruction error,radar imaging,radar polarimetry,statistical analysis,statistical distance,synthetic aperture radar},
}

@Article{Hoshino2013,
  author    = {T. Hoshino and K. Suwa and N. Oishi and T. Wakayama},
  title     = {Slightly moved vehicle detection with coherent change detection on X-band high resolution SAR imagery},
  year      = {2013},
  month     = {Sept},
  pages     = {585-588},
  booktitle = {Proceedings of the Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)},
  keywords  = {geophysical techniques;radar imaging;remote sensing by radar;synthetic aperture radar;vehicle detection;coherent change detection;X-band high resolution SAR imagery;satellite-borne SAR;synthetic aperture radar;effective remote sensor;daily geo-surface measurement;effective change detection system;temporal SAR images;Vehicles;Synthetic aperture radar;Coherence;Monitoring;Remote sensing;Satellites;Azimuth;synthetic aperture radar;coherent change detection;vehicle;parking;monitoring;satellite},
}

@Article{Ma2015,
  author       = {{Hui Ma} and Antoniou, Michail and Cherniakov, Mikhail},
  title        = {{Passive GNSS-Based SAR Resolution Improvement Using Joint Galileo E5 Signals}},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  date         = {2015-08},
  volume       = {12},
  pages        = {1640--1644},
  issn         = {1545-598X},
  doi          = {10.1109/LGRS.2015.2417594},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7088585},
  file         = {:home/baffelli/Library/Hui Ma, Antoniou, Cherniakov - 2015 - Passive GNSS-Based SAR Resolution Improvement Using Joint Galileo E5 Signals.pdf:pdf},
  keywords     = {bistatic synthetic aperture radar,bsar,e5 channel combination,galileo,gnss-based sar},
}

@PhdThesis{Huynen1970,
  author      = {Huynen, Jean Richard},
  title       = {{Phenomenological Theory of Radar Targets}},
  institution = {{TU Delft}},
  year        = {1970},
  date        = {1970},
  doi         = {10.1016/b978-0-12-709650-6.50020-1},
  file        = {:P1957-2209.pdf:PDF},
  publisher   = {Drukkerij Bronder-Offset N.V.},
}

@Article{Iannini2011,
  author       = {Iannini, L. and {Monti Guarnieri}, A.},
  title        = {Atmospheric phase screen in ground-based radar: Statistics and compensation},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  year         = {2011},
  date         = {2011},
  volume       = {8},
  month        = {may},
  pages        = {537--541},
  issn         = {1545598X},
  doi          = {10.1109/LGRS.2010.2090647},
  abstract     = {In this letter, we face one of the main issues in ground-based radar applications, i.e., the evaluation and removal of the atmospheric phase screen (APS). The time-varying delay statistics are assessed by means of both radars and meteo simulated data sets and are critically interpreted with particular reference to the entailed compensation issues. A compensation approach based on the available on-site meteo parameters (pressure, temperature, and humidity) is then investigated. The technique proposes an initial calibration step on humidity which leads to significant improvements in the APS removal. The results of the technique are discussed in the case of a real campaign data set (Bolzano, Italy) that covers a temporal baseline of about one week.},
  file         = {:home/baffelli/Library/Iannini, Monti Guarnieri - 2011 - Atmospheric phase screen in ground-based radar Statistics and compensation.pdf:pdf},
  keywords     = {Atmospheric artifact compensation,differential interferometry,ground-based radar (GB-RADAR)},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Iglesias2014a,
  author       = {Ruben Iglesias and Albert Aguasca and Xavier Fabregas and Jordi J. Mallorqui and Dani Monells and Carlos Lopez-Martinez and Luca Pipia},
  title        = {Ground-Based Polarimetric {SAR} Interferometry for the Monitoring of Terrain Displacement Phenomena{\textendash}Part {II}: Applications},
  journal      = {{IEEE} Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  journaltitle = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {8},
  pages        = {1--14},
  issn         = {1939-1404},
  doi          = {10.1109/JSTARS.2014.2366711},
  file         = {:home/baffelli/Library/Iglesias et al. - 2014 - Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain Displacement Phenomena-Part II Appli.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Iglesias2012,
  author       = {Iglesias, Ruben and Fabregas, Xavier and Aguasca, Albert and Lopez-Martinez, Carlos and Alonso-Gonz{\'{a}}lez, Alberto and Mallorqui, Jordi J.},
  title        = {{Polarimetric optimization for DInSAR pixel selection with ground-based SAR}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2012-07},
  publisher    = {IEEE},
  isbn         = {978-1-4673-1159-5},
  pages        = {3122--3125},
  doi          = {10.1109/IGARSS.2012.6350764},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6350764},
  file         = {:home/baffelli/Library/Iglesias et al. - 2012 - Polarimetric optimization for DInSAR pixel selection with ground-based SAR.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Iglesias2014c,
  author       = {Ruben Iglesias and Xavier Fabregas and Albert Aguasca and Jordi J. Mallorqui and Carlos Lopez-Martinez and Josep A. Gili and Jordi Corominas},
  title        = {Atmospheric Phase Screen Compensation in Ground-Based {SAR} With a Multiple-Regression Model Over Mountainous Regions},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {52},
  month        = {may},
  pages        = {2436--2449},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2013.2261077},
  abstract     = {In this paper, a new model-based technique for the compensation of severe height-dependent atmospheric artifacts, using ground-based synthetic aperture radar (SAR) data over mountainous regions, is proposed. The method presented represents an extension of already existing techniques, but now taking into account the effect of steep topography in the atmospheric phase screen compensation process. In addition, the technique is adapted to work with polarimetric SAR data, showing, in that case, a noticeable improvement in the compensation process. The method is validated in the mountainous environment of El Forn de Canillo, located in the Andorran Pyrenees, where there is a slow-moving landslide that nowadays is being reactivated coinciding with strong rain episodes. In this framework, ten zero-baseline fully polarimetric data sets have been acquired at X-band during a one-year measurement campaign (October 2010–October 2011) with the GB-SAR sensor developed at the Universitat Polit{\`{e}}cnica de Catalunya. First, the impact of the severe atmospheric fluctuations among multitemporal GB-SAR measurements is carefully studied and analyzed. Hence, the need to correctly estimate and compensate the resulting phase differences when retrieving interferometric information is put forward in the frame of differential-SAR-interferometry applications.},
  file         = {:home/baffelli/Library/Iglesias et al. - 2014 - Atmospheric phase screen compensation in ground-based sar with a multiple-regression model over mountainous reg.pdf:pdf},
  isbn         = {5},
  keywords     = {Atmospheric phase screen (APS) compensation,differential synthetic aperture radar (SAR) interf,ground-based SAR (GB-SAR),polarimetry,steep topography},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Iglesias2014b,
  author       = {Ruben Iglesias and Dani Monells and Xavier Fabregas and Jordi J. Mallorqui and Albert Aguasca and Carlos Lopez-Martinez},
  title        = {Phase Quality Optimization in Polarimetric Differential {SAR} Interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {52},
  month        = {may},
  pages        = {2875--2888},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2013.2267095},
  abstract     = {In this paper, a study of polarimetric optimization techniques in the frame of differential synthetic aperture radar (SAR) interferometry (DInSAR) is considered. Historically, DInSAR techniques have been limited to the single-polarimetric case, mainly due to the unavailability of fully polarimetric data. Lately, the launch of satellites with polarimetric capabilities, such as the Advanced Land Observing Satellite (ALOS), RADARSAT-2, or TerraSAR-X, allowed merging polarimetric and interferometric techniques to improve the pixels' phase quality and, thus, the density and the reliability of the final DInSAR results. The relationship between the polarimetrically optimized coherence or amplitude dispersion maps and the final DInSAR results is carefully analyzed, using both orbital and ground-based SAR fully polarimetric data. DInSAR processing using polarimetric optimization techniques in the pixel selection process is compared with the classical single-polarimetric approach, achieving up to a threefold increase of the number of pixel candidates in the coherence case and up to a factor of seven in the amplitude dispersion case.},
  file         = {:home/baffelli/Library/Iglesias et al. - 2014 - Phase quality optimization in polarimetric differential SAR interferometry.pdf:pdf},
  keywords     = {Amplitude dispersion optimization,coherence optimization,differential synthetic aperture radar (SAR) interf,polarimetric DInSAR (PolDInSAR),polarimetry},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{In1980a,
  author       = {In, Time},
  title        = {{[K,, K2,}},
  journaltitle = {October},
  date         = {1980},
  volume       = {17},
  pages        = {1008--1011},
  file         = {:home/baffelli/Library/In - 1980 - K,, K2,.pdf:pdf},
  isbn         = {9998722039},
}

@Article{Itten2008,
  author       = {Itten, Klaus I. and Dell'Endice, Francesco and Hueni, Andreas and Kneub{\"{u}}hler, Mathias and Schl{\"{a}}pfer, Daniel and Odermatt, Daniel and Seidel, Felix and Huber, Silvia and Schopfer, J{\"{u}}rg and Kellenberger, Tobias and B{\"{u}}hler, Yves and D'Odorico, Petra and Nieke, Jens and Alberti, Edoardo and Meuleman, Koen},
  title        = {{APEX - the Hyperspectral ESA Airborne Prism Experiment}},
  journaltitle = {Sensors},
  date         = {2008},
  volume       = {8},
  pages        = {6235--6259},
  issn         = {1424-8220},
  doi          = {10.3390/s8106235},
  url          = {http://www.mdpi.com/1424-8220/8/10/6235/},
  abstract     = {The airborne ESA-APEX (Airborne Prism Experiment) hyperspectral mission simulator is described with its distinct specifications to provide high quality remote sensing data. The concept of an automatic calibration, performed in the Calibration Home Base (CHB) by using the Control Test Master (CTM), the In-Flight Calibration facility (IFC), quality flagging (QF) and specific processing in a dedicated Processing and Archiving Facility (PAF), and vicarious calibration experiments are presented. A preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user is presented for limnology, vegetation, aerosols, general classification routines and rapid mapping tasks. BRDF (Bidirectional Reflectance Distribution Function) issues are discussed and the spectral database SPECCHIO (Spectral Input/Output) introduced. The optical performance as well as the dedicated software utilities make APEX a state-of-the-art hyperspectral sensor, capable of (a) satisfying the needs of several research communities and (b) helping the understanding of the Earth's complex mechanisms.},
  file         = {:home/baffelli/Library/Itten et al. - 2008 - APEX - the Hyperspectral ESA Airborne Prism Experiment.pdf:pdf},
  isbn         = {1424-8220},
  keywords     = {Hyperspectral, pushbroom, imaging spectrometer,},
}

@Article{Jacome2013,
  author    = {Jacome, Andres and Bernier, Monique and Chokmani, Karem and Gauthier, Yves and Poulin, Jimmy and S{\`{e}}ve, Danielle De},
  title     = {{Monitoring Volumetric Surface Soil Moisture Content at the La Grande Basin Boreal Wetland by Radar Multi Polarization Data}},
  journal   = {Remote Sensing},
  year      = {2013},
  date      = {2013},
  volume    = {5},
  month     = {oct},
  pages     = {4919--4941},
  doi       = {10.3390/rs5104919},
  abstract  = {Understanding the hydrological dynamics of boreal wetland ecosystems (peatlands) is essential in order to better manage hydropower inter-annual productivity at the La Grande basin (Northern Quebec, QC, Canada). Given the remoteness and the huge dimension of the La Grande basin, it is imperative to develop remote sensing monitoring techniques to retrieve hydrological parameters. The main objective of this study is to find out if multi-date and multi-polarization Radar Satellite 2 (RADARSAT-2) (C-band) image analysis could detect seasonal variations of surface soil moisture conditions of the acrotelm. A change detection approach through the use of multi temporal indexes was chosen based on the assumption that the temporal variability of surface roughness and natural vegetation biomass is generally at a much longer time scale than that of surface soil moisture ($\Delta$-Index is based on a reference image that represents dry soil, in order to maximize the sensitivity of $\sigma$° to changes in soil moisture with respect to the same location when soil is wet). The $\Delta$-Index approach was tested with each polarization: $\sigma$° for fully polarimetric mode (HH, HV, VV) and the cross-polarization coefficient (HV/HH). Results show that the best regression adjustment with regard to surface soil moisture content in boreal wetlands was obtained with the cross-polarization coefficient. The cross-polarization multi-temporal index enables precise volumetric surface soil moisture estimation and monitoring on boreal wetlands, regardless of the influence of vegetation cover and surface roughness conditions (bias was under 1{\%}, standard deviation and RMSE were under 10{\%} for almost all estimation errors). Surface soil moisture estimation was more precise over permanently flooded areas than seasonally flooded ones (standard deviation is systematically greater for the seasonally flooded areas, at all analyzed scales), although the overall quality of the estimation is still precise. Cross-polarization ratio im},
  file      = {:home/baffelli/Library/Jacome et al. - 2013 - Monitoring Volumetric Surface Soil Moisture Content at the La Grande Basin Boreal Wetland by Radar Multi Polariza.pdf:pdf},
  keywords  = {RADARSAT-2,SAR,boreal wetland,cross polarization,remote sensing,soil moisture},
  publisher = {{MDPI} {AG}},
}

@Article{Jia2015,
  author = {Jia, Gaowei and Chang, Wenge and Tu, Ruibin},
  title  = {{Analysis of the Imaging Realization of Frequency Modulated Continuous Wave Circular SAR}},
  date   = {2015},
  volume = {1},
  pages  = {2158--2162},
  file   = {:home/baffelli/Library/Jia, Chang, Tu - 2015 - Analysis of the Imaging Realization of Frequency Modulated Continuous Wave Circular SAR.pdf:pdf},
}

@Article{Jolivet2014,
  author       = {Romain Jolivet and Piyush Shanker Agram and Nina Y. Lin and Mark Simons and Marie-Pierre Doin and Gilles Peltzer and Zhenhong Li},
  title        = {Improving {InSAR} geodesy using Global Atmospheric Models},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {2014},
  date         = {2014},
  volume       = {119},
  month        = {mar},
  pages        = {2324--2341},
  issn         = {2169-9356},
  doi          = {10.1002/2013JB010588},
  file         = {:file\:/home/baffelli/Downloads/Jolivet_et_al-2014-Journal_of_Geophysical_Research-_Solid_Earth.pdf:PDF},
  keywords     = {Instruments and techniques, Space geodetic surveys, Tectonic deformation, InSAR, atmospheric phase screen, Global Atmospheric Models, tectonic deformations, Teledetection},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Jolivet2011,
  author       = {R. Jolivet and R. Grandin and C. Lasserre and M.-P. Doin and G. Peltzer},
  title        = {Systematic {InSAR} tropospheric phase delay corrections from global meteorological reanalysis data},
  journal      = {Geophysical Research Letters},
  journaltitle = {Geophysical Research Letters},
  year         = {2011},
  date         = {2011},
  volume       = {38},
  month        = {sep},
  pages        = {1--6},
  issn         = {00948276},
  doi          = {10.1029/2011GL048757},
  abstract     = {Despite remarkable successes achieved by Differential InSAR, estimations of low tectonic strain rates remain challenging in areas where deformation and topography are correlated, mainly because of the topography-related atmospheric phase screen (APS). In areas of high relief, empirical removal of the stratified component of the APS may lead to biased estimations of tectonic deformation rates. Here we describe a method to correct interferograms from the effects of the spatial and temporal variations in tropospheric stratification by computing tropospheric delay maps coincident with SAR acquisitions using the ERA-Interim global meteorological model. The modeled phase delay is integrated along vertical profiles at the ERA-I grid nodes and interpolated at the spatial sampling of the interferograms above the elevation of each image pixel. This approach is validated on unwrapped interferograms. We show that the removal of the atmospheric signal before phase unwrapping reduces the risk of unwrapping errors in areas of rough topography.},
  file         = {:home/baffelli/Library/Jolivet et al. - 2011 - Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data.pdf:pdf},
  isbn         = {1944-8007},
  keywords     = {http://dx.doi.org/10.1029/2011GL048757, doi:10.102},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Jolivet2012,
  author       = {Jolivet, R. and Lasserre, C. and Doin, M. P. and Guillaso, S. and Peltzer, G. and Dailu, R. and Sun, J. and Shen, Z. K. and Xu, X.},
  title        = {{Shallow creep on the Haiyuan fault (Gansu, China) revealed by SAR interferometry}},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  date         = {2012},
  volume       = {117},
  pages        = {1--18},
  issn         = {21699356},
  doi          = {10.1029/2011JB008732},
  abstract     = {Interferometric synthetic aperture radar data are used to map the interseismic velocity field along the Haiyuan fault system (HFS), at the north-eastern boundary of the Tibetan plateau. Two M ∼ 8 earthquakes ruptured the HFS in 1920 and 1927, but its 260 km-long central section, known as the Tianzhu seismic gap, remains unbroken since ∼1000 years. The Envisat SAR data, spanning the 2003–2009 period, cover about 200 × 300 km2 along three descending and two ascending tracks. Interferograms are processed using an adapted version of ROI{\_}PAC. The signal due to stratified atmospheric phase delay is empirically corrected together with orbital residuals. Mean line-of-sight velocity maps are computed using a constrained time series analysis after selection of interferograms with low atmospheric noise. These maps show a dominant left-lateral motion across the HFS, and reveal a narrow, 35 km-long zone of high velocity gradient across the fault in between the Tianzhu gap and the 1920 rupture. We model the observed velocity field using a discretized fault creeping at shallow depth and a least squares inversion. The inferred shallow slip rate distribution reveals aseismic slip in between two fully locked segments. The average creep rate is ∼5 mm yr−1, comparable in magnitude with the estimated loading rate at depth, suggesting no strain accumulation on this segment. The modeled creep rate locally exceeds the long term rate, reaching 8 mm yr−1, suggesting transient creep episodes. The present study emphasizes the need for continuous monitoring of the surface velocity in the vicinity of major seismic gaps in terms of seismic hazard assessment.},
  file         = {:home/baffelli/Library/Jolivet et al. - 2012 - Shallow creep on the Haiyuan fault (Gansu, China) revealed by SAR interferometry.pdf:pdf},
}

@Article{Jones1981,
  author = {Jones, W},
  title  = {{Writing scientific papers and reports}},
  date   = {1981},
  pages  = {1--21},
  file   = {:home/baffelli/Library/Jones - 1981 - Writing scientific papers and reports.pdf:pdf},
  isbn   = {0697037738},
}

@Article{N1996,
  author       = {Ian Joughin and Ron Kwok and Mark Fahnestock},
  title        = {Estimation of ice-sheet motion using satellite radar interferometry: method and error analysis with application to {Humboldt Glacier}, {Greenland}},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {1996},
  date         = {1996-01},
  volume       = {42},
  pages        = {564--575},
  issn         = {0022-1430},
  doi          = {10.1017/S0022143000003543},
  url          = {https://www.cambridge.org/core/product/identifier/S0022143000003543/type/journal{\_}article},
  abstract     = {Satellite radar interferometry provides glaciologists with an important new tool for determining the motion and topography of large ice sheets. We examine the sources of error in interferometrically derived ice-motion measurements, including those errors due to inaccurate estimates of the interfero-metric baseline. Several simulations are used to assess baseline accuracy in terms of tie-point error and the number and distribution of tie points. These results give insight into how best to select tie points, and also demonstrate the level of accuracy that can be achieved. Examination of two representative cases likely to occur in mapping ice-sheet motion leads to the conclusion that with adequate tie-point information ice velocity can be measured accurately to within a few meters per year. A method to correct horizontal velocity estimates for the effect of vertical displacement using surface slopes is also developed. Finally, we estimate the single-component velocity field for an area on Humboldt Glacier, northern Greenland, using interferograms formed from ERS-1 SAR image. We estimatе that these velocity measurements are accurate to within 2.3 m year 1 .},
  file         = {:home/baffelli/Library/Joughin, Kwok, Fahnestock - 1996 - Estimation of ice-sheet motion using satellite radar interferometry method and error analysis with ap.pdf:pdf},
  publisher    = {Cambridge University Press ({CUP})},
}

@Article{Jung2014,
  author       = {Jungkyo Jung and Duk-jin Kim and Sang-Eun Park},
  title        = {Correction of Atmospheric Phase Screen in Time Series {InSAR} Using {WRF} Model for Monitoring Volcanic Activities},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {52},
  month        = {may},
  pages        = {2678--2689},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2013.2264532},
  abstract     = {利用InSAR测量地表形变的局限在于，存在大气延迟的影响。在火山地区，大气相位延迟影响探测火山动荡，原因在与大气厚度与火山的海拔高度相反。众所周知，APS（大气相位屏？？）可以由分层和湍流两部分组成。本文利用WRF模型模拟火山地区的分层的、湍流大气情况，然后将模拟得到的结果与当地的无线电探空仪的观测量比较。比较结果证明，WRF模型模拟得到的结果能够反映出气候合理的季节变化，并在垂直剖面上。我们还发现分层的APS与时间有着重要的联系，有时严重限制了估计火山变形的精度。这些结果表明高通滤波(在InSAR时序分析中提取和移除APS)在火山地区并不奏效。因此，我们采用新的方法---WRF应用到分层的APS中，WRF与地形有关；残留的APS能够运用PSI的HP滤波消除掉。我们使用含大气纠正的PSI算法应用在ALOS的L波段的SAR数据(覆盖Shinmoedake火山)，发现估计的地表形变与根据GPS计算得到的地表形变符合良好；估计的APS与中尺度光学影像数据符合良好。},
  file         = {:home/baffelli/Library/Jung, Kim, Park - 2014 - Correction of atmospheric phase screen in time series InSAR using WRF model for monitoring volcanic activities.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Atmospheric phase screen (APS),stratified APS,time series interferometric synthetic aperture rad,volcano,weather research and forecasting (WRF)},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Kaab2002,
  author       = {Andreas Kääb},
  title        = {Monitoring high-mountain terrain deformation from repeated air- and spaceborne optical data: examples using digital aerial imagery and {ASTER} data},
  journal      = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  journaltitle = {ISPRS Journal of Photogrammetry and Remote Sensing},
  year         = {2002},
  date         = {2002},
  volume       = {57},
  month        = {nov},
  pages        = {39--52},
  issn         = {09242716},
  doi          = {10.1016/S0924-2716(02)00114-4},
  abstract     = {High mountains represent one of the most dynamic environments on earth. Monitoring their terrain changes is necessary to understand mass-transport systems, to detect related environmental variability, and to assess natural hazards. Here, we apply standard software to automatically generate digital elevation models (DEM) from aerial photography and Advanced Spacebome Thermal Emission and Reflection Radiometer (ASTER) satellite stereo imagery. By comparison to a photogrammetrically derived DEM, an accuracy of ± 60 m RMS of the ASTER DEM was found for rough high-mountain topography, and ± 18 m RMS for moderately mountainous terrain. Differences between multi-temporal DEMs are used to determine vertical terrain changes. Horizontal movements are computed from multi-temporal orthoimages. The techniques are applied for three case studies. (1) The flow-field of Tasman glacier, New Zealand, as measured from ASTER data, showed glacier speeds of up to 250 m per year and a surprising minimum speed in the middle of the glacier. (2) The velocity-field of creeping mountain permafrost in Val Muragl, Swiss Alps, with speeds of up to 0.5 m per year was determined with high resolution from aerial stereo imagery and provided new insights in the spatial coherence of permafrost creep. (3) Deformations of up to 0.1 m per year on a large landslide near Aletsch glacier, Swiss Alps, could be detected. As a rule of thumb, we estimate the achieved accuracy for elevation changes and horizontal displacements to approximate the size of one image pixel, i.e. 15 m for ASTER and 0.2-0.3 m for the here-used aerial photography. {\textcopyright} 2002 Elsevier Science B.V. All rights reserved.},
  file         = {:home/baffelli/Library/K{"{a}}{"{a}}b - 2002 - Monitoring high-mountain terrain deformation from repeated air- and spaceborne optical data Examples using digital aeria.pdf:pdf},
  isbn         = {0924-2716},
  keywords     = {ASTER,DEM,Digital photogrammetry,Displacement,Glacier,Landslide,Mountains,Natural hazards,Permafrost,Remote sensing},
  pmid         = {147},
  publisher    = {Elsevier {BV}},
}

@Article{Kaab2005,
  author       = {A. Kääb and C. Huggel and L. Fischer and S. Guex and F. Paul and I. Roer and N. Salzmann and S. Schlaefli and K. Schmutz and D. Schneider and T. Strozzi and Y. Weidmann},
  title        = {Remote sensing of glacier- and permafrost-related hazards in high mountains: an overview},
  journal      = {Natural Hazards and Earth System Science},
  journaltitle = {Natural Hazards and Earth System Sciences},
  year         = {2005},
  date         = {2005},
  volume       = {5},
  month        = {jul},
  pages        = {527--554},
  issn         = {16849981},
  doi          = {10.5194/nhess-5-527-2005},
  abstract     = {Process interactions and chain reactions, the present shift of cryospheric hazard zones due to atmospheric warming, and the potential far reach of glacier disastersmake it necessary to apply modern remote sensing techniques for the assessment of glacier and permafrost hazards in high mountains. Typically, related hazard source areas are situ-ated in remote regions, often difficult to access for physical and/or political reasons. In this contribution we provide an overview of air- and spaceborne remote sensing methods suitable for glacier and permafrost hazard assessment and disaster management. A number of image classification and change detection techniques support high-mountain hazard studies. Digital terrain models (DTMs), derived from optical stereo data, synthetic aperture radar or laserscanning, represent one of the most important data sets for investigating high-mountain processes. Fusion of satellite stereo-derived DTMs with the DTM from the Shuttle Radar Topography Mission (SRTM) is a promising way to combine the advantages of both technologies. Large changes in terrain volume such as from avalanche deposits can indeed be measured even by repeat satellite DTMs. Multitemporal data can be used to derive surface displacements on glaciers, permafrost and landslides. Combining DTMs, results from spectral image classification, and multitemporal data from change detection and displacement measurements significantly improves the detection of hazard potentials. Modelling of hazardous processes based on geographic information systems (GIS) complements the remote sensing analyses towards an integrated assessment of glacier and permafrost hazards in mountains. Major present limitations in the application of remote sensing to glacier and permafrost hazards in mountains are, on the one hand, of technical nature (e.g. combination and fusion of different methods and data; improved understanding of microwave backscatter). On the other hand, better dissemination of remote sensing expertise towards institutions involved in high-mountain hazard assessment and management is needed in order to exploit the large potential of remote sensing in this field.},
  file         = {:home/baffelli/Library/K{"{a}}{"{a}}b et al. - 2005 - Remote sensing of glacier- and permafrost-related hazards in high mountains an overview.pdf:pdf},
  isbn         = {1561863315618},
  publisher    = {Copernicus {GmbH}},
}

@Article{Kaab2003,
  author       = {Andy Kääb and Rick Wessels and Wilfried Haeberli and Christian Huggel and Jeffrey S. Kargel and Siri Jodha Singh Khalsa},
  title        = {Rapid {ASTER} imaging facilitates timely assessment of glacier hazards and disasters},
  journal      = {Eos, Transactions American Geophysical Union},
  journaltitle = {Eos, Transactions American Geophysical Union},
  year         = {2003},
  date         = {2003},
  volume       = {84},
  pages        = {117},
  issn         = {0096-3941},
  doi          = {10.1029/2003EO130001},
  abstract     = {Glacier- and permafrost-related hazards increasingly threaten human lives, settlements, and infrastructure in high-mountain regions. Present atmospheric warming particularly affects terrestrial systems where surface and sub-surface ice are involved. Changes in glacier and permafrost equilibrium are shifting beyond historical knowledge. Human settlement and activities are extending toward danger zones in the cryospheric system. A number of recent glacier hazards and disasters underscore these trends. Difficult site access and the need for fast data acquisition make satellite remote sensing of crucial importance in high-mountain hazard management and disaster mapping.},
  file         = {:home/baffelli/Library/K{"{a}}{"{a}}b et al. - 2003 - Rapid ASTER imaging facilitates timely assessment of glacier hazards and disasters.pdf:pdf},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Kaiser1980,
  author       = {Kaiser, James F. and Schafer, Ronald W.},
  title        = {{On the use of the I0-Sinh Window for Spectrum Analysis}},
  journaltitle = {IEEE Transactions on Acoustics, Speech, and Signal Processing},
  date         = {1980},
  volume       = {28},
  pages        = {105--107},
  issn         = {00963518},
  doi          = {10.1109/TASSP.1980.1163349},
  abstract     = {Closed form expressions for main-lobe width, modified main-lobe width, and relative sidelobe amplitude are given for the I{\_}{\{}0{\}}- $\backslash$sinh window function. These formulas facilitate exploring the tradeoff between record length, spectral resolution, and leakage in digital spectrum analysis. An especially simple empirical approximation relating main-lobe width and relative sidelobe amplitude is given.},
  file         = {:home/baffelli/Library/Kaiser, Schafer - 1980 - On the use of the I0-Sinh Window for Spectrum Analysis.pdf:pdf},
}

@Article{Kalman1960,
  author       = {Kalman, R. E.},
  title        = {{A New Approach to Linear Filtering and Prediction Problems}},
  journaltitle = {Journal of Basic Engineering},
  date         = {1960},
  volume       = {82},
  pages        = {35},
  issn         = {00219223},
  doi          = {10.1115/1.3662552},
  url          = {http://scholar.google.com/scholar?hl=en{\&}btnG=Search{\&}q=intitle:A+New+Approach+to+Linear+Filtering+and+Prediction+Problems{\#}0{\%}5Cnhttp://fluidsengineering.asmedigitalcollection.asme.org/article.aspx?articleid=1430402},
  abstract     = {The classical filtering and prediction problem is re-examined using the Bode- Shannon representation of random processes and the state transition method of analysis of dynamic systems. New results are: (1) The formulation and methods of solution of the problem apply without modifica- tion to stationary and nonstationary statistics and to growing-memory and infinite- memory filters. (2) A nonlinear difference (or differential) equation is derived for the covariance matrix of the optimal estimation error. From the solution of this equation the co- efficients of the difference (or differential) equation of the optimal linear filter are ob- tained without further calculations. (3) The filtering problem is shown to be the dual of the noise-free regulator problem. The new method developed here is applied to two well-known problems, confirming and extending earlier results. The discussion is largely self-contained and proceeds from first principles; basic concepts of the theory of random processes are reviewed in the Appendix.},
  file         = {:home/baffelli/Library/Kalman - 1960 - A New Approach to Linear Filtering and Prediction Problems.pdf:pdf},
  isbn         = {9783540769897},
  keywords     = {kalman filter,lineal filter,prediction,predictor},
  pmid         = {5311910},
}

@Book{Kampes2006,
  author    = {Kampes, Bert M.},
  title     = {Radar interferometry},
  year      = {2006},
  date      = {2006},
  publisher = {Springer Netherlands},
  isbn      = {978-1-4020-4576-9},
  doi       = {10.1007/978-1-4020-4723-7},
  url       = {http://www.iub.edu/{~}act/files/publications/2004/04-12{\_}LUCCPathways{\_}Impacts.pdf http://link.springer.com/10.1007/978-1-4020-4723-7},
  file      = {:home/baffelli/Library/Kampes - 2006 - Radar interferometry.pdf:pdf},
}

@InProceedings{Kang2010,
  author       = {Moon-Kyung Kang and Kwang-Eun Kim and Hoonyol Lee and Seong-Jun Cho and Jae-Hee Lee},
  title        = {Preliminary result of polarization property analysis using fully polarimetric {GB}-{SAR} images},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2010},
  date         = {2010-07},
  publisher    = {{IEEE}},
  month        = {jul},
  isbn         = {978-1-4244-9565-8},
  pages        = {4019--4022},
  doi          = {10.1109/IGARSS.2010.5650762},
  url          = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=5650762 http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5650762},
  file         = {:home/baffelli/Library/Kang et al. - 2010 - Preliminary result of polarization property analysis using fully polarimetric GB-SAR images.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Kang2009,
  author       = {Kang, Moon-Kyung and Kim, Kwang-Eun and Lee, Hoonyol and Cho, Seong-Jun and Lee, Jae-Hee},
  title        = {Preliminary results of polarimetric characteristics for {C}-band quad-polarization {GB-SAR} images using {H / A / $\alpha$} polarimetric decomposition theorem},
  journaltitle = {Korean Journal of Remote Sensing},
  year         = {2009},
  date         = {2009},
  volume       = {25},
  pages        = {531--546},
  file         = {:home/baffelli/Library/Kang et al. - 2009 - Preliminary results of polarimetric characteristics for C-band quad-polarization GB-SAR images using H A a polari.pdf:pdf},
  keywords     = {a,a polarimetric decomposition,fully polarimetric sar,gb-sar,h},
}

@Article{Kenyi2003a,
  author       = {Kenyi, Lado W. and Kaufmann, Viktor},
  title        = {{Estimation of rock glacier surface deformation using SAR interferometry data}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2003},
  volume       = {41},
  pages        = {1512--1515},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2003.811996},
  file         = {:home/baffelli/Library/Kenyi, Kaufmann - 2003 - Estimation of rock glacier surface deformation using SAR interferometry data.pdf:pdf},
  isbn         = {9058095827},
  keywords     = {Differential synthetic aperture radar interferomet,Mountain permafrost creep,Rock glaciers,Synthetic aperture radar (SAR) interferometry},
}

@InProceedings{Kersten2005,
  author        = {Kersten, P.R. and Lee, J.S. and Ainsworth, Thomas L.},
  title         = {{A comparison of change detection statistics in POLSAR images}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {2005-07},
  volume        = {7},
  publisher     = {IEEE},
  isbn          = {0-7803-9050-4},
  pages         = {4836--4839},
  doi           = {10.1109/IGARSS.2005.1526756},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1526756 http://ieeexplore.ieee.org/document/1526756/},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {- change-detection,Covariance matrix,Filters,Pixel,Speckle,Statistical distributions,Statistics,Testing,bartlett,components,contains nine real independent,contrast ratio,ellipticity,hypothesis test,matrix,polsar images,radar imaging,radar polarimetry,statistical analysis,test,the resulting hermitian positive-semidefinite,vector x,which form the,wishart distribution},
  mendeley-tags = {Covariance matrix,Filters,Pixel,Speckle,Statistical distributions,Statistics,Testing,radar imaging,radar polarimetry,statistical analysis},
}

@Article{Klein1992,
  author       = {Klein, JD},
  title        = {{Calibration of complex polarimetric SAR imagery using backscatter correlations}},
  journal      = {{IEEE} Transactions on Aerospace and Electronic Systems},
  journaltitle = {{\ldots} and Electronic Systems, IEEE Transactions on},
  year         = {1992},
  date         = {1992},
  volume       = {28},
  pages        = {183--194},
  issn         = {00189251},
  doi          = {10.1109/7.135444},
  url          = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=135444},
  abstract     = {A new technique for calibration of multipolarization synthetic aperture radar (SAR) imagery is described},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Klein1989,
  author        = {Klein, J.D.},
  title         = {{Calibration of Quadpolarization SAR Data Using Backscatter Statistics}},
  booktitle     = {12\textsuperscript{th} Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,},
  date          = {1989},
  volume        = {5},
  pages         = {2893--2896},
  doi           = {10.1109/IGARSS.1989.575928},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=575928},
  keywords      = {Contamination,Layout,Propulsion,Radar scattering,Statistics,backscatter,calibration,polarization,radar imaging,synthetic aperture radar},
  mendeley-tags = {Contamination,Layout,Propulsion,Radar scattering,Statistics,backscatter,calibration,polarization,radar imaging,synthetic aperture radar},
}

@Article{Kovesi2015,
  author   = {Kovesi, Peter},
  title    = {{Good Colour Maps: How to Design Them}},
  date     = {2015},
  pages    = {1--42},
  url      = {http://arxiv.org/abs/1509.03700},
  abstract = {Many colour maps provided by vendors have highly uneven perceptual contrast over their range. It is not uncommon for colour maps to have perceptual flat spots that can hide a feature as large as one tenth of the total data range. Colour maps may also have perceptual discontinuities that induce the appearance of false features. Previous work in the design of perceptually uniform colour maps has mostly failed to recognise that CIELAB space is only designed to be perceptually uniform at very low spatial frequencies. The most important factor in designing a colour map is to ensure that the magnitude of the incremental change in perceptual lightness of the colours is uniform. The specific requirements for linear, diverging, rainbow and cyclic colour maps are developed in detail. To support this work two test images for evaluating colour maps are presented. The use of colour maps in combination with relief shading is considered and the conditions under which colour can enhance or disrupt relief shading are identified. Finally, a set of new basis colours for the construction of ternary images are presented. Unlike the RGB primaries these basis colours produce images whereby the salience of structures are consistent irrespective of the assignment of basis colours to data channels.},
  arxivid  = {1509.03700},
  file     = {:home/baffelli/Library/Kovesi - 2015 - Good Colour Maps How to Design Them.pdf:pdf},
}

@Book{kraus88,
  author    = {Kraus, J D},
  title     = {{Antennas}},
  date      = {1988},
  edition   = {Second},
  publisher = {McGraw-Hill},
  isbn      = {0074632191},
}

@Article{Krige1952,
  author       = {Krige, D G},
  title        = {A Statistical Approach to Some Basic Mine Valuation Problems on the {Witwatersrand}},
  journaltitle = {Journal of the Chemical, Metallurgical and Mining Society of South Africa},
  date         = {1952},
  pages        = {201--215},
  issn         = {0038-223X},
  doi          = {10.2307/3006914},
  abstract     = {Krige, D. G., “A Statistical Approach to Some Basic Mine Valuation Problems on the Witwatersrand,” Journal of the Chemical, Metallurgical and Mining Society of South Africa, Vol. 52, No. 6, 1951, pp. 119–139.},
  pmid         = {20736204},
}

@Article{Kulpa2013,
  author       = {Kulpa, Janusz S. and Malanowski, Mateusz and Gromek, Damian and Samczy{\'{n}}sk, Piotr and Kulpa, Krzysztof and Gromek, Artur},
  title        = {{Experimental Results of High-Resolution ISAR Imaging of Ground-Moving Vehicles with a Stationary FMCW Radar}},
  journaltitle = {International Journal of Electronics and Telecommunications},
  date         = {2013},
  volume       = {59},
  pages        = {293--299},
  issn         = {0867-6747},
  doi          = {10.2478/eletel-2013-0035},
  url          = {http://www.degruyter.com/view/j/eletel.2013.59.issue-3/eletel-2013-0035/eletel-2013-0035.xml},
  file         = {:home/baffelli/Library/Kulpa et al. - 2013 - Experimental Results of High-Resolution ISAR Imaging of Ground-Moving Vehicles with a Stationary FMCW Radar.pdf:pdf},
  keywords     = {fft,fmcw,fourier transform,image,in practice simple fast,isar,of the signal is,on the,performed to obtain isar,radar imaging,sar,signal can provide information,spectral analysis of the,target shape,translational},
}

@InCollection{Lanaria,
  author    = {Riccardo Lanari and Francesco Casu and Mariarosaria Manzo and Giovanni Zeni and Paolo Berardino and Michele Manunta and Antonio Pepe},
  title     = {An Overview of the Small {BAseline} Subset Algorithm: a {DInSAR} Technique for Surface Deformation Analysis},
  booktitle = {Pure and Applied Geophysics},
  year      = {2007},
  date      = {2007},
  volume    = {164},
  publisher = {Springer Nature},
  isbn      = {0033-4553},
  pages     = {637--661},
  doi       = {10.1007/s00024-007-0192-9},
  url       = {http://www.springerlink.com/index/10.1007/978-3-7643-8417-3{\_}2},
  abstract  = {We present an overview of the Differential SAR Interferometry algorithm referred to as Small BAseline Subset (SBAS) technique, that allows us to detect surface deformation and to analyze their space-time characteristics. Following the description of the main theoretical aspects of the algorithm, we present several results obtained by applying the SBAS approach in selected case studies relevant to phenomena affecting volcanic areas (Campi Flegrei caldera and Somma-Vesuvio complex, Italy), aquifers (Santa Clara area within the San Francisco bay, California) and landslides (Maratea Valley, Italy). The overall analysis is carried out by using multilook DInSAR interferograms with a spatial resolution of the order of 100 × 100 m, computed from SAR data acquired by the ERS-1 and ERS-2 sensors. In particular, we highlight the peculiarities of the SBAS technique and its surface deformation retrieval capability for what concerns both large-scale deformation phenomena and more localized displacement effects. {\textcopyright} Birkh{\"{a}}user Verlag, Basel, 2007.},
  file      = {:home/baffelli/Library/Lanari et al. - 2007 - An overview of the Small BAseline Subset algorithm A DInSAR technique for surface deformation analysis.pdf:pdf},
  issn      = {00334553},
  journal   = {Pure and Applied Geophysics},
  keywords  = {Differential SAR interferometry,SBAS,Surface deformation},
  month     = {apr},
}

@Article{Lasne2004,
  author       = {Lasne, Yannick and Paillou, Philippe and August-Bernex, T. and Ruffie, G. and Grandjean, Gilles},
  title        = {{A phase signature for detecting wet subsurface structures using polarimetric L-band SAR}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2004-08},
  volume       = {42},
  pages        = {1683--1694},
  issn         = {0196-2892},
  doi          = {10.1109/TGRS.2004.830645},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1323125},
  file         = {:home/baffelli/Library/Lasne et al. - 2004 - A phase signature for detecting wet subsurface structures using polarimetric L-band SAR.pdf:pdf},
}

@Article{LeLoch-Duplex1996,
  author       = {{Le Loch-Duplex}, N and Vidal-Madjar, Daniel and Hardange, J.-P.},
  title        = {{On the calibration of the helicopter borne polarimetric radar Ren{\'{e}}}},
  journaltitle = {Annales des Telecommunications/Annals of Telecommunications},
  date         = {1996},
  volume       = {51},
  pages        = {245--257},
  issn         = {00034347 (ISSN)},
  doi          = {10.1007/BF02999804},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0142133313{\&}partnerID=40{\&}md5=d8dab02643f2e6f063441c18e6e488b5},
  abstract     = {The CETP and Thomson-CSF have developed in 1992 a new polarimetric FM/CW X-band radar which has been designed to be easily mounted on small helicopter or aircraft. As it is devoted to research investigations on radar polarimetry applied to land and vegetation remote sensing, it needs to be calibrated in phase and amplitude with a very good accuracy. A calibration procedure using trihedral and dihedral corner reflectors is presented here and then compared to the calibration method using random distributed targets that has been developed at the Jet Propulsion Laboratory. A very good agreement between both methods enables us to apply our calibration algorithms to natural surfaces measurements at different incidence angles (20°, 40° and 50°).},
  isbn         = {0003-4347},
  keywords     = {Airborne radar,Calibration,Continuous wave radar,Dihedron,Frequency modulation,Polarimetry,Reflector,Remote sensing},
  publisher    = {Springer},
}

@Article{Le2014,
  author        = {Le, Thu Trang and Atto, Abdourrahmane M. and Trouve, Emmanuel and Nicolas, Jean Marie},
  title         = {{Adaptive multitemporal SAR image filtering based on the change detection matrix}},
  journaltitle  = {IEEE Geoscience and Remote Sensing Letters},
  date          = {2014},
  volume        = {11},
  pages         = {1826--1830},
  issn          = {1545598X},
  doi           = {10.1109/LGRS.2014.2311663},
  keywords      = {Change detection,change detection,coefficient of variation (CV),synthetic aperture radar (SAR) image time series,temporal adaptive filtering},
  mendeley-tags = {change detection,coefficient of variation (CV),synthetic aperture radar (SAR) image time series,temporal adaptive filtering},
}

@InProceedings{LEE,
  author    = {Hoonyol Lee and Seong-Jun Cho and Nak-Hoon Sung and Jung-Ho Kim},
  title     = {Development of a Ground-based Synthetic Aperture Radar System for Highly Repeatable Measurements},
  booktitle = {The 9th workshop on subsurface electromagnetic measurement},
  year      = {2007},
  pages     = {2--6},
  url       = {http://sar.kangwon.ac.kr/paper/sem{\_}gbsar.pdf},
  abstract  = {This is a traslated version from korean},
  file      = {:home/baffelli/Library/LEE et al. - Unknown - Development of a Ground-based Synthetic Aperture Radar System for Highly Repeatable Measurements.pdf:pdf},
  keywords  = {1990s,2,3,4,5,6,gb-sar,gb-sar have been,interferometry,landslides,of building stability,performed for the study,practical outdoor application of,synthetic aperture radar},
}

@InProceedings{Lee2010,
  author       = {Hoonyol Lee and Seong-Jun Cho and Kwang-Eun Kim},
  title        = {A ground-based Arc-scanning synthetic aperture radar ({ArcSAR}) system and focusing algorithms},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2010},
  date         = {2010},
  publisher    = {{IEEE}},
  month        = {jul},
  isbn         = {9781424495658},
  pages        = {3490--3493},
  doi          = {10.1109/IGARSS.2010.5652569},
  file         = {:home/baffelli/Library/Lee, Cho, Kim - 2010 - A ground-based Arc-scanning synthetic aperture radar (ArcSAR) system and focusing algorithms.pdf:pdf},
  issn         = {2153-6996},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {ArcSAR,Polar format algorithm,Scan mode,Spot mode,Synthetic aperture radar},
}

@Article{Lee2014,
  author        = {Hoonyol Lee and Jae-Hee Lee and Kwang-Eun Kim and Nak-Hoon Sung and Seong-Jun Cho},
  title         = {Development of a Truck-Mounted Arc-Scanning Synthetic Aperture Radar},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2014},
  date          = {2014-05},
  volume        = {52},
  month         = {may},
  pages         = {2773--2779},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2013.2265700},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6553134},
  file          = {:home/baffelli/Library/Lee et al. - 2014 - Development of a Truck-Mounted Arc-Scanning Synthetic Aperture Radar.pdf:pdf},
  keywords      = {Arc-scanning synthetic aperture radar (ArcSAR),ArcSAR formulation,ArcSAR scan mode image,ArcSAR system development,Doppler radar,SAR,SAR focusing algorithms,antenna view angle fixing,antennas,arc-scanning real aperture radar,azimuth resolution,conventional ground-based SAR system linear scanni,exemplary X-band ArcSAR spot mode image,extendable boom,geophysical equipment,ground-based arc-scanning synthetic aperture radar,high-resolution image,horizontal circular antenna motion,image area,image processing accuracy,image processing efficiency,imaging mode,radar imaging,range Doppler algorithm,reduced resolution,remote sensing by radar,scan mode,spot mode,synthetic aperture radar,time domain algorithm,truck-mounted arc-scanning synthetic aperture rada,wider image coverage},
  mendeley-tags = {Arc-scanning synthetic aperture radar (ArcSAR),ArcSAR formulation,ArcSAR scan mode image,ArcSAR system development,Doppler radar,SAR,SAR focusing algorithms,antenna view angle fixing,antennas,arc-scanning real aperture radar,azimuth resolution,conventional ground-based SAR system linear scanni,exemplary X-band ArcSAR spot mode image,extendable boom,geophysical equipment,ground-based arc-scanning synthetic aperture radar,high-resolution image,horizontal circular antenna motion,image area,image processing accuracy,image processing efficiency,imaging mode,radar imaging,range Doppler algorithm,reduced resolution,remote sensing by radar,scan mode,spot mode,synthetic aperture radar,time domain algorithm,truck-mounted arc-scanning synthetic aperture rada,wider image coverage},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Lee1994,
  author       = {Lee, J. S. and Jurkevich, L. and Dewaele, P. and Wambacq, P. and Oosterlinck, A.},
  title        = {{Speckle filtering of synthetic aperture radar images: A review}},
  journaltitle = {Remote Sensing Reviews},
  date         = {1994},
  volume       = {8},
  pages        = {313--340},
  issn         = {0275-7257},
  doi          = {10.1080/02757259409532206},
  isbn         = {0275-7257},
}

@Article{Lee2000,
  author        = {Lee, Jong S. and Schuler, Dale L. and Ainsworth, Thomas L.},
  title         = {{Polarimetric SAR data compensation for terrain azimuth slope variation}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2000-09},
  volume        = {38},
  pages         = {2153--2163},
  issn          = {01962892},
  doi           = {10.1109/36.868874},
  abstract      = {This paper addresses the problem of polarimetric SAR (POLSAR) data$\backslash$ncorrection for changes in radar cross sections, which are caused by$\backslash$nazimuth slopes. Most radiometric slope corrections remove slope effects$\backslash$nto account for the effective scattering pixel area. However, few studies$\backslash$naddress the slope effect on the radar cross section as a function of$\backslash$npolarization states. The authors propose two approaches to compensate$\backslash$nfor this azimuth slope effect for POLSAR data. In the first approach,$\backslash$nthe digital elevation model (DEM), obtained from interferometric SAR or$\backslash$nfrom other means, is used to estimate orientation angles, and in the$\backslash$nsecond approach, orientation angles are derived directly from the POLSAR$\backslash$ndata. They have developed three new methods to implement this second$\backslash$napproach. One is based on the right-right and left-left circular$\backslash$npolarizations, and the other two are based on Cloude's and Huynelt's$\backslash$ndecompositions. The results are compared with the original polarization$\backslash$nsignature method using the DEM-generated orientation angles as the$\backslash$nreference. POLSAR data is then compensated using the derived orientation$\backslash$nangles. Significant changes were observed in many elements of the$\backslash$ncoherency matrix. The compensated POLSAR data should improve the$\backslash$naccuracy of geophysical parameter estimation techniques. NASA/JPL AIRSAR$\backslash$ndata for an area in central California is used for illustration},
  isbn          = {0-7803-5207-6},
  keywords      = {Azimuth,Digital elevation models,Matrix decomposition,NASA,POLSAR,Parameter estimation,Radar scattering,Radiometry,Terrain mapping,azimuth slope variation,data compensation,effective scattering pixel area,geophysical measurement technique,geophysical techniques,land surface,polarimetric SAR,polarization,radar cross section,radar imaging,radar polarimetry,radar remote sensing,radiometric slope correction,remote sensing by radar,synthetic aperture radar},
  mendeley-tags = {Azimuth,Digital elevation models,Matrix decomposition,NASA,POLSAR,Parameter estimation,Radar scattering,Radiometry,Terrain mapping,azimuth slope variation,data compensation,effective scattering pixel area,geophysical measurement technique,geophysical techniques,land surface,polarimetric SAR,polarization,radar cross section,radar imaging,radar polarimetry,radar remote sensing,radiometric slope correction,remote sensing by radar,synthetic aperture radar},
}

@Article{Lee1981,
  author       = {Lee, Jong-Sen},
  title        = {{Refined filtering of image noise using local statistics}},
  journaltitle = {Computer Graphics and Image Processing},
  date         = {1981},
  volume       = {15},
  pages        = {380--389},
  issn         = {0146664X},
  doi          = {10.1016/S0146-664X(81)80018-4},
  abstract     = {An effective algorithm for digital image noise filtering is presented in this paper. Mostnoise filtering techniques such as Kalman filter and transform domain methods require extensive image modeling and produce filtered images with considerable contrast loss. The algorithm proposed in this paper is an extension of Lee's local statistics method modified to utilize local gradient information. It does not require image modeling, and it will not smear edges and subtle details. For both the additive and multiplicative noise cases, the local mean and variance are computed from a reduced set of pixels depending on the orientation of the edge. Consequently, noise along the edge is removed, and the sharpness of the edge is enhanced. For practical applications when the noise variance is spatially varying and unknown, an adaptive filtering algorithm is developed. Experiments show its good potential for processing real-life images. Examples on images containing 256×256 pixels are given to substantiate the theoretical development.},
  isbn         = {0146-664X},
}

@Article{Lee1980,
  author       = {Lee, Jong-Sen},
  title        = {{Digital Image Enhancement and Noise Filtering by Use of Local Statistics}},
  journaltitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  date         = {1980-03},
  volume       = {PAMI-2},
  pages        = {165--168},
  issn         = {0162-8828},
  doi          = {10.1109/TPAMI.1980.4766994},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4766994},
  abstract     = {Computational techniques involving contrast enhancement and noise filtering on two-dimensional image arrays are developed based on their local mean and variance. These algorithms are nonrecursive and do not require the use of any kind of transform. They share the same characteristics in that each pixel is processed independently. Consequently, this approach has an obvious advantage when used in real-time digital image processing applications and where a parallel processor can be used. For both the additive and multiplicative cases, the a priori mean and variance of each pixel is derived from its local mean and variance. Then, the minimum mean-square error estimator in its simplest form is applied to obtain the noise filtering algorithms. For multiplicative noise a statistical optimal linear approximation is made. Experimental results show that such an assumption yields a very effective filtering algorithm. Examples on images containing 256 × 256 pixels are given. Results show that in most cases the techniques developed in this paper are readily adaptable to real-time image processing.},
  isbn         = {0162-8828 VO - PAMI-2},
  pmid         = {21868887},
}

@Article{Lee1999,
  author        = {Jong-Sen Lee and M.R. Grunes and T.L. Ainsworth and Li-Jen Du and D.L. Schuler and S.R. Cloude},
  title         = {Unsupervised classification using polarimetric decomposition and the complex {W}ishart classifier},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {1999},
  date          = {1999-09},
  volume        = {37},
  pages         = {2249--2258},
  issn          = {0196-2892},
  doi           = {10.1109/36.789621},
  keywords      = {Covariance matrix,Electromagnetic scattering,Neural networks,Radar scattering,SAR,Terrain mapping,complex Wishart classifier,complex Wishart distribution,entropy-alpha plane,geophysical measurement technique,geophysical signal processing,geophysical techniques,image classification,image processing,initial classification map,iteration,land surface,man-made object,maximum likelihood classifier,polarimetric decomposition,polarimetric synthetic aperture radar,polarimetric target decomposition,polarization,radar applications,radar imaging,radar polarimetry,radar remote sensing,remote sensing by radar,synthetic aperture radar,terrain type,training,unsupervised classification},
  mendeley-tags = {Covariance matrix,Electromagnetic scattering,Neural networks,Radar scattering,SAR,Terrain mapping,complex Wishart classifier,complex Wishart distribution,entropy-alpha plane,geophysical measurement technique,geophysical signal processing,geophysical techniques,image classification,image processing,initial classification map,iteration,land surface,man-made object,maximum likelihood classifier,polarimetric decomposition,polarimetric synthetic aperture radar,polarimetric target decomposition,polarization,radar applications,radar imaging,radar polarimetry,radar remote sensing,remote sensing by radar,synthetic aperture radar,terrain type,training,unsupervised classification},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Lee1992,
  author        = {Lee, Jong-Sen and Grunes, Mitchell R},
  title         = {{Classification of Multi-Look Polarimetric SAR Data Base on Complex Wishart Distribution}},
  booktitle     = {Telesystems Conference, 1992. NTC-92., National},
  date          = {1992-05},
  isbn          = {0143-1161},
  pages         = {721--724},
  doi           = {10.1109/NTC.1992.267879},
  abstract      = {Multi-look polarimetric SAR (synthetic aperture radar) data can be represented either in Mueller matrix form or in complex covariance matrix form. The latter has a complex Wishart distribution. A maximum likelihood classifier to segment polarimetric SAR data according to terrain types has been developed based on the Wishart distribution. This algorithm can also be applied to multi-frequency multi-look polarimetric SAR data, as well as to SAR data containing only intensity information. A procedure is then developed for unsupervised classification. The classification error is assessed by using Monte Carlo simulation of multi-look polarimetric SAR data, owing to the lack of ground truth for each pixel. Comparisons of classification errors using the training sets and single-look data are also made. Applications of this algorithm are demonstrated with NASA/JPL P-, L- and C-band polarimetric SAR data.},
  issn          = {0143-1161 ER},
  keywords      = {C-band,Cities and towns,Covariance matrix,Gaussian distribution,JPL,Jet Propulsion Laboratory,L-band,Layout,Monte Carlo simulation,NASA,Oceans,P-band,Radar scattering,Speckle,Stoke matrix,Vegetation mapping,a land scene are,algorithm,city block,classification errors,complex Wishart distribution,complex covariance,complex covariance matrix,each pixel,electromagnetic wave polarisation,feature classification,forest,function,ground covers,image processing,is then classified using,matrix algebra,matrix is converted to,multifrequency polarimetric data,multilook polarimetric SAR,ocean,optimal feature classification,polarimetric SAR data,polarimetric sar,radar imagery,remote sensing by radar,sea ice,sea ice scene and,synthetic aperture radar,the covariance matrix for,the derived optimal discriminating,the pixel,the stokes,utilized for illustration,vegetation},
  mendeley-tags = {C-band,Cities and towns,Covariance matrix,Gaussian distribution,JPL,Jet Propulsion Laboratory,L-band,Layout,Monte Carlo simulation,NASA,Oceans,P-band,Radar scattering,Speckle,Stoke matrix,Vegetation mapping,algorithm,city block,classification errors,complex Wishart distribution,complex covariance,complex covariance matrix,electromagnetic wave polarisation,forest,ground covers,image processing,matrix algebra,multifrequency polarimetric data,multilook polarimetric SAR,ocean,optimal feature classification,polarimetric SAR data,radar imagery,remote sensing by radar,sea ice,synthetic aperture radar,vegetation},
}

@Book{Lee2009,
  author    = {Lee, Jon-Sen and Pottier, Eric},
  title     = {Polarimetric Radar Imaging: From Basics To Applications},
  date      = {2009},
  publisher = {CRC press},
  isbn      = {9781420054972},
  doi       = {10.1201/9781420054989},
}

@Article{Leinss2014,
  author       = {Silvan Leinss and Giuseppe Parrella and Irena Hajnsek},
  title        = {Snow height determination by polarimetric phase differences in {X}-Band {SAR} data},
  journal      = {{IEEE} Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  journaltitle = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year         = {2014},
  date         = {2014-09},
  volume       = {7},
  month        = {sep},
  pages        = {3794--3810},
  issn         = {1939-1404},
  doi          = {10.1109/JSTARS.2014.2323199},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6841006},
  file         = {:home/baffelli/Library/Leinss, Parrella, Hajnsek - 2014 - Snow height determination by polarimetric phase differences in X-Band SAR data.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Leva2003,
  author       = {D. Leva and G. Nico and D. Tarchi and J. Fortuny-Guasch and A.J. Sieber},
  title        = {Temporal analysis of a landslide by means of a ground-based {SAR} interferometer},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2003},
  date         = {2003},
  volume       = {41},
  month        = {apr},
  pages        = {745--752},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2003.808902},
  abstract     = {A ground-based synthetic aperture radar (GB-SAR) interferometer is used to retrieve the velocity field of a landslide. High-resolution images are obtained by means of a time domain SAR processor. An in-depth analysis of the sequence of SAR interferograms enables the recognition of a slowly deforming upper scarp in the scene, and a debris flow that feeds the accumulation zone of the landslide, where a fast change in terrain morphology is observed. The estimated deformation map is in agreement with the available measurements obtained by means of Global Positioning System receivers. Results show that GB-SAR interferometry is a cost-effective solution for the monitoring of landslides. The proposed method is shown to be a valid complement to space- and airborne SAR and to the traditional geodetic instruments.},
  file         = {:home/baffelli/Library/Leva et al. - 2003 - Temporal analysis of a landslide by means of a ground-based SAR interferometer.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Differential synthetic aperture radar interferomet,Ground-based synthetic aperture radar (GB-SAR) int,Landslide monitoring,Phase image analysis,Synthetic aperture radar (SAR)},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Li2012,
  author       = {Li, Jia and Xin, Jia},
  title        = {Research on Flat Earth Removal Techniques of {INSAR}},
  journal      = {Advanced Materials Research},
  journaltitle = {Advanced Materials Research},
  year         = {2012},
  date         = {2012},
  volume       = {433-440},
  month        = {jan},
  pages        = {7487--7492},
  issn         = {1662-8985},
  doi          = {10.4028/www.scientific.net/AMR.433-440.7487},
  url          = {http://www.scientific.net/AMR.433-440.7487},
  file         = {:home/baffelli/Library/Li, Xin - 2012 - Research on Flat Earth Removal Techniques of INSAR.pdf:pdf},
  publisher    = {Trans Tech Publications},
}

@Article{Li2015,
  author       = {Li, Yake and O'Young, Siu},
  title        = {{Focusing Bistatic FMCW SAR Signal by Range Migration Algorithm Based on Fresnel Approximation}},
  journaltitle = {Sensors},
  date         = {2015-12},
  volume       = {15},
  pages        = {32123--32137},
  issn         = {1424-8220},
  doi          = {10.3390/s151229910},
  url          = {http://www.mdpi.com/1424-8220/15/12/29910},
  file         = {:home/baffelli/Library/Li, O'Young - 2015 - Focusing Bistatic FMCW SAR Signal by Range Migration Algorithm Based on Fresnel Approximation.pdf:pdf},
  isbn         = {1709864834},
  keywords     = {bistatic fmcw sar,range migration algorithm,sar signal spectrum},
}

@InProceedings{Li2008,
  author    = {Li, Zhaolong and Wu, Ke},
  title     = {{On the Leakage of FMCW Radar Front-End Receiver}},
  booktitle = {2008 Global Symposium on Millimeter Waves},
  date      = {2008-04},
  publisher = {IEEE},
  isbn      = {978-1-4244-1885-5},
  pages     = {127--130},
  doi       = {10.1109/GSMM.2008.4534576},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4534576},
  abstract  = {As an accurate range measurement sensor, frequency-modulation continuous-wave$\backslash$n(FMCW) radar receives wide research attention throughout years. One$\backslash$nwell-known challenges of the design of a high-performance FMCW radar$\backslash$nis the well-recognized leakage problems associated with a homodyne$\backslash$nreceiver. In this study, the actual effect of free space leakage$\backslash$nfor a FMCW radar system-on-substrate is measured. The experiment$\backslash$nprinciples and results are discussed in detail. Other sources of$\backslash$nleakage within a FMCW radar receiver are also explained. The appropriate$\backslash$nmethods to reduce or remove these negative effects on the receiver$\backslash$nperformance are discussed as well.},
  file      = {:home/baffelli/Library/Li, Wu - 2008 - On the Leakage of FMCW Radar Front-End Receiver.pdf:pdf},
  keywords  = {FMCW radar front-end receiver,frequency-modulation},
}

@Article{Liebe1981,
  author       = {Liebe, Hans J.},
  title        = {{Modeling attenuation and phase of radio waves in air at frequencies below 1000 GHz}},
  journaltitle = {Radio Science},
  date         = {1981},
  volume       = {16},
  pages        = {1183--1199},
  issn         = {1944799X},
  doi          = {10.1029/RS016i006p01183},
  abstract     = {Moist air is characterized for the frequency range 1–1000 GHz as a nonturbulent propagation medium described by meteorological parameters. An adequate spectroscopic data base for air consists of three terms: (1) resonance information for 29 H2O lines up to 1097 GHz and 44 O2 lines up to 834 GHz in the form of intensity coefficients and center frequency for each line; (2) an empirical water vapor continuum spectrum; and (3) a liquid water attenuation term for haze and cloud conditions. This data base is the heart of two computer programs which calculate and plot attenuation rates (in decibels per kilometer), refractivity (in parts per million), and refractive dispersion (in parts per million). The first covers the troposphere and requires pressure, temperature, and relative humidity as input data. The second addresses isolated line behavior in the mesosphere wherein the geomagnetic field strength H is an additional input parameter due to the Zeeman effect of the O2 molecules. Each oxygen line splits proportionally with H into numerous sublines, which are juxtaposed to form Zeeman patterns spread over a megahertz scale. Patterns of three main polarization cases are considered. Various typical examples for a model atmosphere demonstrate the utility of the approach, provide new information, and underline the serious role that water vapor plays above 120 GHz.},
  file         = {:home/baffelli/Library/Liebe - 1981 - Modeling attenuation and phase of radio waves in air at frequencies below 1000 GHz.pdf:pdf},
  keywords     = {http://dx.doi.org/10.1029/RS016i006p01183, doi:10.},
}

@Article{Liu2010,
  author       = {Liu, Tao and Huang, GaoMing M. and Wang, XueSong S. and Xiao, ShunPing P.},
  title        = {Statistical assessment of {H/A} target decomposition theorems in radar polarimetry},
  journaltitle = {Science in China, Series F: Information Sciences},
  year         = {2010},
  date         = {2010},
  volume       = {53},
  pages        = {355--366},
  issn         = {10092757},
  doi          = {10.1007/s11432-010-0023-y},
  abstract     = { The performance of quantitative remote sensing based on multidimensional synthetic aperture radars (SARs), and polarimetric SAR systems in particular, depends strongly on a correct statistical characterization of the data, i.e., on a complete knowledge of the effects of the speckle noise. In this framework, the eigendecompostion of the covariance or coherency matrices and the associated{\textless}tex{\textgreater}{\$}H/underlinealpha/A{\$}{\textless}/tex{\textgreater}decomposition have demonstrated the potential for quantitative estimation of physical parameters. In this paper, we present a detailed study of the statistics associated with this decomposition. This analysis requires the introduction of mathematical tools that are not well known in the remote sensing community. For this reason, we include a review section to present them. Using this work, we then present an expression for the probability density function of the sample eigenvalues of the covariance or coherency matrix. The availability of this expression allows a complete study of the separated sample eigenvalues, as well as, the entropy H and the anisotropy A. As demonstrated, all these parameters must be considered as asymptotically nonbiased with respect to the number of looks. In order to reduce the biases for a small number of averaged samples, a novel estimator for the eigenvalues is proposed. The results of this work are analyzed by means of simulated and real airborne SAR data. This analysis permits us to determine in detail the effects of the number of averaged samples in the estimation of physical information in radar polarimetry.},
  file         = {:home/baffelli/Library/Liu et al. - 2010 - Statistical assessment of HA target decomposition theorems in radar polarimetry.pdf:pdf},
  isbn         = {9781424447756},
  keywords     = {Characteristic parameters,H/A,MLE,Statistical analysis,Target decomposition theorems},
}

@Article{Lucchitta1986,
  author       = {Lucchitta, B. K. and Ferguson, H M},
  title        = {{Antarctica: measuring glacier velocity from satellite images.}},
  journaltitle = {Science},
  date         = {1986},
  volume       = {234},
  pages        = {1105--1108},
  issn         = {0036-8075},
  doi          = {10.1126/science.234.4780.1105},
  abstract     = {Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.},
  pmid         = {17778951},
}

@Article{Luo2014,
  author       = {Yunhua Luo and Hongjun Song and Robert Wang and Yunkai Deng and Fengjun Zhao and Zheng Xu},
  title        = {Arc {FMCW} {SAR} and Applications in Ground Monitoring},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {52},
  month        = {sep},
  pages        = {5989--5998},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2014.2325905},
  file         = {:home/baffelli/Library/Luo et al. - 2014 - Arc FMCW SAR and Applications in Ground Monitoring.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Luzi2007,
  author       = {G. Luzi and M. Pieraccini and D. Mecatti and L. Noferini and G. Macaluso and A. Tamburini and C. Atzeni},
  title        = {Monitoring of an Alpine Glacier by Means of Ground-Based {SAR} Interferometry},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  year         = {2007},
  date         = {2007-07},
  volume       = {4},
  month        = {jul},
  pages        = {495--499},
  issn         = {1545-598X},
  doi          = {10.1109/lgrs.2007.898282},
  url          = {http://ieeexplore.ieee.org/document/4271456/},
  abstract     = {Spaceborne differential synthetic aperture radar (SAR) interferometry has been proven to be a powerful tool in monitoring environmental phenomena and, in particular, in observing glaciers and retrieving information about their surface topography and dynamics. In the last decade, the use of this technique has been successfully extended from space to ground-based observations as a tool for monitoring, on a smaller scale, single landslides, unstable slopes, and more recently, areas covered by snow but not yet glaciers. In this letter, the results of an experimental activity carried out to evaluate the potential of ground-based microwave interferometry to estimate the velocity of an unstable area belonging to a glacier is reported. This experiment demonstrated the possibility of remotely monitoring surface displacements of the monitored glacier up to a distance of about 3 km even if, due to the lack of ground truths on the observed area, the data interpretation must be carefully worked out.},
  file         = {:home/baffelli/Library/Luzi et al. - 2007 - Monitoring of an Alpine Glacier by Means of Ground-Based SAR Interferometry.pdf:pdf},
  isbn         = {1545-598X},
  keywords     = {Glaciers,Ground-based synthetic aperture radar (GB SAR) int,Monitoring},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Maslikowski2011a,
  author       = {Ma{\'{s}}likowski, {\L}ukasz and Kulpa, Krzysztof},
  title        = {{Bistatic Noise SAR Experiment with a Non-Cooperative Illuminator}},
  journaltitle = {International Journal of Electronics and Telecommunications},
  date         = {2011},
  volume       = {57},
  pages        = {85--89},
  issn         = {0867-6747},
  doi          = {10.2478/v10177-011-0012-0},
  url          = {http://www.degruyter.com/view/j/eletel.2011.57.issue-1/v10177-011-0012-0/v10177-011-0012-0.xml},
  file         = {:home/baffelli/Library/Ma{'{s}}likowski, Kulpa - 2011 - Bistatic Noise SAR Experiment with a Non-Cooperative Illuminator.pdf:pdf},
  keywords     = {cots,noise radar,passive radar,sar},
}

@Article{Maslikowski2011,
  author       = {Ma{\'{s}}likowski, \L. and Misiurewicz, J.},
  title        = {{Nonuniform spatial sampling in a ground-based noise SAR}},
  journaltitle = {International Journal of Electronics and Telecommunications},
  date         = {2011},
  volume       = {57},
  pages        = {71--75},
  issn         = {20818491},
  doi          = {10.2478/v10177-011-0010-2},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-80053644623{\&}partnerID=40{\&}md5=a5a50aa2482a3a52b51e409b324855ba},
  abstract     = {The paper presents an idea of nonuniform spatial sampling applied to a noise synthetic aperture radar. In certain cases it is desirable to limit the number of spatial (along-track) domain samples acquired in a SAR radar because of external constraints on sampling frequency or on the overall number of samples - e.g. in order to economy on time or power consumed. Lowering number of samples taken may, however, lead to spatial aliasing and incorrect reconstruction of the image. Nonuniform sampling allows to reduce the aliasing effect and reconstruct the image better. This technique can be applied with standard reconstruction methods, but it works best together with Compressive Sensing reconstruction algorithms. The idea will be verified with an experimental noise SAR built at ISE PW.},
  file         = {:home/baffelli/Library/Ma{'{s}}likowski, Misiurewicz - 2011 - Nonuniform spatial sampling in a ground-based noise SAR.pdf:pdf},
  keywords     = {Aliasing effects; Compressive sampling; External c,Synthetic aperture radar,Synthetic apertures},
}

@Article{Magnard2012,
  author       = {Magnard, C. and Brehm, T. and Essen, H. and Meier, E. and Electromagnet, Acad},
  title        = {{High Resolution MEMPHIS SAR Data Processing and Applications}},
  journaltitle = {Proceedings Of Progress In Electromagnetics Research Symposium},
  date         = {2012},
  pages        = {328--332},
  abstract     = {This paper focuses on MEMPHIS (Multi-frequency Experimental Monopulse High-resolution Interferometric SAR) data processing, possible applications using its various SAR modes and the results obtained. The processing chain used to focus MEMPHIS data is presented. To demonstrate the focusing quality, the signatures of corner reflectors were analyzed, revealing not only a high resolution, but also a very precise geometric positioning accuracy on the order of the resolution, in spite of MEMPHIS' experimental and portable design. Finally, applications and results using the various antennas are presented, such as the generation of digital surface models with the multi-baseline interferometric antenna along with a quality evaluation, as well as channel combinations of the polarimetric data.},
  file         = {:home/baffelli/Library/Magnard et al. - 2012 - High Resolution MEMPHIS SAR Data Processing and Applications.pdf:pdf},
  isbn         = {1559-9450$\backslash$n978-1-934142-20-2},
}

@Article{Many2002,
  author = {Many, Introduction and Rad, A. M. S. and Wo, Calibration and Whereas, Reflector Configuration},
  title  = {{Radar Calibration Using a Trihedral Corner Reflector Brooks E . Martner , Kurt A . Clark , and Bruce W . Bartram}},
  date   = {2002},
  pages  = {3--5},
  file   = {:home/baffelli/Library/Many et al. - 2002 - Radar Calibration Using a Trihedral Corner Reflector Brooks E . Martner , Kurt A . Clark , and Bruce W . Bartram.pdf:pdf},
}

@Article{Marino2013,
  author        = {Marino, Armando},
  title         = {{A Notch Filter for Ship Detection With Polarimetric SAR Data}},
  journaltitle  = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  date          = {2013-06},
  volume        = {6},
  pages         = {1219--1232},
  issn          = {1939-1404},
  doi           = {10.1109/JSTARS.2013.2247741},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6475202},
  keywords      = {Clutter,Detectors,Marine vehicles,Monte Carlo methods,Monte Carlo simulations,Probability,Scattering,TerraSAR-X,TerraSAR-X quadpolarimetric data,Vectors,backscatter,detection probability extraction,false alarm probability extraction,maritime area monitoring,maritime area security,negative filter,notch filter,notch filters,object detection,oceanographic techniques,perturbation analysis,polarimetric SAR data,polarimetric acquisitions,polarimetric target space,radar polarimetry,sea,ship detection,ships,synthetic aperture radar},
  mendeley-tags = {Clutter,Detectors,Marine vehicles,Monte Carlo methods,Monte Carlo simulations,Probability,Scattering,TerraSAR-X,TerraSAR-X quadpolarimetric data,Vectors,backscatter,detection probability extraction,false alarm probability extraction,maritime area monitoring,maritime area security,negative filter,notch filter,notch filters,object detection,oceanographic techniques,perturbation analysis,polarimetric SAR data,polarimetric acquisitions,polarimetric target space,radar polarimetry,sea,ship detection,ships,synthetic aperture radar},
}

@InCollection{Marino2012,
  author    = {Marino, Armando},
  title     = {{Synthetic Aperture Radar BT - A New Target Detector Based on Geometrical Perturbation Filters for Polarimetric Synthetic Aperture Radar (POL-SAR)}},
  booktitle = {A New Target Detector Based on Geometrical Perturbation Filters for Polarimetric Synthetic Aperture Radar (POL-SAR)},
  date      = {2012},
  language  = {EN},
  isbn      = {978-3-642-27162-5},
  pages     = {9--27},
  doi       = {10.1007/978-3-642-27163-2},
  url       = {http://link.springer.com/10.1007/978-3-642-27163-2{\_}2 papers2://publication/doi/10.1007/978-3-642-27163-2{\_}2},
}

@Article{Marino2013a,
  author        = {Marino, Armando and Cloude, Shane R. and Lopez-Sanchez, Juan M.},
  title         = {{A new polarimetric change detector in radar imagery}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2013},
  volume        = {51},
  pages         = {2986--3000},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2012.2211883},
  keywords      = {Change detection,Covariance matrix,Detectors,Polarimetry,Scattering,Symmetric matrices,Synthetic aperture radar (SAR),Thyristors,Vectors,change detection,polarimetry,radar polarimetry,synthetic aperture radar (SAR)},
  mendeley-tags = {Covariance matrix,Detectors,Scattering,Symmetric matrices,Thyristors,Vectors,change detection,polarimetry,radar polarimetry,synthetic aperture radar (SAR)},
}

@Article{Marino2012a,
  author        = {Marino, Armando and Cloude, Shane R. and Woodhouse, Iain H.},
  title         = {{Detecting Depolarized Targets Using a New Geometrical Perturbation Filter}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2012},
  volume        = {50},
  pages         = {3787--3799},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2012.2185703},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6165655},
  abstract      = {Target detectors using polarimetry are often focused on single targets, since these can be characterized in a simpler and deterministic way. The algorithm proposed in this paper is aimed at the more difficult problem of partial-target detection (i.e., targets with arbitrary degree of polarization). The authors have already proposed a single-target detector employing filters based on a geometrical perturbation. In order to enhance the algorithm to the detection of partial targets, a new vector formalism is introduced. The latter is similar to the one exploited for single targets but suitable for complete characterization of partial targets. A new feature vector is generated starting from the covariance matrix and exploited for the perturbation method. Validation against L-band fully polarimetric airborne E-SAR and ALOS PALSAR data and X-band dual-polarimetric TerraSAR-X data is provided with significant agreement with the expected results. Additionally, a comparison with the supervised Wishart classifier is presented revealing improvements.},
  isbn          = {0196-2892},
  keywords      = {ALOS PALSAR data,Classification,Clutter,Coherence,Covariance matrix,Detectors,L-band fully polarimetric airborne E-SAR data,Vectors,X-band dual-polarimetric TerraSAR-X data,covariance matrices,depolarized targets,feature vector,geometrical perturbation filter,geophysical techniques,object detection,partial-target detection,perturbation method,perturbation techniques,polarimetry,radar polarimetry,single-target detector,supervised Wishart classifier,synthetic aperture radar,synthetic aperture radar (SAR),target detection,vector formalism},
  mendeley-tags = {ALOS PALSAR data,Classification,Clutter,Coherence,Covariance matrix,Detectors,L-band fully polarimetric airborne E-SAR data,Vectors,X-band dual-polarimetric TerraSAR-X data,covariance matrices,depolarized targets,feature vector,geometrical perturbation filter,geophysical techniques,object detection,partial-target detection,perturbation method,perturbation techniques,polarimetry,radar polarimetry,single-target detector,supervised Wishart classifier,synthetic aperture radar,synthetic aperture radar (SAR),target detection,vector formalism},
}

@Article{Marino2014,
  author        = {Marino, Armando and Hajnsek, Irena},
  title         = {{A Change Detector Based on an Optimization With Polarimetric SAR Imagery}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2014-08},
  volume        = {52},
  pages         = {4781--4798},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2013.2284510},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6651778},
  keywords      = {Clutter,Coherence,Detectors,Eigenvalues and eigenfunctions,Experimental-SAR German Aerospace Center system,L-band,Lagrange optimization,Optimization,aerospace instrumentation,change detection,change detector,covariance matrices,equiscattering mechanisms (ESMs),equiscattering-mechanism hypothesis,ground surveys,optimisation,polarimetric SAR imagery,polarimetry,probability density function,radar imaging,remote sensing by radar,synthetic aperture radar},
  mendeley-tags = {Clutter,Coherence,Detectors,Eigenvalues and eigenfunctions,Experimental-SAR German Aerospace Center system,L-band,Lagrange optimization,Optimization,aerospace instrumentation,change detection,change detector,covariance matrices,equiscattering mechanisms (ESMs),equiscattering-mechanism hypothesis,ground surveys,optimisation,polarimetric SAR imagery,polarimetry,probability density function,radar imaging,remote sensing by radar,synthetic aperture radar},
}

@Article{Massonnet1995,
  author       = {Didier Massonnet and Pierre Briole and Alain Arnaud},
  title        = {Deflation of Mount {Etna} monitored by spaceborne radar interferometry},
  journal      = {Nature},
  journaltitle = {Nature},
  year         = {1995},
  date         = {1995-06},
  volume       = {375},
  month        = {jun},
  pages        = {567--570},
  issn         = {0028-0836},
  doi          = {10.1038/375567a0},
  abstract     = {GROUND-BASED measurements of volcano deformation can be used to assess eruptive hazard, but require the costly (and often hazardous) installation and maintenance of an instrument network, Here we show that spaceborne radar interferometry, which has already shown its utility in mapping earthquake-related deformation(1), can be used to monitor long-term volcano deformation. Two families of synthetic aperture radar images, acquired from ascending and descending orbits by the satellite ERS-1, and looking at Mount Etna from opposite sides, cover the time period from 17 May 1992 to 24 October 1993, and include the second half of Etna's most recent eruption, Despite artefacts of the interferometric technique, we can observe a volcano-wide deflation, which is an expected consequence of the eruption, but which had not previously been appreciated, We quantify it using a simple model based on the change of pressure in a sphere located in an elastic half-space; the modelled deformation increases linearly with time until the end of the eruption. Our results show that it will be possible to use this technique to detect the inflation of volcanic edifices that usually precedes eruptions.},
  isbn         = {0028-0836},
  publisher    = {Springer Nature},
}

@Article{Massonnet1993,
  author        = {D. Massonnet and T. Rabaute},
  title         = {Radar interferometry: limits and potential},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {1993},
  date          = {1993-03},
  volume        = {31},
  month         = {mar},
  pages         = {455--464},
  issn          = {01962892},
  doi           = {10.1109/36.214922},
  abstract      = {The contribution of radar interferometry to the field of digital terrain modeling is important because this technique offers specific features which optical instruments cannot attain. However, the complexity of the height restitution and the accuracy of the result strongly depend on the orbital geometry at the time of the data takes. The present study aims at assessing the potential of a given image pair with regard to interferometry and at automatically reducing the phase ambiguity intrinsic to such processing. Particular applications of differential interferometry are also discussed in order to estimate their requirements and prepare future experiments},
  keywords      = {-synthetic aperture radar,Geometrical optics,Instruments,Laser radar,Optical interferometry,Optical sensors,Radar antennas,Spaceborne radar,accuracy,differential inlerferometry,differential interferometry,digital terrain model,digital terrain modeling,dtm,electromagnetic wave interferometry,geophysical techniques,height restitution,image pair,image processing,interferometry,orbital geometry,phase,phase ambiguity,radar imaging,radar interferometry,remote sensing by radar,sar,synthetic aperture radar,topography,topography (Earth)},
  mendeley-tags = {Geometrical optics,Instruments,Laser radar,Optical interferometry,Optical sensors,Radar antennas,Spaceborne radar,accuracy,differential interferometry,digital terrain modeling,electromagnetic wave interferometry,geophysical techniques,height restitution,image pair,image processing,orbital geometry,phase ambiguity,radar imaging,radar interferometry,remote sensing by radar,synthetic aperture radar,topography,topography (Earth)},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Massonnet1993a,
  author       = {Didier Massonnet and Marc Rossi and C{\'{e}}sar Carmona and Fr{\'{e}}d{\'{e}}ric Adragna and Gilles Peltzer and Kurt Feigl and Thierry Rabaute},
  title        = {The displacement field of the {Landers} earthquake mapped by radar interferometry},
  journal      = {Nature},
  journaltitle = {Nature},
  year         = {1993},
  date         = {1993-07},
  volume       = {364},
  month        = {jul},
  pages        = {138--142},
  issn         = {0028-0836},
  doi          = {10.1038/364138a0},
  abstract     = {The movements produced by the 1992 earthquake in Landers, California are mapped using SAR interferometry. An interferogram is constructed by combining topographic information with SAR images obtained by the ERS-1 satellite before and after the earthquake. It is shown that the observed changes in the range from the ground surface to the satellite agree well with the slip measured in the field, with the displacements measured by surveying, and with the results of Okada's (1985) elastic dislocation model. This interferogram provides a denser spatial sampling than surveying methods and a better precision than earlier space imaging techniques.},
  isbn         = {0028-0836},
  pmid         = {2989708},
  publisher    = {Springer Nature},
}

@Article{Massonnet1996,
  author       = {D. Massonnet and H. Vadon and M. Rossi},
  title        = {Reduction of the need for phase unwrapping in radar interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1996},
  date         = {1996-03},
  volume       = {34},
  month        = {mar},
  pages        = {489--497},
  issn         = {01962892},
  doi          = {10.1109/36.485126},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=485126},
  file         = {:home/baffelli/Library/Massonnet, Vadon, Rossi - 1996 - Reduction of the need for phase unwrapping in radar interferometry.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Caduff_2017,
  author    = {Rafael Caduff and Tazio Strozzi},
  title     = {Terrestrial Radar Interferometry Monitoring During a Landslide Emergency 2016, Ghirone, Switzerland},
  year      = {2017},
  series    = {EGU General Assembly Conference Abstracts},
  volume    = {15},
  eid       = {EGU2013-1523},
  month     = apr,
  pages     = {301--309},
  doi       = {10.1007/978-3-319-53487-9_34},
  adsnote   = {Provided by the SAO/NASA Astrophysics Data System},
  adsurl    = {http://adsabs.harvard.edu/abs/2013EGUGA..15.1523M},
  booktitle = {Advancing Culture of Living with Landslides},
  publisher = {Springer International Publishing},
}

@Misc{Matheron1973,
  author    = {Matheron, G.},
  title     = {{The Intrinsic Random Functions and Their Applications}},
  date      = {1973},
  doi       = {10.2307/1425829},
  url       = {http://www.jstor.org/stable/1425829 http://cg.ensmp.fr/bibliotheque/public/MATHERON{\_}Publication{\_}00180.pdf{\%}5Cnhttp://www.jstor.org/stable/1425829?origin=crossref},
  abstract  = {The intrinsic random functions (IRF) are a particular case of the Guelfand generalized processes with stationary increments. They constitute a much wider class than the stationary RF, and are used in practical applications for representing non-stationary phenomena. The most important topics are: existence of a generalized covariance (GC) for which statistical inference is possible from a unique realization; theory of the best linear intrinsic estimator (BLIE) used for contouring and estimating problems; the turning bands method for simulating IRF; and the models with polynomial GC, for which statistical inference may be performed by automatic procedures.},
  booktitle = {Advances in Applied Probability},
  file      = {:home/baffelli/Library/Matheron - 1973 - The Intrinsic Random Functions and Their Applications.pdf:pdf},
  isbn      = {00018678},
  issn      = {00018678},
  pages     = {439},
  volume    = {5},
}

@Article{Matheron1973a,
  author    = {G. Matheron},
  title     = {The intrinsic random functions and their applications},
  journal   = {Advances in Applied Probability},
  year      = {1973},
  date      = {1973},
  volume    = {5},
  month     = {dec},
  pages     = {439--468},
  issn      = {00018678},
  doi       = {10.1017/s0001867800039379},
  url       = {http://www.jstor.org/stable/1425829 http://cg.ensmp.fr/bibliotheque/public/MATHERON{\_}Publication{\_}00180.pdf{\%}5Cnhttp://www.jstor.org/stable/1425829?origin=crossref},
  booktitle = {Advances in Applied Probability},
  file      = {:home/baffelli/Library/Matheron - 1973 - The Intrinsic Random Functions and Their Applications.pdf:pdf},
  isbn      = {00018678},
  publisher = {Cambridge University Press ({CUP})},
}

@Article{MatthiasSchonlau2005,
  author       = {{Matthias Schonlau}},
  title        = {{Background on spatial-temporal modeling}},
  journaltitle = {The Stata Journal},
  date         = {2005},
  volume       = {5},
  pages        = {330--354},
  abstract     = {Boosting, or boosted regression, is a recent data-mining technique that has shown considerable success in predictive accuracy. This article gives an overview of boosting and introduces a new Stata command, boost, that im- plements the boosting algorithm described in Hastie, Tibshirani, and Friedman (2001, 322). The plugin is illustrated with a Gaussian and a logistic regression example. In the Gaussian regression example, the R2 value computed on a test dataset is R2 = 21.3{\%} for linear regression and R2 = 93.8{\%} for boosting. In the logistic regression example, stepwise logistic regression correctly classifies 54.1{\%} of the observations in a test dataset versus 76.0{\%} for boosted logistic regression. Currently, boost accommodates Gaussian (normal), logistic, and Poisson boosted regression. boost is implemented as a Windows C++ plugin.},
  file         = {:home/baffelli/Library/Matthias Schonlau - 2005 - Background on spatial-temporal modeling.pdf:pdf},
}

@InProceedings{Mayer2003,
  author    = {Mayer, W. and Wetzel, M. and Menzel, W.},
  title     = {A novel direct-imaging radar sensor with frequency scanned antenna},
  booktitle = {{IEEE} {MTT}-S International Microwave Symposium Digest, 2003},
  date      = {2003},
  volume    = {3},
  publisher = {{IEEE}},
  isbn      = {0-7803-7695-1},
  pages     = {1941--1944},
  doi       = {10.1109/MWSYM.2003.1210538},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1210538},
  file      = {:home/baffelli/Library/Mayer, Wetzel, Menzel - 2003 - A novel direct-imaging radar sensor with frequency scanned antenna.pdf:pdf},
}

@InProceedings{Mecatti2007,
  author       = {D. Mecatti and L. Noferini and G. Macaluso and M. Pieraccini and G. Luzi and C. Atzeni and A. Tamburini},
  title        = {{Remote sensing of glacier by ground-based radar interferometry}},
  booktitle    = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year         = {2007},
  date         = {2007},
  publisher    = {{IEEE}},
  isbn         = {1424412129},
  pages        = {4501--4504},
  doi          = {10.1109/IGARSS.2007.4423856},
  abstract     = {The Belvedere Glacier, east face of Monte Rosa, has been investigated for many decades because of a long history of outburst threatening the village of Macugnaga and, in the latest years, a surge-type evolution, responsible for the formation of a large depression at the foot of the east wall of Monte Rosa, which hosted a supraglacial lake named "Lago Effimero" in summer 2002. In this contribution, a Ground Based SAR (GB-SAR) interferometer was employed for determining the ice-flow velocity of the illuminated part of the Belvedere Glacier in order to enhance the understanding of ice flow mechanics and hopefully reduce the glacier hazard. The deformation field and the velocities measured by the GB-SAR sensor have been validated with data by more conventional ground-based measurements.},
  file         = {:home/baffelli/Library/Mecatti et al. - 2007 - Remote sensing of glacier by ground-based radar interferometry.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Menke2015,
  author       = {Menke, William},
  title        = {{Review of the Generalized Least Squares Method}},
  journaltitle = {Surveys in Geophysics},
  date         = {2015},
  volume       = {36},
  pages        = {1--25},
  issn         = {15730956},
  doi          = {10.1007/s10712-014-9303-1},
  file         = {:home/baffelli/Library/Menke - 2015 - Review of the Generalized Least Squares Method.pdf:pdf},
  isbn         = {0169-3298},
  keywords     = {Biconjugate gradient,Covariance,Inverse theory,Least squares,Prior information,Resolution,Splines,Tomography},
}

@InCollection{Menke2012,
  author    = {Menke, William},
  title     = {{Chapter 5 - Solution of the Linear, Gaussian Inverse Problem, Viewpoint 3: Maximum Likelihood Methods}},
  booktitle = {Geophysical Data Analysis: Discrete Inverse Theory (Third Edition)},
  date      = {2012},
  publisher = {Elsevier},
  isbn      = {978-0-12-397160-9},
  pages     = {89--114},
  doi       = {10.1016/B978-0-12-397160-9.00005-9},
  url       = {http://www.sciencedirect.com/science/article/pii/B9780123971609000059},
  abstract  = {This chapter is the third of a trio of chapters devoted to solving the canonical inverse problem, that is, the linear problem with Gaussian statistics. It views the solution of an inverse problem as one that maximizes a probability, either that the observed data were in fact observed or that the model parameters obey a priori expectations, or some combination of the two. This principle of maximum likelihood, together with the assumption of Gaussian (Normal) statistics, is used to derive the solution to inverse problems, solutions that turn out to be identical to the weighted least squares solution of Chapter 3. The meaning of the weight matrices in weighted least squares now becomes clear. They are related to the covariance matrices of the data and the a priori model parameters. The solution is then generalized to allow for an inexact theory, with the results indicating that an inexact theory is equivalent to measurement noise. The quantity that is alternately called information gain or relative entropy is defined; it allows the information content of a p.d.f. to be quantified. It is used as a guiding principle for the construction of inverse theory solutions. They are shown to be identical to those previously derived. The F-test is introduced as a way of testing whether one solution to an inverse problem fits the data better than another, taking into consideration random variation due to measurement noise. Keywords: Maximum likelihood method, Gaussian (Normal) p.d.f., Covariance matrix, Inexact theory, Information gain, Relative entropy, Maximum relative entropy (MRE) method, F-test },
  file      = {:home/baffelli/Library/Menke - 2012 - Chapter 5 - Solution of the Linear, Gaussian Inverse Problem, Viewpoint 3 Maximum Likelihood Methods.pdf:pdf},
}

@InCollection{Menke2012a,
  author    = {Menke, William},
  title     = {{Solution of the Linear, Gaussian Inverse Problem, Viewpoint 1: The Length Method}},
  booktitle = {Geophysical Data Analysis: Discrete Inverse Theory},
  date      = {2012},
  publisher = {Elsevier},
  isbn      = {978-0-12-397160-9},
  pages     = {39--68},
  doi       = {10.1016/B978-0-12-397160-9.00003-5},
  url       = {http://www.sciencedirect.com/science/article/pii/B9780123971609000059 http://linkinghub.elsevier.com/retrieve/pii/B9780123971609000035},
  abstract  = {This chapter is the third of a trio of chapters devoted to solving the canonical inverse problem, that is, the linear problem with Gaussian statistics. It views the solution of an inverse problem as one that maximizes a probability, either that the observed data were in fact observed or that the model parameters obey a priori expectations, or some combination of the two. This principle of maximum likelihood, together with the assumption of Gaussian (Normal) statistics, is used to derive the solution to inverse problems, solutions that turn out to be identical to the weighted least squares solution of Chapter 3. The meaning of the weight matrices in weighted least squares now becomes clear. They are related to the covariance matrices of the data and the a priori model parameters. The solution is then generalized to allow for an inexact theory, with the results indicating that an inexact theory is equivalent to measurement noise. The quantity that is alternately called information gain or relative entropy is defined; it allows the information content of a p.d.f. to be quantified. It is used as a guiding principle for the construction of inverse theory solutions. They are shown to be identical to those previously derived. The F-test is introduced as a way of testing whether one solution to an inverse problem fits the data better than another, taking into consideration random variation due to measurement noise. Keywords: Maximum likelihood method, Gaussian (Normal) p.d.f., Covariance matrix, Inexact theory, Information gain, Relative entropy, Maximum relative entropy (MRE) method, F-test},
  file      = {:home/baffelli/Library/Menke - 2012 - Solution of the Linear, Gaussian Inverse Problem, Viewpoint 1 The Length Method.pdf:pdf},
}

@InCollection{Menke2012b,
  author    = {Menke, William},
  title     = {{Describing Inverse Problems}},
  booktitle = {Geophysical Data Analysis: Discrete Inverse Theory},
  date      = {2012},
  publisher = {Elsevier},
  isbn      = {978-0-12-397160-9},
  pages     = {1--14},
  doi       = {10.1016/B978-0-12-397160-9.00001-1},
  url       = {http://www.sciencedirect.com/science/article/pii/B9780123971609000011 http://linkinghub.elsevier.com/retrieve/pii/B9780123971609000011},
  abstract  = {This chapter shows that inverse problems can be classified on the basis of the mathematical structure of the theory connecting the data and model parameters. The simplest theory is the explicit linear theory, which has the form of a matrix equation relating a vector of model parameters to a vector of data. The most complicated is the implicit nonlinear problem, in which the data and model parameters are mixed together in nonlinear relationships. A series of six exemplary inverse problems are discussed, starting with the simple notion of fitting a straight line to data exhibiting a linear trend, and culminating with acoustic tomography and X-ray imaging. In each case, the mathematical relationship between the data and model parameters is derived and classified. The meaning of the term solution to an inverse problem is debated; for depending upon the context and one's point of view, any of several rather different quantities can be considered solutions. Solutions can include estimates of model parameters, deterministic or probabilistic bounds, probability density functions, and estimates of localized averages. Keywords: Data, Model parameter, Theory, Forward problem, Inverse problem, Linear, Nonlinear, Implicit, Explicit, Data kernel, Estimates, Bounds, Localized average, Probability density function},
  file      = {:home/baffelli/Library/Menke - 2012 - Describing Inverse Problems.pdf:pdf},
}

@PhdThesis{Meta2006,
  author      = {Meta, Adriano},
  title       = {Signal Processing of {FMCW} Synthetic Aperture Radar Data},
  institution = {{TU Delft}},
  year        = {2006},
  date        = {2006},
  isbn        = {907692810X},
  url         = {https://repository.tudelft.nl/islandora/object/uuid%3A24352ff9-c11a-46c9-87d4-4d9d8968ed81},
  file        = {:home/baffelli/Library/Meta - 2006 - Signal Processing of FMCW Synthetic Aperture Radar Data.pdf:pdf},
}

@Article{Meyer2005,
  author       = {Meyer, Franz and Kampes, Bert and Bamler, Richard and Fischer, Juergen},
  title        = {{Methods for Athmospheric Correction in INSAR Data}},
  journaltitle = {International Workshop on ERS SAR Interferometry: Fringe'05},
  date         = {2005},
  file         = {:home/baffelli/Library/Meyer et al. - 2005 - Methods for Athmospheric Correction in INSAR Data.pdf:pdf},
}

@Article{Michael1990,
  author       = {M.W. Whitt and F.T. Ulaby and P. Polatin and V.V. Liepa},
  title        = {A general polarimetric radar calibration technique},
  journal      = {{IEEE} Transactions on Antennas and Propagation},
  journaltitle = {IEEE Transactions on Antennas and Propagation},
  year         = {1991},
  date         = {1990},
  volume       = {39},
  pages        = {62--67},
  doi          = {10.1109/8.64436},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Michel1999,
  author       = {Remi Michel and Eric Rignot},
  title        = {Flow of {Glaciar Moreno}, {Argentina}, from repeat-pass {Shuttle Imaging Radar} images: comparison of the phase correlation method with radar interferometry},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {1999},
  date         = {1999},
  volume       = {45},
  pages        = {93--100},
  issn         = {00221430},
  doi          = {10.1017/S0022143000003075},
  abstract     = {High-resolution radar images of Glaciar Moreno, Argentina, acquired$\backslash$nby the Shuttle Imaging Radar C (SIR-C) on 9 and 10 October 1994 at$\backslash$n24 cm wavelength (L-band), are utilized to map the glacier velocity$\backslash$nboth interferometrically and using the phase correlation method.$\backslash$nThe precision of the interferometric ice velocities is 1.8 cm d(-1)$\backslash$n(6 m a(-1)) (1 sigma). The phase correlation method measures ice$\backslash$nvelocity with a precision of 14 cm d(-1) (50 m a(-1)) with image$\backslash$ndata at a 6 m sample spacing acquired 1 day apart. Averaged strain$\backslash$nrates are measured with a precision of 10(-4) d(-1) at a 240 m sample$\backslash$nspacing with the phase correlation method, and 10(-5) d(-1) with$\backslash$nradar interferometry. The phase correlation method is less precise$\backslash$nthan radar interferometry, but it performs better in areas of rapid$\backslash$nflow, is more robust to temporal changes in glacier scattering and$\backslash$nmeasures the glacier velocity in two dimensions with only one image$\backslash$npair. Using this technique, we find that Glaciar Moreno flows at$\backslash$n400 m a(-1) in the terminal valley and 800 m a(-1) at the calving$\backslash$nfront, in agreement with velocities recorded a decade ago. Assuming$\backslash$nsteady-state now conditions, the vertical strain rates measured by$\backslash$nSIR-C are combined with prior data on mass ablation to estimate the$\backslash$nglacier thickness and ice discharge. The calculated discharge is$\backslash$n0.6 +/- 0.2 km(3) ice a(-1) at 300 m elevation, and 1.1 +/- 0.2 km3$\backslash$nice a(-1) at the equilibrium-line elevation (1150 m), which yields$\backslash$na balance accumulation of 6 +/- 1 m ice a(-1).},
  file         = {:home/baffelli/Library/Michel, Rignot - 1999 - Flow of Glaciar Moreno, Argentina, from repeat-pass Shuttle Imaging Radar images Comparison of the phase correla.pdf:pdf},
  publisher    = {Cambridge University Press ({CUP})},
}

@InProceedings{Milisavljevic2010,
  author        = {Milisavljevi{\'{c}}, Nada and Closson, Damien and Bloch, Isabelle},
  title         = {{Detecting Potential Human Activities Using Coherent Change Detection}},
  booktitle     = {Proc. of 2\textsuperscript{nd} International Conference on Image Processing Theory Tools and Applications (IPTA)},
  date          = {2010-07},
  isbn          = {978-1-4244-7247-5},
  pages         = {482--485},
  doi           = {10.1109/IPTA.2010.5586772},
  keywords      = {Charge coupled devices,Coherence,Humans,Pixel,Robustness,SAR data,Soil,coherent change detection,data combination,decorrelation,image classification,knowledge sources,potential human activities,radar imaging,remote sensing,remote sensing by radar,repeat-pass synthetic aperture radar imagery,subtle scene changes detection,synthetic aperture radar,temporal change interpretation},
  mendeley-tags = {Charge coupled devices,Coherence,Humans,Pixel,Robustness,SAR data,Soil,coherent change detection,data combination,decorrelation,image classification,knowledge sources,potential human activities,radar imaging,remote sensing,remote sensing by radar,repeat-pass synthetic aperture radar imagery,subtle scene changes detection,synthetic aperture radar,temporal change interpretation},
}

@Article{Mishchenko2006,
  author       = {Mishchenko, Michael I.},
  title        = {{Maxwell's equations, radiative transfer, and coherent backscattering: A general perspective}},
  journaltitle = {Journal of Quantitative Spectroscopy and Radiative Transfer},
  date         = {2006},
  volume       = {101},
  pages        = {540--555},
  issn         = {00224073},
  doi          = {10.1016/j.jqsrt.2006.02.065},
  abstract     = {This tutorial paper provides a general overview of the hierarchy of problems involving electromagnetic scattering by particles and clarifies the place of the radiative transfer theory and the theory of coherent backscattering in the context of classical electromagnetics. The self-consistent microphysical approach to radiative transfer is compared with the traditional phenomenological treatment. {\textcopyright} 2006 Elsevier Ltd. All rights reserved.},
  file         = {:home/baffelli/Library/Mishchenko - 2006 - Maxwell's equations, radiative transfer, and coherent backscattering A general perspective.pdf:pdf},
  isbn         = {00224073},
  keywords     = {Coherent backscattering,Electromagnetic scattering,Radiative transfer},
}

@Article{Misilmani2015,
  author       = {Hilal M. El Misilmani and Mohammed Al-Husseini and Karim Y. Kabalan},
  title        = {Design of Slotted Waveguide Antennas with Low Sidelobes for High Power Microwave Applications},
  journal      = {Progress In Electromagnetics Research C},
  journaltitle = {Progress In Electromagnetics Research C},
  year         = {2015},
  date         = {2015},
  volume       = {56},
  pages        = {15--28},
  issn         = {15309681},
  doi          = {10.2528/pierc14121903},
  file         = {:home/baffelli/Library/Misilmani, Al-husseini, Kabalan - 2015 - Design of Slotted Waveguide Antennas with Low Sidelobes for High Power Microwave Applications.pdf:pdf},
  publisher    = {{EMW} Publishing},
}

@InProceedings{Mohr2001,
  author       = {Mohr, J.J. and Madsen, S.N.},
  title        = {{Error analysis for interferometric SAR measurements of ice sheet flow}},
  date         = {2001},
  volume       = {1},
  isbn         = {0-7803-5207-6},
  pages        = {98--100},
  doi          = {10.1109/IGARSS.1999.773413},
  url          = {http://asprs.org/a/publications/pers/2001journal/november/2001{\_}nov{\_}1261-1270.pdf{\%}5Cnhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=773413},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Mohr, Madsen - 2001 - Error analysis for interferometric SAR measurements of ice sheet flow.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Mohr1998,
  author       = {Mohr, Johan J. and Reeh, Niels and Madsen, Soren N.},
  title        = {{Three-dimensional glacial flow and surface elevation measured with radar interferometry}},
  journaltitle = {Nature},
  date         = {1998},
  volume       = {391},
  pages        = {273--276},
  issn         = {00280836},
  doi          = {10.1038/34635},
  abstract     = {Outlet glaciers-which serve to drain ice from ice sheets-seem to be dynamically less stable in North Greenland than in South Greenland(1-3). Storstrommen, a large outlet glacier in northeastern Greenland which surged between 1978 and 1984 (ref. 2), has been well studied. In general, neither glacier surge mechanisms nor the geographical distribution of the surges are well known. Conventional satellite radar interferometry can provide large-scale topography models with high resolution(4), and can measure the radar line-of-sight component of ice-flow vector(5), but cannot map full vector flow fields, Here we present an interferometry method that combines observations from descending and ascending satellite orbits which, assuming ice flow parallel to the topographic surface, allows us to use the differing view angles to estimate full three-dimensional surface flow patterns, The accuracy of our technique is confirmed by the good agreement between our radar-based now model and in situ Global Positioning System (GPS) reference data at Storstrommen, Radar measurements such as these, made regularly and at high spatial density, have the potential to substantially enhance our understanding of glacier dynamics and ice-sheet flow, as well as improve the accuracy of glacier mass-balance estimates.},
}

@InProceedings{Molinier2007,
  author        = {Molinier, Matthieu and Laaksonen, Jorma and Rauste, Yrjo and Hame, Tuomas},
  title         = {{Detecting changes in polarimetric SAR data with content-based image retrieval}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {2007-07},
  isbn          = {978-1-4244-1211-2},
  pages         = {2390--2393},
  doi           = {10.1109/IGARSS.2007.4423323},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4423323},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Content based retrieval,Image analysis,Image databases,Information retrieval,Layout,Optical scattering,Pixel,Self organizing feature maps,airborne radar,change detection,content-based image retrieval,feature extraction,fully polarimetric airborne SAR,image processing,image retrieval,imagelet database,polarimetric SAR data,radar polarimetry,remote sensing,remote sensing by radar,self-organising feature maps,self-organizing maps,synthetic aperture radar},
  mendeley-tags = {Content based retrieval,Image analysis,Image databases,Information retrieval,Layout,Optical scattering,Pixel,Self organizing feature maps,airborne radar,change detection,content-based image retrieval,feature extraction,fully polarimetric airborne SAR,image processing,image retrieval,imagelet database,polarimetric SAR data,radar polarimetry,remote sensing,remote sensing by radar,self-organising feature maps,self-organizing maps,synthetic aperture radar},
}

@InProceedings{Moreira2011,
  author        = {Alberto Moreira and Gerhard Krieger and Marwan Younis and Irena Hajnsek and Kostas Papathanassiou and Michael Eineder and Francesco De Zan},
  title         = {{Tandem}-{L}: A mission proposal for monitoring dynamic {Earth} processes},
  booktitle     = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year          = {2011},
  date          = {2011-07},
  publisher     = {{IEEE}},
  month         = {jul},
  isbn          = {9781457710056},
  pages         = {1385--1388},
  doi           = {10.1109/IGARSS.2011.6049324},
  abstract      = {Tandem-L is a mission proposal for an innovative interferometric L-band$\backslash$nradar instrument that enables the systematic monitoring of dynamic$\backslash$nEarth processes using advanced techniques and technologies. The mission$\backslash$nis science driven aiming to provide a unique data set for climate$\backslash$nand environmental research, geodynamics, hydrology and oceanography.$\backslash$nImportant application examples are global forest height and biomass$\backslash$ninventories, measurements of Earth deformation due to tectonic processes$\backslash$nand/or anthropogenic factors, observations of ice/glacier velocity$\backslash$nfield and 3-D structure changes, and the monitoring of soil moisture$\backslash$nand ocean surface currents. The Tandem-L mission concept consists$\backslash$nof two cooperating satellites flying in close formation. The Pol-InSAR$\backslash$nand repeat-pass acquisition modes provide a unique data source to$\backslash$nobserve, analyse and quantify a wide range of mutually interacting$\backslash$nprocesses in the bio-, litho-, hydro- and cryosphere. The systematic$\backslash$nobservation of these processes benefits from the high data acquisition$\backslash$ncapacity and the novel high-resolution wide-swath SAR imaging modes$\backslash$nthat combine digital beamforming with a large reflector antenna.$\backslash$nThis paper provides an overview of the Tandem-L mission concept and$\backslash$nits main application areas. It is planned to realise the Tandem-L$\backslash$nmission in cooperation with NASA/JPL. The mission concept was developed$\backslash$nin detail in a joint two-year pre-phase A study and it will be further$\backslash$nstudied in the next 18 months. This will allow a cost-effective implementation,$\backslash$nwhereby each partner contributes its predevelopments and experience.$\backslash$nAccording to current planning, the Tandem-L satellites could be launched$\backslash$nin 2019.},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {3D structure change,Biomass,Earth,Earth deformation measurement,Interferometry,NASA-JPL,Pol-InSAR mode,Proposals,SAR INTERFEROMETRY,Satellites,Soil,Systematics,Tandem-L mission,anthropogenic factors,array signal processing,biomass inventory,biosphere,climate research,climatology,cryosphere,data acquisition,data source,digital beamforming,dynamic Earth process monitoring,environmental research,forest height,geodynamics,geophysical techniques,glacier velocity field,glaciology,high-resolution wide-swath SAR imaging mode,hydrology,hydrosphere,ice velocity field,interferometric L-band radar instrument,large reflector antenna,lithosphere,ocean surface current,oceanography,radar imaging,radar interferometry,radar polarimetry,remote sensing by radar,repeat-pass acquisition mode,soil moisture monitoring,synthetic aperture radar,tectonic process,tectonics,vegetation},
  mendeley-tags = {3D structure change,Biomass,Earth,Earth deformation measurement,Interferometry,NASA-JPL,Pol-InSAR mode,Proposals,Satellites,Soil,Systematics,Tandem-L mission,anthropogenic factors,array signal processing,biomass inventory,biosphere,climate research,climatology,cryosphere,data acquisition,data source,digital beamforming,dynamic Earth process monitoring,environmental research,forest height,geodynamics,geophysical techniques,glacier velocity field,glaciology,high-resolution wide-swath SAR imaging mode,hydrology,hydrosphere,ice velocity field,interferometric L-band radar instrument,large reflector antenna,lithosphere,ocean surface current,oceanography,radar imaging,radar interferometry,radar polarimetry,remote sensing by radar,repeat-pass acquisition mode,soil moisture monitoring,synthetic aperture radar,tectonic process,tectonics,vegetation},
}

@Article{Moreira2013,
  author       = {Moreira, Alberto and Prats-iraola, Pau and Younis, Marwan and Krieger, Gerhard and Hajnsek, Irena and Papathanassiou, Konstantinos P.},
  title        = {{A tutorial on synthetic aperture radar}},
  journaltitle = {IEEE Geoscience and Remote Sensing Magazine},
  date         = {2013},
  volume       = {1},
  pages        = {6--43},
  issn         = {2168-6831},
  doi          = {10.1109/MGRS.2013.2248301},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6504845},
  abstract     = {Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring, 2-D and 3-D mapping, change detection, 4-D mapping (space and time), security-related applications up to planetary exploration. With the advances in radar technology and geo/bio-physical parameter inversion modeling in the 90s, using data from several airborne and spaceborne systems, a paradigm shift occurred from the development driven by the technology push to the user demand pull. Today, more than 15 spaceborne SAR systems are being operated for innumerous applications. This paper provides first a tutorial about the SAR principles and theory, followed by an overview of established techniques like polarimetry, interferometry and differential interferometry as well as of emerging techniques (e.g., polarimetric SAR interferometry, tomography and holographic tomography). Several application examples including the associated parameter inversion modeling are provided for each case. The paper also describes innovative technologies and concepts like digital beamforming, Multiple-Input Multiple-Output (MIMO) and bi- and multi-static configurations which are suitable means to fulfill the increasing user requirements. The paper concludes with a vision for SAR remote sensing.},
  file         = {:home/baffelli/Library/Moreira et al. - 2013 - A tutorial on synthetic aperture radar.pdf:pdf},
  isbn         = {2168-6831},
  keywords     = {Earth remote sensing,Radar imaging,Remote sensing,Scattering,Spaceborne radar,Synthetic aperture radar,Tutorials,bistatic configurations,differential interferometry,digital beamforming,geophysical techniques,holographic tomography,multiple-input multiple-output,multistatic configurations,polarimetric SAR interferometry,polarimetry,radar interferometry,radar polarimetry,remote sensing by radar},
}

@Article{Moreland2005,
  author = {Moreland, Kenneth},
  title  = {{Diverging Color Maps for Scientific Visualization ( Expanded )}},
  date   = {2005},
  file   = {:home/baffelli/Library/Moreland - 2005 - Diverging Color Maps for Scientific Visualization ( Expanded ).pdf:pdf},
  isbn   = {978-3-642-10519-7},
}

@Article{Moreland,
  author = {Moreland, Kenneth and Laboratories, Sandia National},
  title  = {{Why We Use Bad Color Maps and What You Can Do About It}},
  doi    = {10.2352/issn.2470-1173.2016.16.hvei-133},
  file   = {:home/baffelli/Library/Moreland, Laboratories - Unknown - Why We Use Bad Color Maps and What You Can Do About It.pdf:pdf},
}

@Article{Morena2004,
  author       = {Morena, L. C. and James, K. V. and Beck, J.},
  title        = {An introduction to the {RADARSAT-2} mission},
  journaltitle = {Canadian Journal of Remote Sensing},
  date         = {2004},
  volume       = {30},
  pages        = {221--234},
  issn         = {07038992},
  doi          = {10.5589/m04-004},
  abstract     = {The RADARSAT-2 mission comprises the construction, launch, and operation of Canada's second synthetic aperture radar earth observation spacecraft and the establishment of ground infrastructure to support the spacecraft and the data users. The RADARSAT-2 mission is being implemented in a partnership arrangement between government and private industry and will be operated and commercialized by industry. This paper provides an introduction to RADARSAT-2 and the overall context for the mission, including the background, an overview of the major operating parameters, and a description of the major elements and events in the mission. Other papers in this special issue provide details on the design of the spacecraft, the ground segment, applications, and other aspects.},
  annotation   = {NULL},
}

@InProceedings{Moses2011,
  author    = {Moses, Allistair a. and Rutherford, Matthew J. and Kontitsis, Michail and Valavanis, Kimon P.},
  title     = {{UAV-borne X-band radar for MAV collision avoidance}},
  booktitle = {Unmanned Systems Technology {XIII}},
  year      = {2011},
  date      = {2011},
  volume    = {8045},
  publisher = {{SPIE}},
  month     = {may},
  pages     = {80450U--80450U--8},
  doi       = {10.1117/12.884150},
  url       = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1270642},
  file      = {:home/baffelli/Library/Moses et al. - 2011 - {&}lttitle{&}gtUAV-borne X-band radar for MAV collision avoidance{&}lttitle{&}gt.pdf:pdf},
  keywords  = {collision avoidance,national airspace system,radar,target identification,unmanned systems},
}

@Article{Moussally2004,
  author    = {Moussally, George and Fries, Robert and Bortins, Richard},
  title     = {{Ground-penetrating , synthetic-aperture radar for wide-area airborne minefield detection}},
  year      = {2004},
  date      = {2004},
  volume    = {5415},
  month     = {sep},
  pages     = {1042--1052},
  doi       = {10.1117/12.542822},
  booktitle = {Detection and Remediation Technologies for Mines and Minelike Targets {IX}},
  file      = {:home/baffelli/Library/Moussally, Fries, Bortins - 2004 - Ground-penetrating , synthetic-aperture radar for wide-area airborne minefield detection.pdf:pdf},
  keywords  = {airborne,detection,ground penetrating radar,minefield,synthetic aperture radar,uav,wide-area},
  publisher = {{SPIE}},
}

@InProceedings{Mura2006,
  author        = {Mura, J.C. and Correia, A.H. and Freitas, C.C.},
  title         = {{A New Unified Approach to Channel Imbalance and Cross-Talk Calibration of Polarimetric Data}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {2006},
  pages         = {1281--1283},
  doi           = {10.1109/IGARSS.2006.331},
  keywords      = {Brazilian Amazon,CENSIPAM Airborne R99-SAR,Covariance matrix,Crosstalk,Iterative methods,L-band,Nonlinear distortion,Radar scattering,SAR image formation,Tapajos Forest,azimuthal symmetry,backscatter,calibration,channel imbalance,covariance matrices,cross-talk calibration,distortion system parameters,geophysical techniques,image processing,noise system,nonreciprocal distortion model,polarimetric SAR L-band data,polarization,polarization signature response,radar polarimetry,synthetic aperture radar,synthetic aperture radar processing technique,trihedral corner reflectors,vegetation},
  mendeley-tags = {Brazilian Amazon,CENSIPAM Airborne R99-SAR,Covariance matrix,Crosstalk,Iterative methods,L-band,Nonlinear distortion,Radar scattering,SAR image formation,Tapajos Forest,azimuthal symmetry,backscatter,calibration,channel imbalance,covariance matrices,cross-talk calibration,distortion system parameters,geophysical techniques,image processing,noise system,nonreciprocal distortion model,polarimetric SAR L-band data,polarization,polarization signature response,radar polarimetry,synthetic aperture radar,synthetic aperture radar processing technique,trihedral corner reflectors,vegetation},
}

@InProceedings{Myers2004,
  author    = {Myers, D.E.},
  title     = {Estimating and Modeling Space-time variograms},
  booktitle = {Proceedings of the joint meeting of The 6\textsuperscript{th} International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15\textsuperscript{th} Annual Conference of The International Environmetrics Society},
  date      = {2004},
  file      = {:home/baffelli/Library/Myers - 2004 - Estimating and Modeling Space-time variograms.pdf:pdf},
}

@Article{Navarro-Sanchez2014,
  author        = {Navarro-Sanchez, Victor D. and Lopez-Sanchez, Juan M.},
  title         = {Spatial adaptive speckle filtering driven by temporal polarimetric statistics and its application to {PSI}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2014-08},
  volume        = {52},
  pages         = {4548--4557},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2013.2282406},
  abstract      = {Persistent scatterer (PS) interferometry (PSI) techniques are designed to measure ground deformations using satellite synthetic aperture radar (SAR) data. They rely on the identification of pixels not severely affected by spatial or temporal decorrelation, which, in general, correspond to pointlike PSs commonly found in urban areas. However, in urban areas, we can find not only PSs but also distributed scatterers (DSs) whose phase information may be exploited for PSI applications. Estimation of DS parameters requires speckle filtering to be applied to the complex SAR data, but conventional speckle filtering approaches tend to mask PS information due to spatial averaging. In the context of single-polarization PSI, adaptive speckle filtering strategies based on the exploitation of amplitude temporal statistics have been proposed, which seek to avoid spatial filtering on nonhomogeneous areas. Given the growing interest on polarimetric PSI techniques, i.e., those using polarimetric diversity to increase performance over conventional single-polarization PSI, in this paper, we propose an adaptive spatial filter driven by polarimetric temporal statistics, rather than single-polarization amplitudes. The proposed approach is able to filter DS while preserving PS information. In addition, a new methodology for the joint processing of PS and DS in the context of PSI is introduced. The technique has been tested for two different urban data sets: 41 dual-polarization TerraSAR-X images of Murcia (Spain) and 31 full-polarization Radarsat-2 images of Barcelona (Spain). Results show an important improvement in terms of number of pixels with valid deformation information, hence denser area coverage.},
  keywords      = {DS parameter,Estimation,Optimization,PSI,Persistent scatterers (PSs),Radar detection,Radarsat-2 images,Scattering,Speckle,Synthetic aperture radar (SAR) interferometry,TerraSAR-X images,Vectors,adaptive filters,amplitude temporal statistics,artificial satellites,distributed scatterer,electromagnetic wave polarisation,electromagnetic wave scattering,ground deformation measurement,nonhomogeneous areas,persistent scatterer interferometry,phase information,pixel identification,point like PS,polarimetric PSI technique,polarimetric diversity,polarimetric temporal statistics,polarimetry,radar imaging,radar interferometry,radar polarimetry,satellite SAR,single polarization PSI,single polarization amplitude,spatial adaptive speckle filtering,spatial averaging,spatial filters,spatiotemporal phenomena,speckle,statistical analysis,subsidence,synthetic aperture radar,synthetic aperture radar (SAR) interferometry,temporal polarimetric statistics,urban areas},
  mendeley-tags = {DS parameter,Estimation,Optimization,PSI,Persistent scatterers (PSs),Radar detection,Radarsat-2 images,Scattering,Speckle,TerraSAR-X images,Vectors,adaptive filters,amplitude temporal statistics,artificial satellites,distributed scatterer,electromagnetic wave polarisation,electromagnetic wave scattering,ground deformation measurement,nonhomogeneous areas,persistent scatterer interferometry,phase information,pixel identification,point like PS,polarimetric PSI technique,polarimetric diversity,polarimetric temporal statistics,polarimetry,radar imaging,radar interferometry,radar polarimetry,satellite SAR,single polarization PSI,single polarization amplitude,spatial adaptive speckle filtering,spatial averaging,spatial filters,spatiotemporal phenomena,statistical analysis,subsidence,synthetic aperture radar,synthetic aperture radar (SAR) interferometry,temporal polarimetric statistics,urban areas},
}

@Article{Navarro-Sanchez2014a,
  author       = {Navarro-Sanchez, Victor D. and Lopez-Sanchez, Juan M. and Ferro-Famil, Laurent},
  title        = {Polarimetric Approaches for Persistent Scatterers Interferometry},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2014-03},
  volume       = {52},
  pages        = {1667--1676},
  issn         = {0196-2892},
  doi          = {10.1109/TGRS.2013.2253111},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6514125},
  abstract     = {In previous works, a general framework to exploit polarimetric diversity to optimize the results of persistent scatterers interferometry (PSI) was presented, but tested only with dual-pol data. In this paper, the performance of these algorithms is assessed using fully polarimetric data, acquired by the Radarsat-2 satellite over the urban area of Barcelona, Spain. In addition, two new highly efficient polarimetric optimization methods, mean intensity polarimetric optimization and joint diagonalization-based polarimetric optimization, are introduced and evaluated. Given the variety of dual-pol configurations provided by current polarimetric satellites, such as TerraSAR-X and Radarsat-2, and the upcoming launch of Sentinel-1, ALOS-2, and Radarsat Constellation Mission, a study has been also carried out to determine the best performing dual-pol configurations for polarimetric PSI. Subsidence maps of the area of study are computed for single-pol, dual-pol, and full-pol data, which show the increase in pixel density with valid deformation results as more polarimetric information is made available. In particular, for full-pol data we get an increase of up to 2.5 times more pixels for coherence-based PSI techniques (degraded resolution), and over four times more for amplitude-based approaches (full resolution), in comparison with single-pol data. Both higher density and quality of pixels yield better results in terms of coverage and accuracy.},
  file         = {:home/baffelli/Library/Navarro-Sanchez, Lopez-Sanchez, Ferro-Famil - 2014 - Polarimetric Approaches for Persistent Scatterers Interferometry.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Persistent scatterers,polarimetry,subsidence,synthetic aperture radar (SAR) interferometry},
}

@Article{Network2016,
  author   = {Network, Resste},
  title    = {{Analyzing spatio-temporal data with R : Everything you always wanted to know -- but were afraid to ask}},
  date     = {2016},
  file     = {:home/baffelli/Library/Network - 2016 - Analyzing spatio-temporal data with R Everything you always wanted to know – but were afraid to ask.pdf:pdf},
  isbn     = {9781450342056},
  keywords = {62-01,62-07,62f99,62m40,air pollution,ams 2000 subject classifications,covariance function,fonction de covariance,geostatistics,g{\'{e}}ostatistique,krigeage,kriging,mots-cl{\'{e}}s,pollution atmosph{\'{e}}rique,space-time},
}

@InProceedings{Newey2012,
  author        = {Newey, Michael and Benitz, Gerald and Kogon, Stephen},
  title         = {{A generalized likelihood ratio test for SAR CCD}},
  booktitle     = {2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)},
  date          = {2012-11},
  isbn          = {978-1-4673-5051-8},
  pages         = {1727--1730},
  doi           = {10.1109/ACSSC.2012.6489328},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6489328},
  keywords      = {GLRT,SAR CCD,SAR imagery,coherent change detection,detection statistics,footprints tracks,generalized likelihood ratio test,likelihood parameters,likelihood ratio test,object detection,optical imagery,radar imaging,statistical testing,synthetic aperture radar,synthetic aperture radar coherent change detection,synthetic aperture radar data,synthetic aperture radar imagery,vehicle tracks},
  mendeley-tags = {GLRT,SAR CCD,SAR imagery,coherent change detection,detection statistics,footprints tracks,generalized likelihood ratio test,likelihood parameters,likelihood ratio test,object detection,optical imagery,radar imaging,statistical testing,synthetic aperture radar,synthetic aperture radar coherent change detection,synthetic aperture radar data,synthetic aperture radar imagery,vehicle tracks},
}

@Article{Nguyen2007,
  author       = {Nguyen, L},
  title        = {{Image Resolution Computation for Ultra-Wideband (UWB) Synchronous Impulse Reconstruction (SIRE) Radar}},
  journaltitle = {Distribution},
  date         = {2007},
  url          = {http://oai.dtic.mil/oai/oai?verb=getRecord{\&}metadataPrefix=html{\&}identifier=ADA480190},
  file         = {:home/baffelli/Library/Nguyen - 2007 - Image Resolution Computation for Ultra-Wideband (UWB) Synchronous Impulse Reconstruction (SIRE) Radar.pdf:pdf},
}

@Article{Nguyen2008,
  author       = {Nguyen, Lam and Ressler, Marc and Sichina, Jeffrey},
  title        = {{Sensing through the wall imaging using the Army Research Lab ultra-wideband synchronous impulse reconstruction (UWB SIRE) radar}},
  journaltitle = {Proceedings of SPIE},
  date         = {2008},
  volume       = {6947},
  pages        = {69470B--69470B--10},
  issn         = {0277786X},
  doi          = {10.1117/12.776869},
  url          = {http://link.aip.org/link/PSISDG/v6947/i1/p69470B/s1{\&}Agg=doi},
  file         = {:home/baffelli/Library/Nguyen, Ressler, Sichina - 2008 - Sensing through the wall imaging using the Army Research Lab ultra-wideband synchronous impulse recons.pdf:pdf},
  isbn         = {9780819471383},
  keywords     = {sar,sensing through the wall,synthetic aperture radar,ultra-wideband radar,uwb},
}

@Article{Nguyen2007a,
  author       = {Nguyen, Lam and Wong, David and Ressler, Marc and Koenig, Francois and Stanton, Brian and Smith, Gregory and Sichina, Jeffrey and Kappra, Karl},
  title        = {{Obstacle avoidance and concealed target detection using the Army Research Lab ultra-wideband synchronous impulse reconstruction (UWB SIRE) forward imaging radar}},
  journaltitle = {Proceedings of SPIE},
  date         = {2007},
  volume       = {6553},
  pages        = {65530H--65530H--8},
  issn         = {0277786X},
  doi          = {10.1117/12.719313},
  url          = {http://link.aip.org/link/PSISDG/v6553/i1/p65530H/s1{\&}Agg=doi},
  file         = {:home/baffelli/Library/Nguyen et al. - 2007 - Obstacle avoidance and concealed target detection using the Army Research Lab ultra-wideband synchronous impulse.pdf:pdf},
  isbn         = {0819466751},
  keywords     = {forward looking radar,sar,synthetic aperture radar,ultra-wideband radar,uwb},
}

@Article{Nielsen1998,
  author       = {Nielsen, Allan A. and Conradsen, Knut and Simpson, James J.},
  title        = {{Multivariate Alteration Detection (MAD) and MAF Postprocessing in Multispectral, Bitemporal Image Data: New Approaches to Change Detection Studies}},
  journaltitle = {Remote Sensing of Environment},
  date         = {1998},
  volume       = {64},
  pages        = {1--19},
  issn         = {00344257},
  doi          = {10.1016/S0034-4257(97)00162-4},
  url          = {http://www2.imm.dtu.dk/pubdb/p.php?1220 http://www.sciencedirect.com/science/article/pii/S0034425797001624},
  abstract     = {This article introduces the multivariate alteration detection (MAD) transformation which is based on the established canonical correlations analysis. It also proposes using postprocessing of the change detected by the MAD variates using maximum autocorrelation factor (MAF) analysis. The MAD and the combined MAF/MAD transformations are invariant to linear scaling. Therefore, they are insensitive, for example, to differences in gain settings in a measuring device, or to linear radiometric and atmospheric correction schemes. Other multivariate change detection schemes described are principal component type analyses of simple difference images. Case studies with AHVRR and Landsat MSS data using simple linear stretching and masking of the change images show the usefulness of the new MAD and MAF/MAD change detection schemes. Ground truth observations confirm the detected changes. A simple simulation of a no-change situation shows the accuracy of the MAD and MAF/MAD transformations compared to principal components based methods.},
  isbn         = {0034-4257},
}

@Article{Noferini2009,
  author       = {Linhsia Noferini and Daniele Mecatti and Giovanni Macaluso and Massimiliano Pieraccini and Carlo Atzeni},
  title        = {{Monitoring of {Belvedere} {Glacier} using a wide angle {GB-SAR} interferometer}},
  journal      = {Journal of Applied Geophysics},
  journaltitle = {Journal of Applied Geophysics},
  year         = {2009},
  date         = {2009},
  volume       = {68},
  month        = {jun},
  pages        = {289--293},
  issn         = {09269851},
  doi          = {10.1016/j.jappgeo.2009.02.004},
  abstract     = {Belvedere Glacier, east face of the Mount Rosa, has experienced drastic changes in flow regime and morphology in the last years. Within the activities of the GALAHAD project funded by the European Commission, a ground-based SAR (GB-SAR) interferometer was employed on this glacier. Although based on the ground, the sensor works with the same principles as satellite radar interferometry measuring the deformation field of the illuminated surface. It was used for the first time on this glacier in 2004 and a new survey, here reported, was arranged last summer (2007). During this latter survey, the radar antenna moved around a vertical axis in order to illuminate a larger part of the glacier. It provided deformation maps of a wider part of the glacier every half an hour almost continually for 1 month. Finally, a procedure for building a digital elevation model (DEM) of the glacier was developed and the obtained DEM was compared with an available topographic map dated July 2005. Large differences in the ice surface height appear from the comparison confirming the overall reduction of the ice mass. {\textcopyright} 2009 Elsevier B.V. All rights reserved.},
  file         = {:home/baffelli/Library/Noferini et al. - 2009 - Monitoring of Belvedere Glacier using a wide angle GB-SAR interferometer.pdf:pdf},
  keywords     = {Glacier monitoring,Ground-based radar,Interferometry},
  publisher    = {Elsevier {BV}},
}

@Article{Noferini2005,
  author    = {L. Noferini and M. Pieraccini and D. Mecatti and G. Luzi and C. Atzeni and A. Tamburini and M. Broccolato},
  title     = {Permanent scatterers analysis for atmospheric correction in ground-based {SAR} interferometry},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2005},
  date      = {2005},
  volume    = {43},
  month     = {jul},
  pages     = {1459--1471},
  doi       = {10.1109/tgrs.2005.848707},
  file      = {:home/baffelli/Library/Noferini et al. - 2005 - Permanent Scatterers Analysis for Atmospheric Correction in Ground-Based SAR Interferometry.pdf:pdf},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Oishi2009,
  author        = {Oishi, Noboru and Tsuchida, Masayoshi and Wakayama, Toshio and Hasegawa, Hideki and Okada, Yu},
  title         = {{A Coherence Improvement Technique for Coherent Change Detection in SAR Interferometry}},
  booktitle     = {Proceedings of the European Radar Conference},
  date          = {2009-09},
  isbn          = {9782874870149},
  pages         = {278--281},
  keywords      = {Charge coupled devices,Inertial navigation,Instruments,Interferometry,Performance evaluation,Radar detection,Radar tracking,SAR images,SAR interferometry,Surfaces,[Electronic Manuscript],airborne SAR amplitude image,airborne radar,car tracking,coherence improvement technique,coherent change detection,fringe rate,image resolution,inertial navigation system,interferometric baseline,radar imaging,radar interferometry,synthetic aperture radar,terrain topography},
  mendeley-tags = {Charge coupled devices,Inertial navigation,Instruments,Interferometry,Performance evaluation,Radar detection,Radar tracking,SAR images,SAR interferometry,Surfaces,airborne SAR amplitude image,airborne radar,car tracking,coherence improvement technique,coherent change detection,fringe rate,image resolution,inertial navigation system,interferometric baseline,radar imaging,radar interferometry,synthetic aperture radar,terrain topography},
}

@Article{Olmsted1993,
  author   = {Olmsted, Coert},
  title    = {{Alaska SAR Facility Scientific SAR User's Guide}},
  date     = {1993},
  pages    = {57},
  abstract = {Radar sensing has been developed on the basis of four technological principles. These are: 1) the ability of an antenna to emit a brief electromagnetic pulse in a precise direction, 2) the ability to detect, also with directional precision, the greatly attenuated echo scattered from a target, 3) the ability to measure the time delay between emission and detection and thus the range to the target, and 4) the ability to scan with the directional beam and so examine an extended area for targets. A fifth principle, spectral analysis of precisely phase controlled signals, enables extreme enhancements of the application of the four physical principals. It is this last methodology which lies at the heart of synthetic aperture radar (SAR). By means of detection of small Doppler shifts in signals from targets in motion relative to the radar, it is possible to obtain, from limited peak power, imaging resolutions on the order of 3 arc seconds for spaceborne SAR and 0.01 arc second for planetary radar telescopy. These techniques depend on precise determination of the relative position and velocity of the radar with respect to the target, and on integrating the return signal information over a time period (or look ) which is long compared to the time between pulses (inter-pulse period , IPP).},
  file     = {:home/baffelli/Library/Olmsted - 1993 - Alaska SAR Facility Scientific SAR User's Guide.pdf:pdf},
}

@Article{Onn2006,
  author       = {F. Onn and H. A. Zebker},
  title        = {Correction for interferometric synthetic aperture radar atmospheric phase artifacts using time series of zenith wet delay observations from a {GPS} network},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {2006},
  date         = {2006},
  volume       = {111},
  pages        = {1--16},
  issn         = {21699356},
  doi          = {10.1029/2005JB004012},
  abstract     = {1 Radar interferograms provide precise (millimeter level) measurements of crustal deformation at fine resolution over wide areas. The dominant error source in many interferograms results from spatial heterogeneity of the wet component of atmospheric refractivity, resulting in excess path length of the radar signal propagating through the neutral atmosphere. In this report, we introduce a method to compensate for atmospheric phase artifacts in a radar interferogram using spatially interpolated zenith wet delay (ZWD) data obtained from a network of Global Positioning System (GPS) receivers in the region imaged by the radar. Our method, based on Taylor's "frozen-flow'' hypothesis, uses GPS data recorded prior to and after the individual radar acquisition times to infer denser spatial networks of control points for interpolation than is suggested by the sparse and irregular spatial distribution of GPS receivers. We test this approach by correcting phase fluctuations observed in a radar interferogram over an area covered by the Southern California Integrated GPS Network stations, using maps of atmospheric delay interpolated from the denser network of GPS ZWD measurements generated by our method. We find that the largest improvement results from removing an altitude-dependent model derived from the GPS data: the uncorrected interferogram in our example has an RMS fluctuation of 16.1 mm, which falls to 8.6 mm after the altitude correction. A map derived from ZWD measurements recorded only at the instances of radar acquisition reduced overall fluctuations in the data from 8.6 to 8.1 mm RMS, while using the inferred denser network reduces the error further to 7.5 mm RMS. Most of this residual variation is due to decorrelation of the signal and does not result from atmospheric propagation, however. After smoothing to remove decorrelation noise, the residual drops from 4.7 to 3.9 mm GPS stations only) and then to 2.7 mm RMS when the denser network algorithm is used.},
  file         = {:home/baffelli/Library/Onn, Zebker - 2006 - Correction for interferometric synthetic aperture radar atmospheric phase artifacts using time series of zenith wet.pdf:pdf},
  isbn         = {01480227},
  keywords     = {doi:10.102,flow,http://dx.doi.org/10.1029/2005JB004012},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Ouchi1985,
  author       = {Ouchi, Uzuo},
  title        = {{On the Multilook Images of Moving Targets by Synthetic Aperture Radars}},
  journaltitle = {IEEE Transactions on Antennas and Propagation},
  date         = {1985},
  volume       = {33},
  pages        = {823--827},
  issn         = {0096-1973},
  doi          = {10.1109/TAP.1985.1143684},
  abstract     = {In the multilook processing of synthetic aperture radar $\backslash$n(SAR) data, subapertures are synthesized at different center times so $\backslash$nthat a time-lapse exists between looks. This does not affect the $\backslash$nimaging of stationary targets but if targets are in motion, the $\backslash$ninformation content about the targets differs from look to look. The $\backslash$npurpose of this paper is to investigate the effects of motions on the $\backslash$nSAR mnltilook images of moving targets. Expressions are derived for $\backslash$nthe impulse response function from a moving point target in terms of $\backslash$nthe look number and the nature of the motion. Discussions are given $\backslash$nonly on the effects inherent to multilook processing.},
  file         = {:home/baffelli/Library/Ouchi - 1985 - On the Multilook Images of Moving Targets by Synthetic Aperture Radars.pdf:pdf},
  keywords     = {MTI,Multilooking,SAR},
}

@Article{Ozdemir2011,
  author       = {Ozdemir, C and Yigit, E and Demirci, S},
  title        = {{A Comparison of Focusing Algorithms for Ground Based SAR System}},
  journaltitle = {PIERS Proceedings, Marrakesh},
  date         = {2011},
  volume       = {1},
  pages        = {548--553},
  issn         = {15599450},
  file         = {:home/baffelli/Library/Ozdemir, Yigit, Demirci - 2011 - A Comparison of Focusing Algorithms for Ground Based SAR System.pdf:pdf},
}

@Article{Papathanassiou,
  author       = {Papathanassiou, Kostas and Cloude, Shane R},
  title        = {{SINGLE vs MULTI-POLARIZATION INTERFEROMETRY}},
  journaltitle = {Structure},
  pages        = {1--22},
  file         = {:home/baffelli/Library/Papathanassiou, Cloude - Unknown - SINGLE vs MULTI-POLARIZATION INTERFEROMETRY.pdf:pdf},
}

@Article{Papathanassiou2001,
  author       = {K.P. Papathanassiou and S.R. Cloude},
  title        = {Single-baseline polarimetric {SAR} interferometry},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2001},
  date         = {2001},
  volume       = {39},
  pages        = {2352--2363},
  issn         = {01962892},
  doi          = {10.1109/36.964971},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=964971},
  abstract     = {The objective of this paper is to examine the applica- tion of single-baseline polarimetric SAR interferometry to the re- mote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable for the estimation of forest parameters frominterfer- ometric observables is introduced, discussed and validated. Based on this model, an inversion algorithm which allows the estimation of forest parameters such as tree height, average extinction, and underlying topography from single-baseline fully polarimetric in- terferometric data is addressed. The performance of the inversion algorithm is demonstrated using fully polarimetric single baseline experimental data acquired by DLR's E-SAR system at L-band.},
  file         = {:home/baffelli/Library/Papathanassiou, Cloude - 2001 - Single-baseline polarimetric SAR interferometry(2).pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Forest parameter inversion,L-band,SAR,coherence,forest structure,model,polarimetric interferometry,radar polarimetry,synthetic aperture radar (SAR) interferometry,tree height},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Parrella2016,
  author       = {Giuseppe Parrella and Irena Hajnsek and Konstantinos P. Papathanassiou},
  title        = {On the Interpretation of Polarimetric Phase Differences in {SAR} Data Over Land Ice},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  year         = {2016},
  date         = {2016-02},
  volume       = {13},
  month        = {feb},
  pages        = {192--196},
  issn         = {1545-598X},
  doi          = {10.1109/LGRS.2015.2505172},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7362141},
  file         = {:home/baffelli/Library/Parrella, Hajnsek, Papathanassiou - 2016 - On the Interpretation of Polarimetric Phase Differences in SAR Data Over Land Ice.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Parrilli2010,
  author    = {S. Parrilli and M. Poderico and C.V. Angelino and G. Scarpa and L. Verdoliva},
  title     = {A nonlocal approach for {SAR} image denoising},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year      = {2010},
  date      = {2010},
  publisher = {{IEEE}},
  month     = {jul},
  pages     = {726--729},
  doi       = {10.1109/igarss.2010.5651432},
  url       = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=5651432},
}

@Article{Perissin2012,
  author       = {Perissin, Daniele and Wang, Teng},
  title        = {{Repeat-pass SAR interferometry with partially coherent targets}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2012},
  volume       = {50},
  pages        = {271--280},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2011.2160644},
  abstract     = {By means of the permanent scatterer (PS) technique, repeated spaceborne synthetic aperture radar (SAR) images with relatively low resolution (about 25 m {\&}{\#}x00D7; 5 m for the European Remote Sensing (ERS) and Envisat satellites) can be used to estimate the displacement (1-mm precision) and 3-D location (1-m precision) of targets that show an unchanged electromagnetic signature. The main drawback of the PS technique is the limited spatial density of targets that behave coherently during the whole observation span (hundreds of PSs per square kilometer in urban site and up to few points in vegetated areas). In this paper, we describe a new approach for multitemporal analysis of SAR images that also allows extracting information from partially coherent targets. The basic idea is to loosen the restrictive conditions imposed by the PS technique. The results obtained in different test sites allowed to increase significantly the spatial coverage of the estimate of height and deformation trend, particularly in extraurban areas.},
  file         = {:home/baffelli/Library/Perissin, Wang - 2012 - Repeat-pass SAR interferometry with partially coherent targets.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Deformation monitoring,digital elevation models (DEMs),synthetic aperture radar interferometry (InSAR),time-series analysis},
}

@Article{Perna2015,
  author       = {Perna, Stefano and Esposito, Carmen and Berardino, Paolo and Pauciullo, Antonio and Wimmer, Christian and Lanari, Riccardo},
  title        = {{Phase offset calculation for airborne InSAR DEM generation without corner reflectors}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2015},
  volume       = {53},
  pages        = {2713--2726},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2014.2363937},
  file         = {:home/baffelli/Library/Perna et al. - 2015 - Phase offset calculation for airborne InSAR DEM generation without corner reflectors.pdf:pdf},
  keywords     = {SAR interferometry (InSAR),Synthethic aperture radar (SAR),airborne SAR,digital elevation model (DEM)},
}

@Article{Pieraccini2016,
  author    = {Pieraccini, Massimiliano},
  title     = {{Polarimetric RotoSAR}},
  journal   = {Proceedings of the IEEE International Radar Conference},
  year      = {2016},
  date      = {2016},
  month     = {may},
  pages     = {7--11},
  doi       = {10.1109/radar.2016.7485186},
  file      = {:home/baffelli/Library/Pieraccini - 2016 - Polarimetric RotoSAR.pdf:pdf},
  isbn      = {9781509008636},
  keywords  = {after a complete,carries out a stepped,components of the backscattered,f 2 -f 1,for each,frequency f i,gb-sar,i and quadrature q,it acquires the in-phase,radar,sar,signal,sweep of bandwidth b},
  publisher = {{IEEE}},
}

@InProceedings{Pieraccini2015,
  author    = {Pieraccini, Massimiliano and Agostini, Nicola and Papi, Federico and Rocchio, Silvestro},
  title     = {{A rotating antenna ground-based SAR}},
  booktitle = {Proceedings of the European Radar Conference},
  date      = {2015-09},
  publisher = {IEEE},
  isbn      = {978-2-8748-7041-5},
  pages     = {493--496},
  doi       = {10.1109/EuRAD.2015.7346345},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7346345},
  file      = {:home/baffelli/Library/Pieraccini et al. - 2015 - A rotating antenna ground-based SAR.pdf:pdf},
  keywords  = {gb-sar,radar,sar},
}

@Article{Pieraccini2016a,
  author    = {Massimiliano Pieraccini and Lapo Miccinesi},
  title     = {Arc{SAR}: Theory, Simulations, and Experimental Verification},
  journal   = {{IEEE} Transactions on Microwave Theory and Techniques},
  year      = {2017},
  date      = {2016},
  volume    = {65},
  month     = {jan},
  pages     = {1--9},
  doi       = {10.1109/tmtt.2016.2613926},
  file      = {:home/baffelli/Library/Pieraccini, Miccinesi - 2016 - ArcSAR Theory , Simulations , and Experimental Verification.pdf:pdf},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@PhdThesis{Pipia2009,
  author      = {Pipia, Luca},
  title       = {Polarimetric Differential {SAR} Interferometry With Ground-Based Sensors},
  institution = {{Universitat Polit{\`{e}}cnica de Catalunya}},
  date        = {2009},
  doi         = {10.803/6951},
  url         = {http://hdl.handle.net/10803/6951},
  abstract    = {Differential SAR interferometry (DInSAR) deals with the combination of multi-temporal SAR images for the estimation of the linear and non-linear components of the deformation process within an area of interest during the whole observation period. A high stability of the platform is required for a reliable estimation of the geodetic phenomena. Accordingly, space-borne SAR images are operatively employed for DInSAR estimation, air-borne DInSAR still constituting a challenging research issue. SAR Polarimetry aims at charactering the illuminated area through the analysis of its response under different combinations of transmitting and receiving antennas polarization, called polarimetric channels. The Polarimetric SAR Interferometry joins the capability of Polarimetry to separate independent scattering mechanisms and the sensitivity of Interferometry to the corresponding phase centers' elevation, making it possible to describe the volumetric distribution of the scatterers within the observed area. Owing to the lack of long-time collections of polarimetric space-borne SAR data, the studies carried out in this research field have been mainly based on air-borne acquisitions. Yet, there is a great expectation for the improvements that polarimetry may bring to assessed single-polarization techniques such as the DinSAR. The research described in this PhD dissertation fills for the first time the gap between SAR Polarimetry and SAR Differential Interferometry through the employment of an X-band ground-based SAR (gbSAR) sensor developed by the Remote Sensing Lab of the Universitat Polit{\`{e}}cnica de Catalunya (UPC). The work is divided into two main blocks. The first part deals with the algorithms that have been developed to make the UPC system operative and its acquisitions easy to use. Summarily, they include the mathematical formulation of the sensor's working principles, the raw data processing chain and the polarimetric calibration method, the geocoding procedures, and the techniques compensating for the atmospheric artefacts affecting gbSAR zero-baseline acquisitions. The second part is concerned with demonstrating the benefits that polarimetric SAR measurements provide with respect to single-polarization data for differential applications. In order to cope with this task, the data sets acquired during a one-year measurement campaign carried out in the village of Sallent, northeastern Spain, are analyzed. The experiment was focused on monitoring the subsidence phenomenon affecting a district of the village with the UPC gbSAR sensor. Three main issues are here argued. The first one is the time non-stationary behaviors characterizing the urban environment at X-band in the gbSAR observation geometry. Their effects are analyzed in detail and a novel non-stationary filtering technique tailored to deterministic scatterers' properties is introduced to preserve the differential phase information. The second one is the compensation of the troposphere changes in long-time span gbSAR differential interferograms. A new technique is worked out to effectively separate the differential phase variations due to the atmospheric artefacts from the deformation components. The third one is the use of the whole polarimetric differential information. A novel polarimetric differential scattering model is put forward to relax the constraints of an advanced DInSAR technique, the Coherent Pixel Technique, and to propose an innovative polarimetric approach. The advantages offered by Polarimetric DInSAR are demonstrated in terms of quality of the deformation-rate map describing the subsidence phenomenon in Sallent. In the end, the potentials of coherence-optimization techniques for the further improvement of the deformation process estimation are stressed.},
  file        = {:home/baffelli/Library/Pipia - 2009 - Polarimetric Differential SAR Interferometry With Ground-Based Sensors.pdf:pdf},
  keywords    = {Polarimetria SAR,SAR interferometry,SAR polarimetry,diferential SAR interferometry,ground-based SAR sensers,interferometria SAR,interferometria diferencial SAR,sistemas terrestres SAR},
  volume      = {Universita},
}

@Article{Pipia2013,
  author       = {Pipia, Luca and Fabregas, Xavier and Aguasca, Albert and Lopez-Martinez, Carlos},
  title        = {Polarimetric temporal analysis of urban environments with a ground-based {SAR}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2013},
  date         = {2013},
  volume       = {51},
  pages        = {2343--2360},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2012.2211369},
  abstract     = {Revisiting time constitutes a key constraint for continuous monitoring activities based on space- and airborne synthetic aperture radar (SAR) acquisitions. Conversely, the employment of terrestrial platforms overcomes this limitation and makes it possible to perform time-continuous observations of small space-scale phenomena. New research lines of SAR dealing with the backscattering evolution of different types of scenarios become hence possible through the analysis of ground-based SAR (gbSAR) data collections. The Remote Sensing Laboratory of the Universitat Polit{\`{e}}cnica de Catalunya drove a one-year measurements campaign in the village of Sallent, northeastern Spain, using its X-Band gbSAR sensor. The field experiment aimed at studying the subsidence phenomenon induced by the salt mining activity carried out in this area during the past decades. In this paper, the polarimetric behavior of an urban environment is investigated at different time scales. After a brief description of the test site and the measurement campaign, the analysis is focused on the stability on man-made structures at different time scales. PolSAR data monthly acquired from June 2006 to July 2007 are employed to stress the presence of nonstationary backscattering processes within the urban scene and the effect they have on differential phase information. Then, a filtering procedure aiming at reducing backscattering randomness in one-day and long-term data collections is then put forward. The improvements provided by the proposed technique are assessed using a new polarimetric descriptor, the time entropy. In the end, the importance of preserving the interferometric phase information from nonstationary backscattering contaminations using fully polarimetric data is discussed},
  file         = {:home/baffelli/Library/Pipia et al. - 2013 - Polarimetric temporal analysis of urban environments with a ground-based SAR.pdf:pdf},
  keywords     = {Ground-based synthetic aperture radar (gbSAR) syst,polarimetric entropy,radar polarimetry},
}

@Article{Pipia2008,
  author       = {Luca Pipia and Xavier Fabregas and Albert Aguasca and Carlos Lopez-Martinez},
  title        = {Atmospheric Artifact Compensation in Ground-Based {DInSAR} Applications},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  year         = {2008},
  date         = {2008-01},
  volume       = {5},
  month        = {jan},
  pages        = {88--92},
  issn         = {1545-598X},
  doi          = {10.1109/LGRS.2007.908364},
  url          = {http://ieeexplore.ieee.org/document/4383036/},
  file         = {:home/baffelli/Library/Pipia et al. - 2008 - Atmospheric Artifact Compensation in Ground-Based DInSAR Applications.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Pipia2009a,
  author       = {Luca Pipia and Xavier Fabregas and Albert Aguasca and Carlos Lopez-Martinez and Sergi Duque and Jordi J. Mallorqui and Jordi Marturia},
  title        = {Polarimetric Differential {SAR} Interferometry: First Results With Ground-Based Measurements},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  year         = {2009},
  date         = {2009-01},
  volume       = {6},
  month        = {jan},
  pages        = {167--171},
  issn         = {1545-598X},
  doi          = {10.1109/LGRS.2008.2009007},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4729620 http://ieeexplore.ieee.org/document/4729620/},
  abstract     = {In this letter, a ground-based synthetic aperture radar (SAR) interferometer was used to generate digital elevation maps (DEMs) of the illuminated area. With respect to other ground-based data processing techniques, here, the effect of the propagation through the atmosphere is considered. An algorithm similar to multipass satellite SAR techniques was developed in accordance with the phase model used in the ground-based interferometry. Many images taken from different viewing angles were collected and combined to form different interferograms at a test site in Austria. Results from this technique have been compared with an existing geographic model of the test area.},
  file         = {:home/baffelli/Library/Pipia et al. - 2009 - Polarimetric differential SAR interferometry first results with ground-based measurements.pdf:pdf},
  keywords     = {ground based synthetic aperture radar (gbsar) sens,sar differential interferometry (dinsar),sar polarimetry},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Pipia2007a,
  author       = {Pipia, Luca and Fabregas, Xavier and Aguasca, Albert and Lopez-Martinez, Carlos and Mallorqui, Jordi J. and Mora, Oscar},
  title        = {A subsidence monitoring project using a polarimetric {GB-SAR} sensor},
  journaltitle = {European Space Agency, (Special Publication) ESA SP},
  date         = {2007},
  issn         = {03796566},
  file         = {:home/baffelli/Library/Pipia et al. - 2007 - A subsidence monitoring project using a polarimetric GB-SAR sensor.pdf:pdf},
}

@InProceedings{Pipia2007,
  author       = {Luca Pipia and Xavier Fabregas and Albert Aguasca and Carlos Lopez-Martinez and Jordi. J. Mallorqui and Oscar Moraline},
  title        = {Polarimetric temporal information for urban deformation map retrieval},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2007},
  date         = {2007},
  publisher    = {{IEEE}},
  isbn         = {978-1-4244-1211-2},
  pages        = {192--195},
  doi          = {10.1109/IGARSS.2007.4422762},
  abstract     = {In this work, a preliminary study on the use of polarimetric persistent scatterers for differential interferometric applications within an urban environmental is presented. The PolSAR measurements campaign that the RSLab of UPC is carrying on in the village of Salient using an X-Band ground- based SAR sensor is first described. The work is then focused on the additional information the knowledge of full scattering matrix [S] may provide with respect to the single polarization approach. The problem of instability of the polarimetric signature of urban targets is also analyzed. Finally, a solution based on the search of repeated patterns in the long-temporal profile of pixels' polarimetric signature is briefly introduced.},
  file         = {:home/baffelli/Library/Pipia et al. - 2007 - Polarimetric temporal information for urban deformation map retrieval.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {Fasteners,Geometry,Information retrieval,Interferometry,Laboratories,PolSAR,Polarization,Remote monitoring,Remote sensing,Salient village,Scattering,Sensor phenomena and characterization,UPC RSLab,X-Band ground- based SAR sensor,differential interferometric applications,full scattering matrix,polarimetric persistent scatterers,polarimetric temporal information,radar interferometry,radar polarimetry,synthetic aperture radar,town and country planning,urban deformation map retrieval},
}

@Article{Poschinger2011,
  author    = {Poschinger, Andreas Von and Flims, The and Site, Rockslide},
  title     = {{The Flims Rockslide Dam}},
  date      = {2011},
  language  = {English},
  series    = {Lecture Notes in Earth Sciences},
  volume    = {133},
  pages     = {407--421},
  doi       = {10.1007/978-3-642-04764-0},
  isbn      = {9783642047640},
  publisher = {Springer Berlin Heidelberg},
}

@InProceedings{Pottier1995,
  author        = {Pottier, E. and Cloude, S. R.},
  title         = {{Unsupervised classification of full polarimetric SAR data and feature vectors identificat1on using radar target decomposition theorems and entropy analysis}},
  booktitle     = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date          = {1995-07},
  volume        = {3},
  pages         = {2247--2249 vol.3},
  doi           = {10.1109/IGARSS.1995.524161},
  keywords      = {California,Earth,Electromagnetic scattering,Entropy,Neural networks,Radar scattering,San Francisco Bay,Terrain mapping,USA,United States,Vectors,clustering,competitive architecture,entropy analysis,entropy codes,feature extraction,feature vectors identificat1on,geophysical measurement technique,geophysical signal processing,geophysical techniques,identification procedure,image classification,image processing,image segmentation,land surface,neural net,neural network,polarimetric SAR,polarimetric decomposition theorem,radar imaging,radar polarimetry,radar remote sensing,radar target decomposition theorem,radar theory,remote sensing by radar,synthetic aperture radar,unsupervized classification},
  mendeley-tags = {California,Earth,Electromagnetic scattering,Entropy,Neural networks,Radar scattering,San Francisco Bay,Terrain mapping,USA,United States,Vectors,clustering,competitive architecture,entropy analysis,entropy codes,feature extraction,feature vectors identificat1on,geophysical measurement technique,geophysical signal processing,geophysical techniques,identification procedure,image classification,image processing,image segmentation,land surface,neural net,neural network,polarimetric SAR,polarimetric decomposition theorem,radar imaging,radar polarimetry,radar remote sensing,radar target decomposition theorem,radar theory,remote sensing by radar,synthetic aperture radar,unsupervized classification},
}

@Article{Pottier2005,
  author        = {Pottier, E. and Ferro-Famil, L. and Cloude, Shane Robert and Hajnsek, I. and Papathanassiou, K. and Moreira, A. and Pearson, T. and Desnos, Y-L},
  title         = {{PolSARpro v2.0: The Versatile Polarimetric and Interferometric SAR Data Processing Toolbox}},
  journaltitle  = {Proceedings of the European Radar Conference},
  date          = {2005-10},
  pages         = {411--414},
  doi           = {10.1109/EURAD.2005.1605647},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1605647},
  isbn          = {2-9600551-3-6},
  keywords      = {Application software,Contracts,Data analysis,Data processing,Earth,PolSARpro v2.0 software,Remote monitoring,Sea surface,Spaceborne radar,computer aided instruction,data processing toolbox,educational software,electrical engineering education,interferometric SAR,land surface,radar computing,software tools,synthetic aperture radar,versatile polarimetric},
  mendeley-tags = {Application software,Contracts,Data analysis,Data processing,Earth,PolSARpro v2.0 software,Remote monitoring,Sea surface,Spaceborne radar,computer aided instruction,data processing toolbox,educational software,electrical engineering education,interferometric SAR,land surface,radar computing,software tools,synthetic aperture radar,versatile polarimetric},
}

@Article{Pralong2006,
  author       = {Pralong, Antoine and Funk, Martin},
  title        = {{On the instability of avalanching glaciers}},
  journaltitle = {Journal of Glaciology},
  date         = {2006},
  volume       = {52},
  pages        = {31--48},
  issn         = {00221430},
  doi          = {10.3189/172756506781828980},
  abstract     = {The instability of hanging glaciers and more generally of avalanching glaciers is discussed on the basis of observations performed on several glaciers located in the European Alps. A classification of avalanching glaciers is proposed, which allows a primary appreciation of the danger inherent in these glaciers. On the basis of field observations and results of numerical simulations of crevassing, the fracture processes which lead to major icefalls, as well as their recurrence, are analyzed. A method for predicting the time of failure is then discussed. The disaggregation of the unstable ice masses usually observed prior to large icefalls is investigated and its implications for the forecasting of icefalls analyzed.},
  file         = {:home/baffelli/Library/Pralong, Funk - 2006 - On the instability of avalanching glaciers.pdf:pdf},
  isbn         = {0022-1430},
}

@Article{Prats2004,
  author        = {Prats, P. and Reigber, A. and Mallorqui, J.J.},
  title         = {{Interpolation-Free Coregistration and Phase-Correction of Airborne SAR Interferograms}},
  journaltitle  = {IEEE Geoscience and Remote Sensing Letters},
  date          = {2004-07},
  volume        = {1},
  pages         = {188--191},
  issn          = {1545-598X},
  doi           = {10.1109/LGRS.2004.828181},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1315629},
  keywords      = {Azimuth,Error analysis,Interferometry,Interpolation,L-band,Motion detection,Navigation,Phase estimation,Radar detection,SAR,airborne L-band repeat-pass interferometry,airborne SAR interferograms,airborne radar,azimuth registration errors,calibration,error correction,image registration,interpolation-free coregistration,motion compensation,navigation system,phase azimuth undulations,repeat-pass interferometry,residual motion error correction,spectral diversity technique,synthetic aperture radar},
  mendeley-tags = {Azimuth,Error analysis,Interferometry,Interpolation,L-band,Motion detection,Navigation,Phase estimation,Radar detection,SAR,airborne L-band repeat-pass interferometry,airborne SAR interferograms,airborne radar,azimuth registration errors,calibration,error correction,image registration,interpolation-free coregistration,motion compensation,navigation system,phase azimuth undulations,repeat-pass interferometry,residual motion error correction,spectral diversity technique,synthetic aperture radar},
}

@Article{Preiss2006,
  author        = {Preiss, M. and Gray, D.A. and Stacy, N.J.S.},
  title         = {{Detecting scene changes using synthetic aperture Radar interferometry}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2006-08},
  volume        = {44},
  pages         = {2041--2054},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2006.872910},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1661793},
  abstract      = {In repeat-pass interferometric synthetic aperture radar (SAR), man-made scene disturbances are commonly detected by identifying changes in the mean backscatter power of the scene or by identifying regions of low coherence. Change statistics such as the sample mean backscatter-power ratio and the sample coherence, however, are susceptible to high false-alarm rates unless the change in the mean backscatter power is large or there is sufficient contrast in scene coherence between the changed and unchanged regions of the image pair. Furthermore, as the sample mean backscatter-power ratio and sample coherence measure different properties of a SAR image pair, both change statistics need to be considered to properly characterize scene changes. In this paper, models describing the changed and unchanged regions of a scene are postulated, and the detection problem is expressed in a Bayesian hypothesis-testing framework. Forming the log-likelihood ratio gives a single sufficient statistic, encoding changes in both the coherence and the mean backscatter power, for discriminating between the unchanged- and changed-scene models. The theoretical detection performance of the change statistic is derived and shows a significant improvement over both the sample mean backscatter-power ratio and sample coherence change statistics. Finally, the superior detection performance of the log-likelihood change statistic is demonstrated using experimental data collected using the Defence Science and Technology Organisation's Ingara X-band airborne SAR},
  keywords      = {Backscatter,Change detection,Coherence,Defence Science and Technology Organisation,Ingara X-band airborne SAR,Interferometry,Layout,Phase detection,Pixel,Radar detection,Radar imaging,SAR interferometry,Statistics,Synthetic aperture radar,Synthetic aperture radar interferometry,backscatter,change detection,clairvoyant detector,coherence,hypothesis testing,image recognition,interferometry,log-likelihood change statistics,log-likelihood ratio,man-made scene disturbance,mean backscatter-power ratio,radar backscatter,radar coherence,radar imaging,remote sensing by radar,repeat-pass interferometric SAR,sample coherence change statistics,scene change detection,synthetic aperture radar,synthetic aperture radar (SAR) interferometry},
  mendeley-tags = {Coherence,Defence Science and Technology Organisation,Ingara X-band airborne SAR,Interferometry,Layout,Phase detection,Pixel,Radar detection,SAR interferometry,Statistics,Synthetic aperture radar interferometry,backscatter,change detection,clairvoyant detector,hypothesis testing,image recognition,log-likelihood change statistics,log-likelihood ratio,man-made scene disturbance,mean backscatter-power ratio,radar backscatter,radar coherence,radar imaging,remote sensing by radar,repeat-pass interferometric SAR,sample coherence change statistics,scene change detection,synthetic aperture radar,synthetic aperture radar (SAR) interferometry},
}

@Article{Preiss2008,
  author        = {Preiss, Mark and Stacy, Nick},
  title         = {{Polarimetric SAR Coherent Change Detection}},
  journaltitle  = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date          = {2008-06},
  pages         = {3--6},
  abstract      = {In repeat pass interferometric SAR man-made scene changes may be detected$\backslash$nby identifying regions of low coherence. The ability to detect such$\backslash$nchanges however, depends on other sources of decorrelation such as$\backslash$nenvironment effects and baseline decorrelation. Recently a Log Likelihood$\backslash$nChange Statistic (LLCS) has been derived by formulating the problem in a$\backslash$nBayesian hypothesis testing framework. In this paper the LLCS is extended$\backslash$nto exploit the additional information available in polarimetric SAR$\backslash$nimagery. It is shown through simulation and application to experimental$\backslash$ndata that the fully polarimetric LLCS significantly improves the ability to$\backslash$ndetect scene changes.},
  keywords      = {Coherence,Covariance matrix,Data models,Estimation,Pixel,decorrelation,measurement},
  mendeley-tags = {Coherence,Covariance matrix,Data models,Estimation,Pixel,decorrelation,measurement},
}

@Article{Quegan1994,
  author       = {S. Quegan},
  title        = {A unified algorithm for phase and cross-talk calibration of polarimetric data-theory and observations},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1994},
  date         = {1994},
  volume       = {32},
  pages        = {89--99},
  issn         = {01962892},
  doi          = {10.1109/36.285192},
  abstract     = {A unified approach to phase and cross-talk calibration of$\backslash$npolarimetric data which can be applied to calibrating scattering matrix$\backslash$ndata or to extraction of the descriptors of distributed targets is$\backslash$ndescribed. It relies on the scene being dominated by targets with$\backslash$nuncorrelated like and cross-polarized backscattering coefficients, but$\backslash$nprovides cross-talk calibration of targets for which this is not true.$\backslash$nThe algorithm needs unsymmetrized data, but uses only quantities derived$\backslash$nfrom the covariance matrix of large areas. It makes no assumptions about$\backslash$nsystem reciprocity, permits ready interpretation of the terms in the$\backslash$ncalibration procedure, allows comparison of the relative magnitude of$\backslash$nthe system-induced mixing of terms in the observed covariance matrix, is$\backslash$nnoniterative, and produces indicators which allow testing of whether it$\backslash$nmeets its own underlying assumptions. The linear distortion model is$\backslash$nshown to lead to an inconsistent system of equations; this inconsistency$\backslash$ncan be removed by introducing an extra parameter which has properties$\backslash$nexpected of system noise. The modulus of the copolarized correlation$\backslash$ncoefficient, which is important in polarimetric classification and as a$\backslash$nphase descriptor, is shown to be invariant under all effects embodied in$\backslash$nthe linear distortion model. Calibration of the scattering matrix data$\backslash$nis based on a minimum least squares principle. This suggests that$\backslash$ncurrent methods of symmetrization are not optimal. The same analysis$\backslash$nshows that estimates of parameters needed to form an equivalent$\backslash$nreciprocal system are also nonoptimal. The method is more general than$\backslash$nthe well-known van Zyl algorithm for cross-talk removal, and permits an$\backslash$nanalysis of the conditions under which the van Zyl algorithm will yield$\backslash$nvalid results. Correction of phase distortion induced by channel$\backslash$nimbalance Is treated as an optional extra step relying on a known HH-VV$\backslash$nphase difference in some region of the image. Results from the algorithm$\backslash$nare discussed using scattering matrix data from the 1989 MAESTRO$\backslash$ncampaign},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Quin2014,
  author        = {Quin, Guillaume and Pinel-Puyssegur, Beatrice and Nicolas, Jean Marie and Loreaux, Philippe},
  title         = {{MIMOSA: An automatic change detection method for sar time series}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2014-09},
  volume        = {52},
  pages         = {5349--5363},
  issn          = {01962892},
  doi           = {10.1109/TGRS.2013.2288271},
  abstract      = {This paper presents a new automatic change detection technique for synthetic aperture radar (SAR) time series, i.e., Method for generalIzed Means Ordered Series Analysis (MIMOSA). The method compares only two different temporal means between the amplitude images, whatever the length of the time series. The method involves three different steps: 1) estimation of the amplitude distribution parameters over the images; 2) computation of the theoretical joint probability density function between the two temporal means; and 3) automatic thresholding according to a given false alarm rate, which is the only change detection parameter. The procedure is executed with a very low computational cost and does not require any spatial speckle filtering. Indeed, the full image resolution is used. Due to the temporal means, the data volume to process is reduced, which is very helpful. Moreover, the two means can be simply updated using the new incoming images only. Thus, the full time series is not processed again. Change detection results between image pairs are presented with the airborne sensor CARABAS-II, using a public data release, and with TerraSAR-X data. In the case of time series, change detection results are illustrated using a TerraSAR-X time series. In every case, the MIMOSA method produces very good results.},
  keywords      = {CARABAS-II,Change detection,Estimation,Joints,MIMOSA method,Method for generalIzed Means Ordered Series Analys,SAR time series,Speckle,TerraSAR-X data,TerraSAR-X time series,Time series analysis,airborne sensor,amplitude distribution parameters,amplitude images,automatic change detection method,automatic change detection technique,change detection,full image resolution,geophysical techniques,image resolution,probability density function,remote sensing by radar,spatial speckle filtering,synthetic aperture radar,synthetic aperture radar (SAR)},
  mendeley-tags = {CARABAS-II,Estimation,Joints,MIMOSA method,Method for generalIzed Means Ordered Series Analys,SAR time series,Speckle,TerraSAR-X data,TerraSAR-X time series,Time series analysis,airborne sensor,amplitude distribution parameters,amplitude images,automatic change detection method,automatic change detection technique,change detection,full image resolution,geophysical techniques,image resolution,probability density function,remote sensing by radar,spatial speckle filtering,synthetic aperture radar,synthetic aperture radar (SAR)},
}

@PhdThesis{Rodelsperger2011,
  author      = {R{\"{o}}delsperger, Sabine},
  title       = {Real-time Processing of Ground Based Synthetic Aperture Radar ({GB-SAR}) Measurements},
  institution = {{TU} {Darmstadt}},
  year        = {2011},
  date        = {2011},
  isbn        = {9783769650808},
  file        = {:home/baffelli/Library/R{"{o}}delsperger - 2011 - Real-time Processing of Ground Based Synthetic Aperture Radar (GB-SAR) Measurements.pdf:pdf},
}

@InProceedings{Rodelsperger2012,
  author       = {Sabine Rodelsperger and Alex Coccia and Daniel Vicente and Adriano Meta},
  title        = {Introduction to the new {Metasensing} ground-based {SAR}: Technical description and data analysis},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2012},
  date         = {2012},
  publisher    = {{IEEE}},
  month        = {jul},
  isbn         = {978-1-4673-1159-5},
  pages        = {4790--4792},
  doi          = {10.1109/IGARSS.2012.6352542},
  file         = {:home/baffelli/Library/R{"{o}}delsperger et al. - 2012 - Introduction to the new metasensing ground-based SAR Technical description and data analysis.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Rodelsperger2010,
  author       = {Sabine Rödelsperger and Gwendolyn Läufer and Carl Gerstenecker and Matthias Becker},
  title        = {Monitoring of displacements with ground-based microwave interferometry: {IBIS}-{S} and {IBIS}-{L}},
  journal      = {Journal of Applied Geodesy},
  journaltitle = {Journal of Applied Geodesy},
  year         = {2010},
  date         = {2010},
  volume       = {4},
  month        = {jan},
  pages        = {41--54},
  issn         = {1862-9016},
  doi          = {10.1515/jag.2010.005},
  file         = {:home/baffelli/Library/R{"{o}}delsperger et al. - 2010 - Monitoring of displacements with ground-based microwave interferometry IBIS-S and IBIS-L.pdf:pdf},
  keywords     = {displacement monitoring,ground-based synthetic aperture,interferometry,microwave},
  publisher    = {Walter de Gruyter {GmbH}},
}

@Article{Rabus2000,
  author       = {B. T. Rabus and D. R. Fatland},
  title        = {Comparison of {SAR}-interferometric and surveyed velocities on a mountain glacier: {Black Rapids Glacier}, {Alaska}, {U.S.A.}},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {2000},
  date         = {2000},
  volume       = {46},
  pages        = {119--128},
  issn         = {00221430},
  doi          = {10.3189/172756500781833214},
  abstract     = {An interferogram reflecting the motion of Black Rapids Glacier, Alaska, U.S.A., was obtained from two European Remote-sensing Satellite (ERS-1) synthetic-aperture radar (SAR) images, acquired on 22 and 25 January 1992. We investigate whether the interferometric data are quantitatively consistent with terrestrial velocity measurements along three transverse profiles. These terrestrial data are from different years (1987, 1990, 1996) and cover different periods (6-28 April, 23 May-7 July and a whole year) than the SAR interferogram. Terrestrial ice velocity at the date of the SAR imagery is obtained via seasonal and annual corrections that are calculated from other terrestrial velocity measurements available at higher time resolution for selected sites on the glacier. Interferometric and terrestrial velocity are in excellent agreement if a (terrestrially measured) surface-normal velocity component (upsilon(perpendicular to)) is properly accounted for. This suggests that both the interferometric velocities and the conversions of terrestrial data to the winter period are reliable. The terrestrial velocity measurements show that ice now in the upper ablation area (14-16 km sites) changes from longitudinal compression in mid-winter (upsilon(perpendicular to) = +0.82 cm d(-1)) to moderate longitudinal extension during summer (upsilon(perpendicular to) approximate to -0.25 cm d(-1)). In the lower ablation area, the seasonal variations of the longitudinal strain rate are much smaller: +1.0 and about +0.85 cm d(-1) for the respective mid-winter and summer values of upsilon(perpendicular to) at the 20 km site.},
  file         = {:home/baffelli/Library/Rabus, Fatland - 2000 - Comparison of SAR-interferometric and surveyed velocities on a mountain glacier Black Rapids Glacier, Alaska, U..pdf:pdf},
  isbn         = {0022-1430},
  publisher    = {Cambridge University Press ({CUP})},
}

@InProceedings{Reaction1956,
  author    = {J. Ramsay and B. Popovich},
  title     = {Series-slotted waveguide array antennas},
  booktitle = {{IRE} International Convention Record},
  date      = {1956},
  volume    = {11},
  publisher = {Institute of Electrical and Electronics Engineers},
  pages     = {30--55},
  doi       = {10.1109/IRECON.1963.1147177},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1147177},
  file      = {:home/baffelli/Library/Ramsay, Popovich - 1956 - Series-slotted waveguide array antennas.pdf:pdf},
}

@InProceedings{Raney1994,
  author       = {Raney, R.K. and Freeman, T. and Hawkins, R.W. and Bamler, R.},
  title        = {{A plea for radar brightness}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {1994},
  volume       = {2},
  publisher    = {IEEE},
  isbn         = {0-7803-1497-2},
  pages        = {1090--1092},
  doi          = {10.1109/IGARSS.1994.399352},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=399352},
  abstract     = {The radar reflectivity coefficient of a distributed scatterer, expressed either as {\&}sigma;0 or {\&}gamma;, depends on local incidence angle. Prior to incidence angle projection, the reflectivity coefficient may be called "radar brightness", denoted by "beta nought" {\&}beta;0. In most practical situations, the local incidence angle is not known, so the image radiometrics cannot be corrected for it. It follows that {\&}beta;0 is almost always the more appropriate radiometric attribute of radar imagery, whether calibrated or uncalibrated It is recommended that {\&}sigma;0 (or {\&}gamma;) be reserved for situations in which both the local terrain slope and the illumination incidence angles are known, and the image file has been adjusted to take both angles into account. Otherwise, radar brightness is correct, which should be adopted as the standard both as concept and as working terminology. This has been endorsed by the CEOS SAR Calibration Working Group.},
  file         = {:home/baffelli/Library/Raney et al. - 1994 - A plea for radar brightness.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  pmid         = {5004624},
}

@Article{Raney1991,
  author       = {R.K. Raney and A.P. Luscombe and E.J. Langham and S. Ahmed},
  title        = {{RADARSAT} ({SAR} imaging)},
  journal      = {Proceedings of the {IEEE}},
  journaltitle = {Proceedings of the IEEE},
  year         = {1991},
  date         = {1991},
  volume       = {79},
  month        = {jun},
  pages        = {839--849},
  issn         = {00189219},
  doi          = {10.1109/5.90162},
  url          = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=90162},
  abstract     = {RADARSAT, the first Canadian remote-sensing spacecraft, is designed to provide Earth observation information for five years. The satellite is scheduled for launch in 1994. The only payload instrument is a 5.6-cm-wavelength (C-band) synthetic aperture imaging radar (SAR). RADARSAT will gather data on command for up to 28 min during each cycle of its 800-km (nominal) near-polar orbit. Image resolutions from 10 to 100 m at swath widths of 45 to 500 km will be available. The RADARSAT mission is reviewed, and the design, characteristics, and implementation of the radar are introduced. Technical problems addressed include calibration, rapid data processing, the phased array antenna that provides controlled beam steering, and the first satellite implementation of a special radar technique known as ScanSAR},
  annotation   = {NULL},
  isbn         = {0018-9219},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Rao1993,
  author       = {Rao, K.S. and Rao, Y.S. and Gurusamy, R.},
  title        = {{Frequency dependence of polarization phase difference and polarization index for vegetation covered fields using polarimetric AIRSAR data}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {1993},
  publisher    = {IEEE},
  isbn         = {0-7803-1240-6},
  pages        = {37--39},
  doi          = {10.1109/IGARSS.1993.322471},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=322471},
  file         = {:home/baffelli/Library/Rao, Rao, Gurusamy - 1993 - Frequency dependence of polarization phase difference and polarization index for vegetation covered fields u.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@TechReport{Raymond2003,
  author      = {Raymond, M{\'{e}}lanie and Wegmann, Matthias and Funk, Martin},
  title       = {{Inventar} gefährlicher {Gletscher} in der {Schweiz}},
  institution = {{ETH} Zurich},
  year        = {2003},
  date        = {2003},
  type        = {techreport},
  url         = {http://cat.inist.fr/?aModele=afficheN{\&}cpsidt=15381742},
  booktitle   = {Mitteilungen Nr 182 der Versuchsanstalt fur Wasserbau, Hydrologie und Glaziologie an der Eidgenossischen Technischen Hochschule Zurich},
  issn        = {0374-0056},
}

@TechReport{Raynal2013,
  author      = {Raynal, Ann and Doerry, Armin},
  title       = {{Initial assessment of an airborne Ku-band polarimetric SAR.}},
  institution = {Sandia National Laboratories (SNL)},
  date        = {2013-02},
  doi         = {10.2172/1088069},
  url         = {http://www.osti.gov/servlets/purl/1088069/},
  file        = {:home/baffelli/Library/Raynal, Doerry - 2013 - Initial assessment of an airborne Ku-band polarimetric SAR.pdf:pdf},
}

@Article{Refice2011,
  author       = {Refice, Alberto and Belmonte, Antonella and Bovenga, Fabio and Pasquariello, Guido},
  title        = {On the use of anisotropic covariance models in estimating atmospheric {DInSAR} contributions},
  journaltitle = {IEEE Geoscience and Remote Sensing Letters},
  date         = {2011},
  volume       = {8},
  pages        = {341--345},
  issn         = {1545598X},
  doi          = {10.1109/LGRS.2010.2073440},
  abstract     = {Stochastic models are often used to describe the spatial structure of atmospheric phase delays in differential interferometric synthetic aperture radar (DInSAR) data. Synthetic aperture radar interferograms often exhibit anisotropic atmospheric signals. In view of this, the use of anisotropic models for atmospheric phase estimation is increasingly advocated. However, anisotropic models lead to increased computational complexity in estimating the correlation function parameters with respect to the isotropic case. Moreover, the performance is degraded when dealing with DInSAR techniques involving only a few sparse points usable for computations, as in the case of persistent scatterer interferometry applications, particularly when this estimation has to be done in an automated way on many interferograms. In the present work, we propose some observations about the actual advantage given by anisotropic modeling of atmospheric phase in the case of sparse-grid point-target DInSAR applications. Through analysis of simulated data, we observe that an improvement in the performances of kriging reconstruction approaches can be obtained only when sufficient sampling densities are available. In critical sampling conditions, automated methods with reasonable computational cost may improve their performance if external information on the atmospheric phase screen field is available.},
  file         = {:home/baffelli/Library/Refice et al. - 2011 - On the use of anisotropic covariance models in estimating atmospheric DInSAR contributions.pdf:pdf},
  keywords     = {Atmospheric phase screen (APS) estimation,persistent scatterer interferometry (PSI),synthetic aperture radar interferometry},
}

@Article{Refice2013,
  author       = {Refice, Alberto and Belmonte, Antonella and Bovenga, Fabio and Pasquariello, Guido and Nutricato, Raffaele},
  title        = {On the interpolation of sparse-grid {InSAR} data without need of phase unwrapping},
  journaltitle = {European Journal of Remote Sensing},
  date         = {2013},
  volume       = {46},
  pages        = {807--821},
  issn         = {22797254},
  doi          = {10.5721/EuJRS20134648},
  abstract     = {Sparse phase measurements often need to be interpolated on regular grids, to extend the information to unsampled locations. Typical cases involve the removal of atmospheric phase screen information from Interferometric Synthetic Aperture Radar (InSAR) stacks, or the retrieval of displacement information over extended areas in Persistent Scatterers Interferometry (PSI) applications, when sufficient point densities are available. This operation is usually done after a phase unwrapping (PU) of the sparse measurements to remove the sharp phase discontinuities due to the wrap operation. PU is a difficult and error-prone operation, especially for sparse data. In this work, we investigate from the empirical point of view an alternative procedure, which involves an interpolation of the complex field derived from the sparse phase measurements. Unlike traditional approaches, our method allows to bypass the PU step and obtain a regular-grid complex field from which a wrapped phase field can be extracted. Under general conditions, this can be shown to be a good approximation of the original phase without noise. Moreover, the interpolated, wrapped phase field can be fed to state-of-the-art, regular-grid PU algorithms, to obtain an improved absolute phase field, compared to the canonical method consisting of first unwrapping the sparse-grid data. We evaluate the performance of the method in simulation, comparing it to the classical methodology described above, as well as to an alternative procedure, recently proposed, to reduce a sparse PU problem to a regular-grid one, through a nearest-neighbor interpolation step. Results confirm the increased robustness of the proposed method with respect to the effects of noise and undersampling.},
  file         = {:home/baffelli/Library/Refice et al. - 2013 - On the interpolation of sparse-grid InSAR data without need of phase unwrapping.pdf:pdf},
  keywords     = {COSMO/SkyMed,Interpolation,Phase unwrapping,SAR Interferometry},
}

@Article{Reinoso-rondinel2007,
  author = {Reinoso-rondinel, Ricardo and Bruni, Guendalina and Veldhuis, Marie-claire and Russchenberg, Herman},
  title  = {{TOWARD THE OPTIMAL RESOLUTION OF RAINFALL ESTIMATES TO OBTAIN RELIABLE URBAN HYDROLOGICAL RESPONSE : X-BAND POLARIMETRIC RADAR ESTIMATES APPLIED TO ROTTERDAM URBAN DRAINAGE SYSTEM}},
  date   = {2007},
  pages  = {1--11},
  file   = {:home/baffelli/Library/Reinoso-rondinel et al. - 2007 - TOWARD THE OPTIMAL RESOLUTION OF RAINFALL ESTIMATES TO OBTAIN RELIABLE URBAN HYDROLOGICAL RESPONSE X-B.pdf:pdf},
}

@Article{Remote2015a,
  author = {Remote, Gamma and Ag, Sensing},
  title  = {{Sentinel-1 processing with GAMMA software}},
  date   = {2015},
  pages  = {1--38},
  file   = {:home/baffelli/Library/Remote, Ag - 2015 - Sentinel-1 processing with GAMMA software.pdf:pdf},
}

@Article{Ressler2007,
  author       = {Ressler, Marc and Nguyen, Lam and Koenig, Francois and Wong, David and Smith, Gregory},
  title        = {{The Army Research Laboratory (ARL) synchronous impulse reconstruction (SIRE) forward-looking radar}},
  journaltitle = {Proceedings of SPIE},
  date         = {2007},
  volume       = {6561},
  pages        = {656105--656105--12},
  issn         = {0277786X},
  doi          = {10.1117/12.719688},
  url          = {http://link.aip.org/link/PSISDG/v6561/i1/p656105/s1{\&}Agg=doi},
  file         = {:home/baffelli/Library/Ressler et al. - 2007 - The Army Research Laboratory (ARL) synchronous impulse reconstruction (SIRE) forward-looking radar.pdf:pdf},
  isbn         = {0819466832},
  keywords     = {forward-looking radar,sar,synthetic aperture radar,ultra-wideband radar,uwb},
}

@Article{Riesen2011,
  author       = {Patrick Riesen and Tazio Strozzi and Andreas Bauder and Andreas Wiesmann and Martin Funk},
  title        = {Short-term surface ice motion variations measured with a ground-based portable real aperture radar interferometer},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {2011},
  date         = {2011},
  volume       = {57},
  pages        = {53--60},
  issn         = {00221430},
  doi          = {10.3189/002214311795306718},
  abstract     = {We report measurements using a portable real aperture radar (Gamma Portable Radar Interferometer (GPRI)) for interferometric imaging of the surface ice motion on Gornergletscher, Switzerland, during the drainage of the adjacent ice-marginal lake Gornersee. The GPRI tracked the surface ice motion in line of sight over an area of 3km2 down-glacier of Gornersee almost continuously during the drainage event. The displacement maps derived from the acquired interferograms capture the spatial distribution of the surface ice motion. Due to fast acquisition times of the microwave images, the GPRI was able to record sub-daily variations of the ice displacements, most likely caused by the impact of the Gornersee drainage on the ice motion of Gornergletscher. In situ point measurements of the ice displacement agree reasonably well with the results obtained by the GPRI and highlight the use of the GPRI for high-resolution measurements of glacier surface ice motion.},
  file         = {:home/baffelli/Library/Riesen et al. - 2011 - Short-term surface ice motion variations measured with a ground-based portable real aperture radar Interferometer.pdf:pdf},
  publisher    = {Cambridge University Press ({CUP})},
}

@Article{Rignot1992,
  author        = {Rignot, E. and Chellappa, R.},
  title         = {{A Bayes classifier for change detection in synthetic aperture radar imagery}},
  journaltitle  = {[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing},
  date          = {1992-03},
  volume        = {3},
  pages         = {25--28 vol.3},
  doi           = {10.1109/ICASSP.1992.226285},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=226285},
  isbn          = {0-7803-0532-9},
  keywords      = {Bayes classifier,Bayes methods,Data analysis,Image analysis,Meteorological radar,Meteorology,Monitoring,Radar detection,Radiometry,backscatter,change detection,image processing,meteorological cycles,multitemporal SAR data,natural surfaces,pattern recognition,phenologic cycles,radar backscatter,radar imaging,recurring natural phenomena,remote sensing by radar,synthetic aperture radar,synthetic aperture radar imagery},
  mendeley-tags = {Bayes classifier,Bayes methods,Data analysis,Image analysis,Meteorological radar,Meteorology,Monitoring,Radar detection,Radiometry,backscatter,change detection,image processing,meteorological cycles,multitemporal SAR data,natural surfaces,pattern recognition,phenologic cycles,radar backscatter,radar imaging,recurring natural phenomena,remote sensing by radar,synthetic aperture radar,synthetic aperture radar imagery},
}

@Article{Rignot1993,
  author        = {Rignot, Eric J M and {Van Zyl}, Jakob J.},
  title         = {{Change detection techniques for ERS-1 SAR data}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {1993-07},
  volume        = {31},
  pages         = {896--906},
  issn          = {01962892},
  doi           = {10.1109/36.239913},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=239913},
  abstract      = {Several techniques for detecting temporal changes in satellite synthetic aperture radar (SAR) imagery are compared using both theoretical predictions and spaceborne SAR data collected by the European first Remote Sensing Satellite, ERS- 1. In a first set of techniques, changes are detected based on differences in the magnitude of the signal intensity between two dates. Ratioing of the multidate radar intensities is shown to be better adapted to the statistical characteristics of SAR data than subtracting, and works best when the number of looks is large. In a second set of techniques, changes are detected based on estimates of the temporal decorrelation of speckle. This method works best with one-look complex amplitude data, but can also be used with intensity data provided that the number of looks is small. The two techniques, ratioing of the signal intensity and decorrelation of speckle, are compared using actual SAR data collected by ERS-1. The results illustrate the viability as well as the complementary character of these techniques for detecting changes in the structural and dielectric properties of remotely sensed surfaces. Finally, change detection using the ratio method is applied to mosaics of repeat-pass SAR imagery to illustrate the potential of this method for monitoring applications at the regional scale.},
  isbn          = {0196-2892 VO - 31},
  keywords      = {ERS-1,European Remote Sensing Satellite,Radar detection,SAR,Satellites,Spaceborne radar,Speckle,change detection,decorrelation,geophysical techniques,geophysics,imagery,land surface,measurement,multidate,radar imaging,radar remote sensing,radar theory,remote sensing,remote sensing by radar,satellite method,synthetic aperture radar,technique,temporal variation},
  mendeley-tags = {ERS-1,European Remote Sensing Satellite,Radar detection,SAR,Satellites,Spaceborne radar,Speckle,change detection,decorrelation,geophysical techniques,geophysics,imagery,land surface,measurement,multidate,radar imaging,radar remote sensing,radar theory,remote sensing,remote sensing by radar,satellite method,synthetic aperture radar,technique,temporal variation},
}

@Article{Robertson2006,
  author       = {Robertson, Duncan a. and Macfarlane, David G.},
  title        = {{High-resolution long-range radar imaging at 94 GHz}},
  journaltitle = {Proceedings of SPIE},
  date         = {2006},
  volume       = {6210},
  pages        = {62100I--62100I--8},
  issn         = {0277786X},
  doi          = {10.1117/12.669670},
  url          = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1285383},
  file         = {:home/baffelli/Library/Robertson, Macfarlane - 2006 - {&}lttitle{&}gtHigh-resolution long-range radar imaging at 94 GHz{&}lttitle{&}gt.pdf:pdf},
  keywords     = {fmcw,imaging,radar,remote sensing},
}

@Article{Robey1992,
  author       = {Robey, F.C. and Fuhrmann, D.R. and Kelly, E.J. and Nitzberg, R.},
  title        = {{A CFAR adaptive matched filter detector}},
  journaltitle = {IEEE Transactions on Aerospace and Electronic Systems},
  date         = {1992},
  volume       = {28},
  pages        = {208--216},
  issn         = {00189251},
  doi          = {10.1109/7.135446},
  url          = {http://ieeexplore.ieee.org/document/135446/},
}

@Article{Robey1992a,
  author       = {Robey, Frank C. and Fuhrmann, Daniel R. and Kelly, Edward J. and Nitzberg, Ramon},
  title        = {{A CFAR Adaptive Matched Filter Detector}},
  journaltitle = {IEEE Transactions on Aerospace and Electronic Systems},
  date         = {1992},
  volume       = {28},
  pages        = {208--216},
  issn         = {00189251},
  doi          = {10.1109/7.135446},
  abstract     = {An adaptive algorithm for radar target detection using an antenna$\backslash$narray is proposed. The detector is derived in a manner similar to that$\backslash$nof the generalized likelihood-ratio test (GLRT) but contains a$\backslash$nsimplified test statistic that is a limiting case of the GLRT detector.$\backslash$nThis simplified detector is analyzed for performance to signals on$\backslash$nboresight, as well as when the signal direction is misaligned with the$\backslash$nlook direction},
  arxivid      = {arXiv:1011.1669v3},
  file         = {:home/baffelli/Library/Robey et al. - 1992 - A CFAR Adaptive Matched Filter Detector.pdf:pdf},
  isbn         = {9788578110796},
  pmid         = {25246403},
}

@Article{Rocca2007,
  author        = {Fabio Rocca},
  title         = {Modeling Interferogram Stacks},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {2007},
  date          = {2007-10},
  volume        = {45},
  month         = {oct},
  pages         = {3289--3299},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2007.902286},
  url           = {http://ieeexplore.ieee.org/document/4305374/},
  abstract      = {Synthetic aperture radar interferometry is limited by temporal and geometrical decorrelation. Permanent scatterers (PSs) are helpful to overcome these problems, but their density in agricultural and out-of-town areas is not always sufficient. The forthcoming availability of satellite platforms with thinner orbital tubes and shorter revisit times will enhance the use of interferogram stacks, which are usable for distributed and progressively decorrelating targets, like those found in agricultural areas. To estimate the possibilities of the interferogram stack technique, a Markovian model for the temporal decorrelation is considered. ERS-1 data measured in C-band over Rome with a three-day repeat cycle are used to identify the parameters for this model, namely, the decorrelation time (estimated as 40 days) and the short-term coherence (estimated as 0.6). In the hypothesis of small deviations from a model of the motion, the optimal weights to be used to combine a sequence of interferograms taken at intervals that are shorter than the decorrelation time are calculated in the cases of progressive and sinusoidal ground motion. The dispersion of the optimal estimate of the motion is then determined. This model is extended to frequencies other than C-band. These evaluations are compared with the known results obtained for PSs. As an example, the case of a time interval between the takes of T = 12 days is considered. With N consecutive images, interferogram stack results are equivalent to PSs if the pixel count in the window used to smooth the interferograms grows with N2.},
  file          = {:home/baffelli/Library/Rocca - 2007 - Modeling Interferogram Stacks.pdf:pdf},
  isbn          = {0196-2892},
  keywords      = {Differential interferometric SAR (DInSAR),Interferometric SAR (InSAR),Synthetic aperture radar (SAR),stacking},
  mendeley-tags = {stacking},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Rodriguez1992,
  author       = {E. Rodriguez and J.M. Martin},
  title        = {Theory and design of interferometric synthetic aperture radars},
  journal      = {{IEE} Proceedings F Radar and Signal Processing},
  journaltitle = {IEE Proceedings F Radar and Signal Processing},
  year         = {1992},
  date         = {1992},
  volume       = {139},
  pages        = {147},
  doi          = {10.1049/ip-f-2.1992.0018},
  file         = {:home/baffelli/Library/Rodr{'{i}}guez, Martin - 1992 - Theory and design of interferometric synthetic aperture radars.pdf:pdf},
  keywords     = {Interferometry},
  publisher    = {Institution of Engineering and Technology ({IET})},
}

@Article{Roos1983,
  author       = {Roos, IMM and Hattingh, MJ},
  title        = {{Scanning Electron Microscopy of Pseudomonas syringae pv, morsprunorum on Sweet Cherry Leaves}},
  journaltitle = {Journal of Phytopathology},
  date         = {1983},
  volume       = {108},
  pages        = {18--25},
  issn         = {1439-0434},
  doi          = {10.1111/j.1439-0434.1983.tb00559.x},
  url          = {http://dx.doi.org/10.1111/j.1439-0434.1983.tb00559.x{\%}5Cnhttp://onlinelibrary.wiley.com/doi/10.1111/j.1439-0434.1983.tb00559.x/abstract},
  file         = {:home/baffelli/Library/Roos, Hattingh - 1983 - Scanning Electron Microscopy of Pseudomonas syringae pv, morsprunorum on Sweet Cherry Leaves.pdf:pdf},
}

@Article{Rosen2000,
  author       = {P.A. Rosen and S. Hensley and I.R. Joughin and F.K. Li and S.N. Madsen and E. Rodriguez and R.M. Goldstein},
  title        = {Synthetic aperture radar interferometry},
  journal      = {Proceedings of the {IEEE}},
  journaltitle = {Proceedings of the IEEE},
  year         = {2000},
  volume       = {88},
  number       = {3},
  month        = {mar},
  pages        = {333--382},
  doi          = {10.1109/5.838084},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=838084},
  file         = {:home/baffelli/Library/Rosen et al. - 2000 - Synthetic aperture radar interferometry.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Rosenqvist2004,
  author       = {Rosenqvist, Ake and Shimada, Masanobu and Watanabe, Manabu},
  title        = {{ALOS} {PALSAR}: Technical outline and mission concepts},
  booktitle    = {Proceeding of the International Symposium on Retrieval of Bio- and Geophysical Parameters from {SAR} Data for Land Applications},
  year         = {2004},
  date         = {2004},
  volume       = {1},
  pages        = {1--7},
  abstract     = {The Advanced Land Observing Satellite (ALOS) is Japan's next generation Earth Observation satellite, scheduled for launch in the autumn of 2005 by the Japan Aerospace Exploration Agency (JAXA) – formerly known as the National Space Development Agency of Japan, NASDA. Successor to the Japanese Earth Resources Satellite (JERS- 1), in operation 1992 – 1998, ALOS will carry two optical instruments – PRISM and AVNIR – and, to maintain Japan's commitment to L-band Synthetic Aperture Radar, the polarimetric PALSAR instrument. PALSAR will not only provide enhanced sensor performance, including full polarimetry, variable off-nadir viewing and ScanSAR operations, but also feature an entirely new acquisition concept, aiming at spatially and temporally consistent, global coverage on a repetitive basis, to accommodate geo- and bio-physical parameter retrieval over semi-continental scales.},
  annotation   = {NULL},
  journal      = {International Symposium on Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Applications},
  journaltitle = {International Symposium on Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Applications},
}

@Article{Rott2002,
  author       = {Rott, H and Nagler, T and Rocca, F and Prati, C and Mazzotti, a and Keusen, H and Liener, S and Tarchi, D},
  title        = {{InSAR} techniques and applications for monitoring landslides and subsidence},
  journaltitle = {Geoinformation for European-wide integration, proceedings of EARSeL Assembly, Prague},
  date         = {2002},
  pages        = {25--31},
  abstract     = {Interferometric synthetic aperture radar (InSAR) methods and$\backslash$napplications for mapping and monitoring displacements on mountain slopes$\backslash$nand subsidence in urban areas were investigated in the EC project MUSCL$\backslash$n(Monitoring Urban Subsidence, Cavities and Landslides by means of remote$\backslash$nsensing) using various techniques. The area-extended differential InSAR$\backslash$ntechnique was applied for mapping slow slope movements in Alpine areas,$\backslash$nbased on interferograms over annual time spans derived from ERS repeat$\backslash$npass SAR data. The Permanent Scatterer technique, using long time series$\backslash$nof SAR data, was applied to map ground deformation at millimetric$\backslash$naccuracy. The PS technique is based on dense grids of stable radar$\backslash$ntargets, enabling the correction of atmospheric noise and the$\backslash$nmeasurement of motion at the scale of individual pixels. An example is$\backslash$nshown for motion analysis of a landslide in the Italian Alps. The$\backslash$napplication of ground-based InSAR was investigated at a rockfall area in$\backslash$nthe Austrian Alps, revealing a complex deformation pattern. This$\backslash$ntechnique offers flexibility in terms of observation geometry and$\backslash$nenables continuous monitoring, making it an excellent tool for emergency$\backslash$ncases. The investigations demonstrate the power and complementarity of$\backslash$nvarious InSAR methods for detecting and monitoring hazardous mass$\backslash$nwastes.},
  file         = {:home/baffelli/Library/Rott et al. - 2002 - InSAR techniques and applications for monitoring landslides and subsidence.pdf:pdf},
  isbn         = {90-77017-71-2},
  keywords     = {abstract,cavities and landslides by,in the ec pro-,insar,interferometric synthetic aperture radar,ject muscl,landslides,mapping and,means of remote sensing,methods and applications for,monitoring displacements on mountain,monitoring urban subsidence,radar interferometry,slopes and subsidence in,subsidence,urban areas were investigated,using},
}

@InProceedings{Rudolf1999,
  author       = {H. Rudolf and D. Leva and D. Tarchi and A.J. Sieber},
  title        = {A parallelogram shaped arm for improving circular {SARs}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {1999},
  volume       = {1},
  publisher    = {{IEEE}},
  isbn         = {0-7803-5207-6},
  pages        = {553--555},
  doi          = {10.1109/IGARSS.1999.773562},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=773562},
  file         = {:home/baffelli/Library/Rudolf et al. - 1999 - A parallelogram shaped arm for improving circular SARs.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@InProceedings{Rudolf1999a,
  author       = {H. Rudolf and D. Leva and D. Tarchi and A.J. Sieber},
  title        = {A mobile and versatile {SAR} system},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {1999},
  date         = {1999},
  volume       = {1},
  publisher    = {{IEEE}},
  isbn         = {0-7803-5207-6},
  pages        = {592--594},
  doi          = {10.1109/IGARSS.1999.773575},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=773575},
  file         = {:home/baffelli/Library/Rudolf et al. - 1999 - A mobile and versatile SAR system.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Sanchez-Sevilleja2014,
  author       = {S{\'{a}}nchez-Sevilleja, S. and Arenas-Pingarr{\'{o}}n, A. and {Del Castillo-Mena}, J. and Larra{\~{n}}aga-Sudupe, J.R.},
  title        = {{A Novel and Compact Ku-band Sensor for Polarimetric SAR Systems Placed in UAVs: Development and System Performances}},
  journaltitle = {International Journal of Remote Sensing Applications},
  date         = {2014},
  volume       = {4},
  pages        = {87},
  issn         = {2226-4353},
  doi          = {10.14355/ijrsa.2014.0402.02},
  url          = {http://www.ijrsa.org//PaperInfo.aspx?ID=10538},
  file         = {:home/baffelli/Library/S{'{a}}nchez-Sevilleja et al. - 2014 - A Novel and Compact Ku-band Sensor for Polarimetric SAR Systems Placed in UAVs Development and System.pdf:pdf},
  keywords     = {aasr,antenna,nesz,rasr,resolution,sar,uav},
}

@InProceedings{Sabater2003,
  author       = {Sabater, J.M. and Hanssen, Ramon F. and Kampes, Bert M. and Fusco, A. and Adam, Nico},
  title        = {{Physical analysis of atmospheric delay signal observed in stacked radar interferometric data}},
  date         = {2003},
  volume       = {3},
  isbn         = {0-7803-7929-2},
  pages        = {2112--2115},
  doi          = {10.1109/IGARSS.2003.1294356},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1294356},
  file         = {:home/baffelli/Library/Sabater et al. - 2003 - Physical analysis of atmospheric delay signal observed in stacked radar interferometric data.pdf:pdf},
  journal      = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Sabry2009,
  author        = {Sabry, Ramin},
  title         = {{A New Coherency Formalism for Change Detection and Phenomenology in SAR Imagery: A Field Approach}},
  journaltitle  = {IEEE Geoscience and Remote Sensing Letters},
  date          = {2009-07},
  volume        = {6},
  pages         = {458--462},
  issn          = {1545-598X},
  doi           = {10.1109/LGRS.2009.2016359},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4840434},
  keywords      = {Coherence,Radar detection,SAR imagery,coherent change detection,coherent change detection (CCD),coherent correlation,complex synthetic aperture radar imagery,correlation methods,electromagnetic fields,electromagnetic wave polarisation,information extraction,partially polarized electromagnetic fields,radar imaging,synthetic aperture radar,synthetic aperture radar (SAR)},
  mendeley-tags = {Coherence,Radar detection,SAR imagery,coherent change detection,coherent change detection (CCD),coherent correlation,complex synthetic aperture radar imagery,correlation methods,electromagnetic fields,electromagnetic wave polarisation,information extraction,partially polarized electromagnetic fields,radar imaging,synthetic aperture radar,synthetic aperture radar (SAR)},
}

@TechReport{Sanders2005,
  author    = {Sanders, Frank H and Ramsey, Bradley J and {United States. National Telecommunications and Information Administration.}},
  title     = {{Phased array antenna pattern variation with frequency and implications for radar spectrum measurements}},
  date      = {2005-12},
  language  = {EN-US},
  url       = {http://purl.access.gpo.gov/GPO/LPS71154},
  abstract  = {Measured antenna patterns of an end-fed slotted waveguide antenna and a phased-array patch antenna used in maritime radionavigation radars across the frequency range 8500-10800 MHz are presented along with a measurement technique that characterizes the antenna patterns as a function of frequency. The frequency-dependent variation in the measured pattern of the slotted waveguide is compared to the frequency dependence of an ideal pattern based on the slot geometry. The implications for radar emissions measurement techniques are discussed.},
  booktitle = {NTIA report TR-06-436},
  file      = {:home/baffelli/Library/Sanders, Ramsey, United States. National Telecommunications and Information Administration. - 2005 - Phased array antenna pattern variat.pdf:pdf},
  keywords  = {Antenna radiation patterns.,Radar United States.},
  publisher = {ITS},
}

@Article{Sanders2005b,
  author       = {Sanders, Frank H and Ramsey, Bradley J and {United States. National Telecommunications and Information Administration.}},
  title        = {{Comparison of radar spectra on varying azimuths relative to the base of the antenna rotary joint}},
  journaltitle = {NTIA technical memorandum TM-05-430},
  date         = {2005},
  url          = {http://purl.access.gpo.gov/GPO/LPS71219},
  file         = {:home/baffelli/Library/Sanders, Ramsey, United States. National Telecommunications and Information Administration. - 2005 - Comparison of radar spectra on vary.pdf:pdf},
  keywords     = {Radar transmitters.},
  pmid         = {4797850},
}

@Article{Sanders2005a,
  author       = {Sanders, Frank H and {United States. National Telecommunications and Information Administration.}},
  title        = {{Bandwidth dependence of emission spectra of selected pulsed-CW radars}},
  journaltitle = {NTIA technical memorandum TM-05-431},
  date         = {2005},
  url          = {http://purl.access.gpo.gov/GPO/LPS71227},
  file         = {:home/baffelli/Library/Sanders, United States. National Telecommunications and Information Administration. - 2005 - Bandwidth dependence of emission spectra of.pdf:pdf},
  keywords     = {Radar transmitters.},
  pmid         = {4797851},
}

@Article{Sarabandi1994,
  author       = {K. Sarabandi},
  title        = {Calibration of a polarimetric synthetic aperture radar using a known distributed target},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1994},
  date         = {1994},
  volume       = {32},
  month        = {may},
  pages        = {575--582},
  issn         = {01962892},
  doi          = {10.1109/36.297998},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=297998},
  keywords     = {calibration},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Saraband1990,
  author       = {K. Sarabandi and F.T. Ulaby},
  title        = {A convenient technique for polarimetric calibration of single-antenna radar systems},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1990},
  date         = {1990},
  volume       = {28},
  number       = {6},
  pages        = {1022--1033},
  doi          = {10.1109/36.62627},
  file         = {:home/baffelli/Library/Sarabandi - 1990 - A Convenient Technique For Polarimetric Calibration of Single-Antenna Radar Systems.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Sarabandi1992a,
  author       = {K. Sarabandi and L.E. Pierce and F.T. Ulaby},
  title        = {Calibration of a polarimetric imaging {SAR}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1992},
  date         = {1992-05},
  volume       = {30},
  month        = {may},
  pages        = {540--549},
  issn         = {15580644},
  doi          = {10.1109/36.142932},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=142932},
  abstract     = {Calibration using point targets is discussed. The fourport network$\backslash$ncalibration technique is used to describe the radar error model. The$\backslash$nprocessor ambiguity function and the radar distortion matrices are$\backslash$ncombined to form a generalized polarimetric ambiguity function. The$\backslash$npolarimetric ambiguity function of the SAR is found using a single point$\backslash$ntarget, namely a trihedral corner reflector. Based on the resultant$\backslash$npolarimetric ambiguity function, an estimate for the backscattering$\backslash$ncoefficient of the terrain is found using a modified version of the$\backslash$nsingle target calibration technique (STCT). A radar image recorded by$\backslash$nthe JPL aircraft SAR, which includes a variety of point targets, is used$\backslash$nfor verification of the new calibration method. The calibrated responses$\backslash$nof the point targets are compared both with theory and responses based$\backslash$non the POLCAL technique},
  file         = {:home/baffelli/Library/Sarabandi, Pierce, Ulaby - 1992 - Calibration of a polarimetric imaging SAR.pdf:pdf},
  isbn         = {0196-2892},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Sarabandi1990,
  author        = {Sarabandi, K. and Ulaby, F.T. and Tassoudji, M.A.},
  title         = {{Calibration of polarimetric radar systems with good polarization isolation}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {1990},
  volume        = {28},
  pages         = {70--75},
  issn          = {0196-2892},
  doi           = {10.1109/36.45747},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=45747},
  abstract      = {A practical technique is proposed for calibrating single-antenna polarimetric radar systems using a metal sphere plus any second target with a strong cross-polarized radar cross section. It is shown that all magnitudes and phases (relative to one of the like-polarized linear polarization configurations) of the radar transfer function can be calibrated without knowledge of the scattering matrix of the second target. Comparison of values measured (using this calibration technique) for a tilted cylinder at X-band with theoretical values shows agreement with + or - 0.3 dB in magnitude and + or - 5 deg in phase. The technique is particularly useful for calibrating a radar under field conditions because it does not require careful alignment of calibration targets.},
  file          = {:home/baffelli/Library/Sarabandi, Ulaby, Tassoudji - 1990 - Calibration of polarimetric radar systems with good polarization isolation.pdf:pdf},
  keywords      = {Laboratories,Particle scattering,Phase measurement,Radar antennas,Radar measurements,Radar scattering,X-band,alignment,calibration,cross-polarized radar cross section,electromagnetic wave polarisation,metal sphere,polarization,polarization isolation,radar cross section,radar measurement,radar overall cross-polarization isolation,radar polarimetry,radar systems,radar transfer function,remote sensing,scattering matrix,single-antenna polarimetric radar systems,tilted cylinder},
  mendeley-tags = {Laboratories,Particle scattering,Phase measurement,Radar antennas,Radar measurements,Radar scattering,X-band,alignment,calibration,cross-polarized radar cross section,electromagnetic wave polarisation,metal sphere,polarization,polarization isolation,radar cross section,radar measurement,radar overall cross-polarization isolation,radar polarimetry,radar systems,radar transfer function,remote sensing,scattering matrix,single-antenna polarimetric radar systems,tilted cylinder},
}

@InProceedings{Sarkar1989,
  author        = {Sarkar, B.K. and Roy, R. and Reddy, C.J.},
  title         = {Deterioration in resolution of a radar using long slotted waveguide antenna},
  booktitle     = {Digest on Antennas and Propagation Society International Symposium},
  year          = {1989},
  date          = {1989-06},
  publisher     = {{IEEE}},
  pages         = {1740--1742},
  doi           = {10.1109/aps.1989.135070},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=135070},
  keywords      = {Antenna feeds,Antenna radiation patterns,Fourier series,Frequency,Gratings,Pulse measurements,Radar antennas,Slot antennas,Space vector pulse width modulation,Waveguide transitions,angular resolution,beam spread,interelement spacing,long slotted waveguide antenna,radar,range resolution,resolution deterioration,waveguide antennas},
  mendeley-tags = {Antenna feeds,Antenna radiation patterns,Fourier series,Frequency,Gratings,Pulse measurements,Radar antennas,Slot antennas,Space vector pulse width modulation,Waveguide transitions,angular resolution,beam spread,interelement spacing,long slotted waveguide antenna,radar,range resolution,resolution deterioration,waveguide antennas},
}

@InProceedings{174893,
  author     = {Sarkar, B.K. K},
  title      = {{Range resolution versus angular resolution in a long slotted waveguide antenna}},
  booktitle  = {Proceedings of the IEEE International Symposium on Antennas and Propagation},
  date       = {1991},
  publisher  = {IEEE},
  isbn       = {0-7803-0144-7},
  pages      = {535--536 vol.1},
  doi        = {10.1109/APS.1991.174893},
  url        = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=174893},
  abstract   = {It is noted that there is a limit to the length of the slotted waveguide antenna (i.e. angular resolution) with respect to the minimum pulse width of the transmitted pulse (i.e. range resolution). It is not possible to get both high range and angular resolution in a radar using the slotted waveguide antenna. An expression is derived which shows that the product of range and angular resolution is constant. Therefore, if the angular resolution is increased, then range resolution will be decreased. For example, a slotted waveguide antenna of 6-m length gave a beamwidth of 0.4 degrees . The transmitted pulsewidth could not be lowered below 3T/sub t/=84 ns at 9375 MHz, where T/sub t/ is the transit time.},
  file       = {:home/baffelli/Library/Sarkar - 1991 - Range resolution versus angular resolution in a long slotted waveguide antenna.pdf:pdf},
  keywords   = {Antenna arrays,High-resolution imaging,Image resolution,Microwave antennas,Microwave imaging,Radar antennas,Radar imaging,Slot antennas,Space vector pulse width modulation,Transmitting antennas,angular resolution,antenna length,antenna theory,beamwidth,minimum pulse width,radar,radar antennas,radar theory,range resolution,slotted waveguide antenna,transmitted pulse,wavegui,waveguide antennas},
  shorttitle = {Antennas and Propagation Society International Sym},
}

@InProceedings{Satake2000,
  author    = {Satake, Makoto and Umehara, Toshihiko and Nadai, Akitsugu and Maeno, Hideo and Uratsuka, Seiho and Matsuoka, Takeshi and Honma, Hiroaki},
  title     = {{Development and Experiment of Polarization Selective Corner Reflectors}},
  booktitle = {CEOS SAR Workshop},
  date      = {2001},
  pages     = {3--5},
  file      = {:home/baffelli/Library/Satake et al. - 2001 - Development and Experiment of Polarization Selective Corner Reflectors.pdf:pdf},
}

@InProceedings{Satake2001,
  author       = {Satake, Makoto and Umehara, Toshihiko and Nadai, Akitsugu and Maeno, Hideo and Uratsuka, Seiho and Matsuoka, Takeshi and Honma, Hiroaki},
  title        = {{Development of polarization selective corner reflectors and its experiment for calibration of airborne polarimetric synthetic aperture radar}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2001},
  volume       = {1},
  publisher    = {IEEE},
  isbn         = {0-7803-7031-7},
  pages        = {417--419},
  doi          = {10.1109/IGARSS.2001.976176},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=976176},
  file         = {:home/baffelli/Library/Satake et al. - 2001 - Development of polarization selective corner reflectors and its experiment for calibration of airborne polarimetr.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Scambos1992,
  author       = {Theodore A. Scambos and Melanie J. Dutkiewicz and Jeremy C. Wilson and Robert A. Bindschadler},
  title        = {Application of image cross-correlation to the measurement of glacier velocity using satellite image data},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {1992},
  date         = {1992},
  volume       = {42},
  month        = {dec},
  pages        = {177--186},
  issn         = {00344257},
  doi          = {10.1016/0034-4257(92)90101-o},
  abstract     = {Image-to-image cross-correlation software is applied to pairs of digital satellite images to map the velocity field of moving ice. This technique uses small-scale glacial surface features, such as crevasse scars and snow dunes, as markers on the surface of the moving ice. Displacements of the surface features are mapped by selecting small image areas centered on distinct features, or by dividing a large area of densely featured glacial surface into a grid of areas, and searching a subsequent image for matching areas using a cross-correlation algorithm. Interpolation of the peak correlation values allows the displacements to be measured to subpixel accuracy, resulting in very precise velocity measurements. Cross-correlation is also applied to provide image coregistration in areas devoid of bedrock exposures. In such areas, subtle large-scale topographic undulations in the ice surface, related to underlying bedrock structure, may be correlated by using large image areas and low-pass filtered images. Both types of applications are demonstrated, using Ice Stream D and Ice Stream E in West Antarctica as test areas. A high-resolution map of the velocity field of the central portion of Ice Stream E, generated by the displacement-measuring technique, is presented. The use of cross-correlation software is a significant improvement over previous manually-based photogrammetric methods for velocity measurement, and is far more cost-effective than in situ methods in remote polar areas. ?? 1992.},
  file         = {:home/baffelli/Library/Scambos et al. - 1992 - Application of image cross-correlation to the measurement of glacier velocity using satellite image data.pdf:pdf},
  isbn         = {0034-4257},
  publisher    = {Elsevier {BV}},
}

@Article{Schmidt2003,
  author       = {David A. Schmidt and Roland Bürgmann},
  title        = {Time-dependent land uplift and subsidence in the {Santa Clara} valley, {California}, from a large interferometric synthetic aperture radar data set},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {2003},
  date         = {2003},
  volume       = {108},
  month        = {sep},
  pages        = {2416},
  issn         = {0148-0227},
  doi          = {10.1029/2002jb002267},
  abstract     = {We invert 115 differential interferograms derived from 47 synthetic aperture radar (SAR) scenes for a time-dependent deformation signal in the Santa Clara valley, California. The time-dependent deformation is calculated by performing a linear inversion that solves for the incremental range change between SAR scene acquisitions. A nonlinear range change signal is extracted from the ERS InSAR data without imposing a model of the expected deformation. In the Santa Clara valley, cumulative land uplift is observed during the period from 1992 to 2000 with a maximum uplift of 41 ± 18 mm centered north of Sunnyvale. Uplift is also observed east of San Jose. Seasonal uplift and subsidence dominate west of the Silver Creek fault near San Jose with a maximum peak-to-trough amplitude of ∼35 mm. The pattern of seasonal versus long-term uplift provides constraints on the spatial and temporal characteristics of water-bearing units within the aquifer. The Silver Creek fault partitions the uplift behavior of the basin, suggesting that it acts as a hydrologic barrier to groundwater flow. While no tectonic creep is observed along the fault, the development of a low-permeability barrier that bisects the alluvium suggests that the fault has been active since the deposition of Quaternary units.},
  file         = {:home/baffelli/Library/Schmidt, B{"{u}}rgmann - 2003 - Time-dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometri.pdf:pdf},
  isbn         = {2156-2202},
  keywords     = {1243 Space geodetic surveys,1829 Groundwater hydrology,1884 Water supply,5114 Permeability and porosity,6924 Interferometry,InSAR,Santa Clara Valley,land subsidence,time series},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Schreiber2013,
  author       = {Schreiber, E and Peichl, M and Jirousek, M and Suess, H and {The Society of Photo-Optical Instrumentation}, Engineers},
  title        = {{Vesas: A novel concept for fully-electronic passive mw imaging}},
  journaltitle = {Passive and Active Millimeter-Wave Imaging XVI},
  date         = {2013},
  volume       = {8715},
  pages        = {1--7},
  issn         = {0277786X},
  doi          = {10.1117/12.2016990},
  url          = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84881053731{\&}partnerID=40{\&}md5=2b9519590df12e8f749e43c86636bc65},
  abstract     = {These days passive microwave (MW) remote sensing has found many applications. For example, in Earth observation missions, it is possible to estimate the salinity of oceans, the soil moisture of landscapes, or to extract atmospheric parameters like the liquid water content of clouds [1, 2, 3]. Due to the penetration capabilities of microwaves through many dielectric materials, and the purely passive character of this kind of remote sensing, this technique nowadays is considered as well in many security and reconnaissance applications (e.g. observation of sensitive areas, detection of concealed objects, trough-wall imaging, etc.). Presently different imaging principles for MW radiometry are possible. Most of them still are based on pure mechanical scanning or they combine this with electronic scanning by using parts of a focal plane array [4]. Due to many advantages, the technological trend is going towards fully-electronic beam steering or two-dimensional focal plane arrays. These systems are able to achieve high frame rates, but they are still very expensive because of a significantly higher number of receiver modules, compared to a mechanical scanning system. In our approach a novel concept for a Ka band fully-electronic wide swath MW imaging radiometer system is introduced [5]. It is based on a combination of beam steering by frequency shift for one scanning direction using a slottedwaveguide antenna, and the application of aperture synthesis in the other. In the following a proof of concept is outlined using a two-element interferometer system called VESAS (Voll elektronischer Scanner mit Apertursynthese) demonstrator. The advantage of using the aperture synthesis technique is the possibility to implement minimal redundant sparse arrays without a degradation of the antenna pattern. In combination with the beam steering by frequency shift, one requires a one dimensional receiver/antenna array for a two dimensional imaging, hence a low-cost, fully-electronic wide swath microwave radiometer system with high frame rates is feasible. In the following a proof of concept is outlined by presenting different MW imaging measurement results, using this kind of imaging principle.{\textcopyright} 2013 SPIE.},
  file         = {:home/baffelli/Library/Schreiber et al. - 2013 - Vesas A novel concept for fully-electronic passive mw imaging.pdf:pdf},
  isbn         = {0277786X (ISSN); 9780819495068 (ISBN)},
  keywords     = {Antennas,Aperture synthesis,Dielectric materials,Frequency scan,Frequency scans,Frequency shift keying,Fully-electronic imaging,Ka band,Low-cost,Microwave devices,Millimeter waves,Minimal redundant,Radiometry,Real-time imaging,Realtime imaging,Remote sensing,Scanning,Slotted-waveguide antenna,Slotted-waveguide antennas,Soil moisture,Two dimensional,Wide swath},
}

@Article{Segment2012,
  author = {Segment, Tandem-x Payload Ground and Generation, Cossc and Considerations, Interferometric},
  title  = {{TanDEM-X Payload Ground Segment CoSSC Generation and Interferometric Considerations}},
  date   = {2012},
  file   = {:home/baffelli/Library/Segment, Generation, Considerations - 2012 - TanDEM-X Payload Ground Segment CoSSC Generation and Interferometric Considerations.pdf:pdf},
}

@Article{Sheen1989,
  author        = {Sheen, D.R. and Freeman, A. and Kasischke, E.S.},
  title         = {{Phase calibration of polarimetric radar images}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {1989},
  volume        = {27},
  pages         = {719--731},
  issn          = {0196-2892},
  doi           = {10.1109/36.35960},
  keywords      = {C-band,L-band,NASA,P-band,Radar antennas,Radar scattering,Sea measurements,Signal to noise ratio,antennas,calibration,channel leakage,displacement,distributed ground targets,phase calibration,phase errors,picture processing,polarimetric radar images,polarization,polarization channels,radar applications,radar imaging,radar polarimetry,radar remote sensing,radar system architecture,radar systems,remote sensing,spatial variation,synthetic aperture radar,system imperfections},
  mendeley-tags = {C-band,L-band,NASA,P-band,Radar antennas,Radar scattering,Sea measurements,Signal to noise ratio,antennas,calibration,channel leakage,displacement,distributed ground targets,phase calibration,phase errors,picture processing,polarimetric radar images,polarization,polarization channels,radar applications,radar imaging,radar polarimetry,radar remote sensing,radar system architecture,radar systems,remote sensing,spatial variation,synthetic aperture radar,system imperfections},
}

@Article{Shi-qiXing2012,
  author        = {{Shi-qi Xing} and {Da-hai Dai} and {Jin Liu} and {Xue-song Wang}},
  title         = {{Comment on "Orientation Angle Preserving A Posteriori Polarimetric SAR Calibration"}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {2012-06},
  volume        = {50},
  pages         = {2417--2419},
  issn          = {0196-2892},
  doi           = {10.1109/TGRS.2012.2188297},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6191317},
  keywords      = {Algorithm design and analysis,Covariance matrix,Crosstalk,Equations,Mathematical model,calibration,orientation angle,polarimetric SAR calibration,radar,radar polarimetry,synthetic aperture radar,synthetic aperture radar (SAR)},
  mendeley-tags = {Algorithm design and analysis,Covariance matrix,Crosstalk,Equations,Mathematical model,calibration,orientation angle,polarimetric SAR calibration,radar,radar polarimetry,synthetic aperture radar,synthetic aperture radar (SAR)},
}

@InCollection{Snieder1999,
  author    = {R. Snieder and J. Trampert},
  title     = {Inverse Problems in Geophysics},
  booktitle = {Wavefield Inversion},
  year      = {1999},
  date      = {1999},
  publisher = {Springer Vienna},
  isbn      = {978-3-7091-2486-4},
  pages     = {119--190},
  doi       = {10.1007/978-3-7091-2486-4_3},
  file      = {:home/baffelli/Library/Snieder, Trampert - 1999 - Inverse Problems in Geophysics.pdf:pdf},
}

@InCollection{SniederRoel1999,
  author    = {R. Snieder and J. Trampert},
  title     = {Inverse Problems in Geophysics},
  booktitle = {Springer Vienna},
  year      = {1999},
  date      = {1999},
  publisher = {Springer Vienna},
  pages     = {119--190},
  doi       = {10.1007/978-3-7091-2486-4_3},
  url       = {http://link.springer.com/10.1007/978-3-7091-2486-4{\_}3},
  file      = {:home/baffelli/Library/Snieder, Trampert - 1999 - Inverse Problems in Geophysics.pdf:pdf},
}

@Article{Soumekh1994,
  author    = {Soumekh, Mehrdad},
  title     = {{Fourier array imaging}},
  date      = {1994-05},
  url       = {http://dl.acm.org/citation.cfm?id=174727},
  isbn      = {0-13-063769-6},
  publisher = {Prentice-Hall, Inc.},
}

@Article{Springman2012,
  author       = {Springman, Sarah M. and Arenson, Lukas U. and Yamamoto, Yuko and Maurer, Hansruedi and Kos, Andrew and Buchli, Thomas and Derungs, Guido},
  title        = {{Multidisciplinary investigations on three rock glaciers in the swiss alps: Legacies and future perspectives}},
  journaltitle = {Geografiska Annaler, Series A: Physical Geography},
  date         = {2012},
  volume       = {94},
  pages        = {215--243},
  issn         = {04353676},
  doi          = {10.1111/j.1468-0459.2012.00464.x},
  abstract     = {This paper recognizes the contribution of Professor Wilfried Haeberli for his inspiration and leadership in the field of permafrost science and his generous encouragement, both direct and indirect, to the ETH Researchers who have, through him, endeavoured to contribute to this fascinating research area. The multidisciplinary investigations described in this paper have focused on three rock glaciers, Muragl, Murt{\`{e}}l-Corvatsch and Furggwanghorn, all of which have been subject to a varying degree of prior study, and which are continuing to attract new generations of researchers to understand and explain the processes and predict future behaviour. This paper marks a stage at which it is possible to summarize some advances in the state of the art and associated innovations that can be attributed to early motivation by Wilfried Haeberli and offers a tribute as well as gratitude for his ongoing feedback and advice. Some thoughts on the development of thermokarst due to water ponding and flow, and a conceptual model of geotechnical mechanisms that aim to explain some aspects of rock glacier kinematics, are also introduced.},
  file         = {:home/baffelli/Library/Springman et al. - 2012 - Multidisciplinary investigations on three rock glaciers in the swiss alps Legacies and future perspectives.pdf:pdf},
  keywords     = {Alpine permafrost,Characterization,Degradation,Modelling,Monitoring,Rock glacier},
}

@Article{Pettersson2000,
  author       = {Stangl, M. and Werninghaus, R. and Schweizer, B. and Fischer, C. and Brandfass, M. and Mittermayer, J. and Breit, H.},
  title        = {{TerraSAR-X technologies and first results}},
  journaltitle = {IEE Proceedings - Radar, Sonar and Navigation},
  date         = {2006},
  volume       = {153},
  pages        = {86},
  issn         = {13502395},
  doi          = {10.1049/ip-rsn:20045119},
  url          = {http://digital-library.theiet.org/content/journals/10.1049/ip-rsn{\_}20045119},
  abstract     = {Identification concerning different types of radar targets can be achieved by using various radar signatures, such as one-dimensional (1-D) range profiles, 2-D radar images, and 1-D or 2-D scattering centres on a target. To solve the target identification problem, the authors utilise 1-D scattering centres, which correspond to the highest peaks in the 1-D range profile. The proposed approach obtains scale and translational-invariant features based on the central moments from the distribution of the 1-D scattering centres on the target; these 1-D scattering centres can be extracted from various techniques such as inverse fast Fourier transform (IFFT), fast root-multiple signal classification (fast root-MUSIC), total least squares-Prony (TLS-Prony), generalised eigenvalues utilising signal subspace eigenvectors (GEESE), and the matrix-pencil (MP) algorithm. The information redundancy contained in these features, as well as their dimensions, are further reduced via the Karhunen–Loeve transform, followed by adequate scaling of the computed central moments. The resulting small dimensional and redundancy-free feature vectors are classified using the Bayes classifier. Finally, this new strategy for radar-target identification is demonstrated with data measured in the compact range facility, and the above five different techniques for 1-D scattering centre extraction are compared and investigated in the context of target identification},
  annotation   = {NULL},
  file         = {:home/baffelli/Library/Stangl et al. - 2006 - TerraSAR-X technologies and first results.pdf:pdf},
  isbn         = {1350-2395 VO - 148},
  pmid         = {23609804},
}

@Article{Stein1986,
  author       = {Stein, Michael},
  title        = {{A simple model for spatial-temporal processes}},
  journaltitle = {Water Resources Research},
  date         = {1986-12},
  volume       = {22},
  pages        = {2107--2110},
  issn         = {00431397},
  doi          = {10.1029/WR022i013p02107},
  file         = {:home/baffelli/Library/Stein - 1986 - A simple model for spatial-temporal processes(2).pdf:pdf},
}

@Article{Stein2013,
  author       = {Stein, Michael L},
  title        = {{On a class of space -- time intrinsic random functions}},
  journaltitle = {Bernoulli},
  date         = {2013},
  volume       = {19},
  pages        = {387--408},
  issn         = {1350-7265},
  doi          = {10.3150/11-BEJ405},
  arxivid      = {arXiv:1303.4620v1},
  file         = {:home/baffelli/Library/Stein - 2013 - On a class of space – time intrinsic random functions.pdf:pdf},
  keywords     = {ern covariance function,fox,generalized covariance function,mat,s h -function},
}

@Article{Stein2013a,
  author       = {Stein, Michael L},
  title        = {{On a class of space -- time intrinsic random functions}},
  journaltitle = {Bernoulli},
  date         = {2013},
  volume       = {19},
  pages        = {387--408},
  issn         = {1350-7265},
  doi          = {10.3150/11-BEJ405},
  arxivid      = {arXiv:1303.4620v1},
  file         = {:home/baffelli/Library/Stein - 2013 - On a class of space – time intrinsic random functions.pdf:pdf},
  keywords     = {ern covariance function,fox,generalized covariance function,mat,s h -function},
}

@Article{Stove1992,
  author        = {A.G. Stove},
  title         = {Linear {FMCW} radar techniques},
  journal       = {{IEE} Proceedings F Radar and Signal Processing},
  journaltitle  = {IEE Proceedings F Radar and Signal Processing},
  year          = {1992},
  date          = {1992-10},
  volume        = {139},
  pages         = {343},
  issn          = {0956375X},
  doi           = {10.1049/ip-f-2.1992.0048},
  abstract      = {Frequency modulated continuous wave (FMCW) radar uses a very low probability of intercept waveform, which is also well suited to make good use of simple solid-state transmitters. FMCW is finding applications in such diverse fields as naval tactical navigation radars, smart ammunition sensors and automotive radars. The paper discusses some features of FMCW radar which are not dealt with in much detail in the generally available literature. In particular, it discusses the effects of noise reflected back from the transmitter to the receiver and the application of moving target indication to FMCW radars. Some of the strengths and weaknesses of FMCW radar are considered. The paper describes how the strengths are utilised in some systems and how the weaknesses can be mitigated. It also discusses a modern implementation of a reflected power canceller, which can be used to suppress the leakage between the transmitter and the receiver, a well known problem with continuous wave radars},
  file          = {:home/baffelli/Library/Stove - 1992 - Linear FMCW radar techniques.pdf:pdf},
  keywords      = {automotive radars,frequency modulated continuous wave,frequency modulation,linear FMCW radar,low probability of intercept waveform,military systems,moving target indication,naval tactical navigation radars,radar systems,reflected power canceller,smart ammunition sensors,solid-state transmitters},
  mendeley-tags = {automotive radars,frequency modulated continuous wave,frequency modulation,linear FMCW radar,low probability of intercept waveform,military systems,moving target indication,naval tactical navigation radars,radar systems,reflected power canceller,smart ammunition sensors,solid-state transmitters},
  publisher     = {Institution of Engineering and Technology ({IET})},
}

@InProceedings{Strozzi2010,
  author       = {Tazio Strozzi and Reynald Delaloye and Hugo Raetzo and Urs Wegm{\"{u}}ller},
  title        = {{Radar interferometric observations of destabilized rock glaciers}},
  booktitle    = {Prooceedings of Fringe},
  year         = {2009},
  date         = {2010},
  pages        = {5},
  doi          = {10.1126/science.170.3962.1090},
  url          = {http://earth.esa.int/workshops/fringe09/proceedings/papers/s12{\_}4stroz.pdf},
  abstract     = {Analysis of ERS-1/2 Tandem SAR interferograms for inventorying mass wasting in the periglacial belt of the Valais Alps (Switzerland) has evidenced - what was not expected before - that at least 10 rockglaciers were affected by very rapid movements of about 1 cm/day in 1995-1999. Currently, the detection of the state of activity of these very rapidly moving rockglaciers is hardly feasible with sate llite SAR data, because of signal decorrelation after the 35, 46 and 11 days repeat intervals of the ENVISA T, ALOS and TerraSAR-X satellites, respectively. The role of space-borne radar interferometry as an element in a warning system is thus insignificant for these very rapid landslides, but an in- situ radar imaging system can overcome some of the limitations of satellite systems. In this contribution we present results from terrestrial radar interferometric measurements of two destabilized rockglaciers performed in August 2009.},
  file         = {:home/baffelli/Library/Strozzi et al. - 2010 - Radar interferometric observations of destabilized rock glaciers.pdf:pdf},
  issn         = {0036-8075},
  journaltitle = {Proc. ‘Fringe 2009 Workshop', Frascati, Italy, 30 November – 4 December 2009 (ESA SP-677, March 2010)},
  pmid         = {17777829},
}

@Article{Strozzi2002,
  author       = {T. Strozzi and A. Luckman and T. Murray and U. Wegmüller and C.L. Werner},
  title        = {Glacier motion estimation using {SAR} offset-tracking procedures},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2002},
  date         = {2002},
  volume       = {40},
  month        = {nov},
  pages        = {2384--2391},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2002.805079},
  abstract     = {Two image-to-image patch offset techniques for estimating feature motion between satellite synthetic aperture radar (SAR) images are discussed. Intensity tracking, based on patch intensity cross-correlation optimization, and coherence tracking, based on patch coherence optimization, are used to estimate the movement of glacier surfaces between two SAR images in both slant-range and azimuth direction. The accuracy and application range of the two methods are examined in the case of the surge of Monacobreen in Northern Svalbard between 1992 and 1996. Offset-tracking procedures of SAR images are an alternative to differential SAR interferometry for the estimation of glacier motion when differential SAR interferometry is limited by loss of coherence, i.e. in the case of rapid and incoherent flow and of large acquisition time intervals between the two SAR images. In addition, an offset-tracking procedure in the azimuth direction may be combined with differential SAR interferometry in the slant-range direction in order to retrieve a two-dimensional displacement map when SAR data of only one orbit configuration are available.},
  file         = {:home/baffelli/Library/Strozzi et al. - 2002 - Glacier motion estimation using SAR offset-tracking procedures.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Glacier-motion estimation,Offset tracking SAR,SAR interferometry,Surge-type glacier},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Strozzi2001,
  author       = {Strozzi, T and Wegm{\"{u}}ller, Urs and Tosi, L and Bitelli, G and Spreckels, V},
  title        = {Land subsidence monitoring with differential {SAR} interferometry},
  journaltitle = {Photogrammetric Engineering {\&} Remote Sensing},
  date         = {2001},
  volume       = {67},
  pages        = {1261--1270},
  issn         = {0099-1112},
  abstract     = {The potential of differential SAR interferometry for land subsidence monitoring is reported on. The principle of the technique and the approach to be used on a specific case are first presented. Then significant results using SAR data from the ERS satellites for various sites in Germany, Mexico, and Italy, representing fast (m/year) to slow (mm/year) deformation velocities, are discussed. The SAR interferometric displacement maps are validated with available leveling data. The accuracy of the subsidence maps produced, the huge SAR data archive starting in 1991, the expected continued availability of SAR data, and the maturity of the required processing techniques lead to the conclusion that differential SAR interferometry is suitable for operational monitoring of land subsidence.},
  file         = {:home/baffelli/Library/Strozzi et al. - 2001 - Land subsidence monitoring with differential SAR interferometry.pdf:pdf},
  keywords     = {ICE-SHEET MOTION,SATELLITE RADAR INTERFEROMETRY},
}

@InProceedings{Strozzi2000,
  author    = {Strozzi, Tazio and Wegm{\"{u}}ller, Urs and Werner, Charles and Wiesmann, Andreas},
  title     = {Measurement of slow uniform surface displacement with mm/year accuracy},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date      = {2000},
  volume    = {00},
  publisher = {{IEEE}},
  isbn      = {0780363620},
  pages     = {4--6},
  doi       = {10.1109/igarss.2000.858368},
  file      = {:home/baffelli/Library/Strozzi et al. - 2000 - Measurement of slow uniform surface displacement with mm year accuracy.pdf:pdf},
  journal   = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Strozzi2011,
  author        = {Strozzi, Tazio and Werner, Charles and Wiesmann, Andreas and Wegm{\"{u}}ller, Urs},
  title         = {{Topography mapping with a portable real-aperture radar interferometer}},
  journaltitle  = {IEEE Geoscience and Remote Sensing Letters},
  date          = {2011-03},
  volume        = {9},
  pages         = {277--281},
  issn          = {1545-598X},
  doi           = {10.1109/LGRS.2011.2166751},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6035758},
  abstract      = {In this letter, the requirements to derive topography from a portable terrestrial radar interferometer are introduced, the instrument design and the relationship between interferometric phase shift and surface topography are explained, and two examples of topographic maps from measurements at the Rhone glacier and Grabengufer rock glacier in Switzerland are presented. In the first case, an external digital elevation model was used to assess the error of topography mapping with the portable radar interferometer and to analyze ice surface changes of the glacier in the last 14 years. We found that the height error standard deviation is about 3 m within a distance of 2 km from the sensor and observed massive thinning of the Rhone glacier. In the second case, we used the terrestrial radar interferometer in order to measure the height difference between August 2009 and March 2010 over the rock glacier as a consequence of its destabilization.},
  file          = {:home/baffelli/Library/Strozzi et al. - 2011 - Topography mapping with a portable real-aperture radar interferometer.pdf:pdf},
  isbn          = {1545-598X},
  keywords      = {AD 2009 08 to 2010 03,Digital elevation model (DEM),Digital elevation models,Grabengufer rock glacier,Radar antennas,Spaceborne radar,Surface topography,Surfaces,Switzerland,Terrain mapping,digital elevation model,glacier,glaciology,height error standard deviation,ice surface change,instrument design,interferometric phase shift,massive Rhone glacier thinning,portable real-aperture radar interferometer,portable terrestrial radar interferometer,radar,radar imaging,radar interferometry,radar remote sensing,rock glacier destabilization,rocks,topography (Earth),topography mapping},
  mendeley-tags = {AD 2009 08 to 2010 03,Digital elevation model (DEM),Digital elevation models,Grabengufer rock glacier,Radar antennas,Spaceborne radar,Surface topography,Surfaces,Switzerland,Terrain mapping,digital elevation model,glacier,glaciology,height error standard deviation,ice surface change,instrument design,interferometric phase shift,massive Rhone glacier thinning,portable real-aperture radar interferometer,portable terrestrial radar interferometer,radar,radar imaging,radar interferometry,radar remote sensing,rock glacier destabilization,rocks,topography (Earth),topography mapping},
}

@InProceedings{Tao2007,
  author       = {Tao, Wu and Hong, Zhang and Chao, Wang},
  title        = {{Ground deformation retrieval of urban and suburb areas based on multi-baseline DInSAR algorithm: A case study in Cangzhou city (China)}},
  date         = {2007},
  isbn         = {1424412129},
  pages        = {4898--4901},
  doi          = {10.1109/IGARSS.2007.4423959},
  file         = {:home/baffelli/Library/Tao, Hong, Chao - 2007 - Ground deformation retrieval of urban and suburb areas based on multi-baseline DInSAR algorithm A case study in.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {DInSAR,Deformation,Multi-baseline,Subsidence},
}

@Article{Tao2015,
  author   = {Tao, Zeng and Mao, Z H U and Cheng, H U and Weiming, Tian and Michail, Antoniou},
  title    = {{DEM generation using bistatic interferometry : high-coherence pixel selection and residual reference phase compensation}},
  date     = {2015},
  volume   = {58},
  pages    = {1--14},
  doi      = {10.1007/s11432-015-5333-7},
  file     = {:home/baffelli/Library/Tao et al. - 2015 - DEM generation using bistatic interferometry high-coherence pixel selection and residual reference phase compensati.pdf:pdf},
  keywords = {bistatic insar,bistatic sar,dem,high coherence pixel,sar},
}

@Article{Tarantola1982,
  author  = {Albert Tarantola and Bernard Valette},
  title   = {Inverse problems - Quest for information},
  journal = {Journal of Geophysics},
  year    = {1982},
  pages   = {159--170},
}

@InCollection{Tebaldini2010,
  author    = {Stefano Tebaldini and Andrea Monti},
  title     = {Methods and Performances for Multi-Pass {SAR} Interferometry},
  booktitle = {Geoscience and Remote Sensing New Achievements},
  year      = {2010},
  date      = {2010},
  publisher = {{InTech}},
  pages     = {329--357},
  doi       = {10.5772/9112},
  url       = {http://cdn.intechopen.com/pdfs/10403/InTech-Methods{\_}and{\_}performances{\_}for{\_}multi{\_}pass{\_}sar{\_}interferometry.pdf},
  file      = {:home/baffelli/Library/Tebaldini, Guarnieri - 2010 - Methods and performances for multi-pass SAR Interferometry.pdf:pdf},
  month     = {feb},
}

@Article{Tebaldini2008,
  author        = {Stefano Tebaldini and Andrea Monti Guarnieri},
  title         = {A {Cram{\'{e}}r} {Rao} like lower bound for parametric phase estimation in multi-pass {SAR} interferometry},
  journal       = {Italian Journal of Remote Sensing},
  journaltitle  = {Italian Journal of Remote Sensing},
  year          = {2008},
  date          = {2008-06},
  volume        = {40},
  month         = {jun},
  pages         = {123--131},
  issn          = {11298596},
  doi           = {10.5721/ItJRS200840211},
  url           = {http://www.aitjournal.com/articleView.aspx?ID=284},
  abstract      = {This paper focuses on the determination of a Cramer Rao like bound$\backslash$nfor the estimation of phase parameters referring to temporal series$\backslash$nin spaceborne interferometric RADAR. These data are affected by a$\backslash$nmultiplicative random noise due to the atmospheric propagation, besides$\backslash$nthe usual additive noise. These factors combine non linearly, jeopardizing$\backslash$nboth the quality of the estimates and the assessment of the estimator's$\backslash$naccuracy. The analysis proposed within this paper handles this issue$\backslash$nby splitting the calculus of the Cramer Rao bound (CRB) into two$\backslash$nparts, each of which involves the calculus of a CRB over a normal$\backslash$ndistribution. We show the implication of such result in the example$\backslash$nof multipass Synthetic Aperture Radar Interferometry (InSAR).},
  file          = {:home/baffelli/Library/Tebaldini, Monti Guarnieri - 2008 - A Cram{'{e}}r Rao like lower bound for parametric phase estimation in multi-pass SAR interferometry.pdf:pdf},
  keywords      = {hybrid cram{\'{e}}r rao bound,sar interferometry,stacking,target decorrelation},
  mendeley-tags = {stacking},
  publisher     = {Associazione Italiana di Telerilevamento},
}

@Article{Thonfeld2013,
  author       = {Thonfeld, Frank and Nielsen, Allan A and Skriver, Henning and Conradsen, Knut and Morton, J},
  title        = {{COMPLEX WISHART DISTRIBUTION-BASED CHANGE DE- TECTION WITH POLARIMETRIC TERRASAR-X IMAGERY Complex Wishart distribution}},
  journaltitle = {Imm.Dtu.Dk},
  date         = {2013},
  pages        = {3--6},
  file         = {:home/baffelli/Library/Thonfeld et al. - 2013 - COMPLEX WISHART DISTRIBUTION-BASED CHANGE DE- TECTION WITH POLARIMETRIC TERRASAR-X IMAGERY Complex Wishart dist.pdf:pdf},
}

@Article{Tomasz,
  Title                    = {{Space-Time Adaptive Processing analysis for the moving target on the sea surface indication purpose Overview of STAP}},
  Author                   = {Tomasz, G and Czarnecki, Witold and Pietrasi, Jerzy},
  Pages                    = {3--6},

  File                     = {:home/baffelli/Library/Tomasz, Czarnecki, Pietrasi - Unknown - Space-Time Adaptive Processing analysis for the moving target on the sea surface indication purp.pdf:pdf}
}

@Article{Torres2012,
  author       = {Torres, Ramon and Snoeij, Paul and Geudtner, Dirk and Bibby, David and Davidson, Malcolm and Attema, Evert and Potin, Pierre and Rommen, Bj{\"{O}}rn and Floury, Nicolas and Brown, Mike and Traver, Ignacio Navas and Deghaye, Patrick and Duesmann, Berthyl and Rosich, Betlem and Miranda, Nuno and Bruno, Claudio and L'Abbate, Michelangelo and Croci, Renato and Pietropaolo, Andrea and Huchler, Markus and Rostan, Friedhelm},
  title        = {{GMES Sentinel-1 mission}},
  journaltitle = {Remote Sensing of Environment},
  date         = {2012-05},
  volume       = {120},
  pages        = {9--24},
  issn         = {00344257},
  doi          = {10.1016/j.rse.2011.05.028},
  url          = {http://linkinghub.elsevier.com/retrieve/pii/S0034425712000600},
  annotation   = {NULL},
}

@InProceedings{Tospann1995a,
  author    = {Tospann, Franz-Jose and Pirkl, Martin and Gruener, W.},
  title     = {{Multifunction 35-GHz FMCW radar with frequency scanning antenna for synthetic vision applications}},
  booktitle = {SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics},
  date      = {1995-06},
  volume    = {2463},
  publisher = {International Society for Optics and Photonics},
  pages     = {28--37},
  doi       = {10.1117/12.212752},
  url       = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=998250},
  file      = {:home/baffelli/Library/Tospann, Pirkl, Gruener - 1995 - Multifunction 35-GHz FMCW radar with frequency scanning antenna for synthetic vision applications.pdf:pdf},
  keywords  = {autonomous landing,enhanced situation awareness systems,fmcw radar,frequency scanning radar,high vision radar,vessel traflic radar systems},
}

@InProceedings{Touzi2010,
  author       = {Touzi, Ridha and Hawkins, R. K. and Cote, Stephane},
  title        = {{On the use of transponder measurements for high precision assessment and calibration of polarimetric Radarsat-2}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2010-07},
  volume       = {51},
  publisher    = {IEEE},
  isbn         = {978-1-4244-9565-8},
  pages        = {4847--4850},
  doi          = {10.1109/IGARSS.2010.5651635},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6236138 http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5651635},
  file         = {:home/baffelli/Library/Touzi, Hawkins, Cote - 2010 - On the use of transponder measurements for high precision assessment and calibration of polarimetric Radar.pdf:pdf},
  issn         = {0196-2892},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{Treuhaft1987,
  author       = {R. N. Treuhaft and G. E. Lanyi},
  title        = {{The effect of the dynamic wet troposphere on radio interferometric measurements}},
  journal      = {Radio Science},
  journaltitle = {Radio Science},
  year         = {1987},
  date         = {1987-03},
  volume       = {22},
  month        = {mar},
  pages        = {251--265},
  issn         = {00486604},
  doi          = {10.1029/RS022i002p00251},
  file         = {:home/baffelli/Library/Treuhaft, Lanyi - 1987 - The effect of the dynamic wet troposphere on radio interferometric measurements.pdf:pdf},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Treuhaft1996,
  author       = {Robert N. Treuhaft and S{\o}ren N. Madsen and Mahta Moghaddam and Jakob J. van Zyl},
  title        = {Vegetation characteristics and underlying topography from interferometric radar},
  journal      = {Radio Science},
  journaltitle = {Radio Science},
  year         = {1996},
  date         = {1996-11},
  volume       = {31},
  month        = {nov},
  pages        = {1449--1485},
  issn         = {00486604},
  doi          = {10.1029/96RS01763},
  file         = {:home/baffelli/Library/Treuhaft et al. - 1996 - Vegetation characteristics and underlying topography from interferometric radar.pdf:pdf},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Ulaby1978,
  author        = {Fawwaz Ulaby and Percy Batlivala and Myron Dobson},
  title         = {Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part {I}-Bare Soil},
  journal       = {{IEEE} Transactions on Geoscience Electronics},
  journaltitle  = {IEEE Transactions on Geoscience Electronics},
  year          = {1978},
  date          = {1978-10},
  volume        = {16},
  month         = {oct},
  pages         = {286--295},
  issn          = {03594237},
  doi           = {10.1109/TGE.1978.294586},
  abstract      = {This is the first in a series of two papers on the use of active microwave remote sensing for measuring the moisture content of bare (Part I) and vegetation-covered (Part II) soil. An experimental program was conducted to evaluate the response of the backscattering coefficient to soil moisture content as a means to specify radar system parameters for future airborne and/or spaceborne soil moisture mappers. Particular attention was paid to the effects of surface roughness, and a preliminary examination of the role of soil texture was performed. The results of this investigation confirm the findings of a previous experiment [1] which concluded that the effects of surface roughness can be minimized by operating at a frequency in the neighborhood of 5 GHz over the 7-17° angle of incidence range. The precision with which soil moisture in the surface soil layer can be estimated is comparable to the precision of the ground-truthed estimate. Because the moisture in the surface layer is highly correlated to the subsurface moisture, it was not possible to determine experimentally the effective depth of the layer responsible for the observed radar backscatter.},
  isbn          = {0018-9413},
  keywords      = {Microwave measurements,Moisture measurement,Rough surfaces,Soil moisture,Soil texture,Spaceborne radar,Surface roughness,Surface texture,backscatter,remote sensing},
  mendeley-tags = {Microwave measurements,Moisture measurement,Rough surfaces,Soil moisture,Soil texture,Spaceborne radar,Surface roughness,Surface texture,backscatter,remote sensing},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Ulaby1987,
  author       = {Fawwaz T. Ulaby and Daniel Held and Myron C. Donson and Kyle C. McDonald and Thomas B. A. Senior},
  title        = {Relating Polarization Phase Difference of {SAR} Signals to Scene Properties},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {1987},
  date         = {1987-01},
  volume       = {{GE}-25},
  month        = {jan},
  pages        = {83--92},
  issn         = {0196-2892},
  doi          = {10.1109/TGRS.1987.289784},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4072602},
  abstract     = {This paper examines the statistical behavior of the phase difference AO between the HH-polarized and VV-polarized backscattered signals recorded by an L-band SAR over an agricultural test site in Illinois. Polarization-phase difference ({\~{A}}‚{\^{A}}¿{\~{A}}‚{\^{A}}¿) distributions were generated for about 200 agricultural fields for which ground information had been acquired in conjunction with the SAR mission. For the over-whelming majority of cases, the AX distribution is symmetrical and has a single major lobe centered at the mean value of the disstribution {\~{A}}‚{\^{A}}¿{\~{A}}‚{\^{A}}¿ Whereas the mean AX was found to be close to zero degrees for bare soil, cut vegetation, alfalfa, soybeans, and clover, a different pattern was observed for the corn fields; the mean {\~{A}}‚{\^{A}}¿{\~{A}}‚{\^{A}}¿ increased with increasing incidence angle 0 from about zero at 0 = 150 (near-range of the image) to about 140{\~{A}}‚{\^{A}}° at 0 = 35{\~{A}}‚{\^{A}}°. The explanation proposed for this variation is that the corn canopy, most of whose mass is contained in its vertical stalks, acts like a uniaxial crystal characterized by different velocities of propogation for waves with horizontal and vertical polarization. Thus, it is hypothesized that the observed backscatter is contributed by a combination of propagation delay, forward scatter by the soil surface, and specular bistatic reflection by the stalks. Model calculations based on this assumption were found to be in general agreement with the phase observations.},
  file         = {:home/baffelli/Library/Ulaby et al. - 1987 - Relating polarization phase difference of SAR signals to scene properties.pdf:pdf},
  isbn         = {0196-2892},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Book{Ulaby1982,
  author    = {Ulaby, Fawwaz T and Moore, Richard K and Fung, Adrian K},
  title     = {{Microwave Remote Sensing: Active and Passive Volume II: Radar Remote Sensing and Surface Scattering and Emission Theory}},
  date      = {1982},
  volume    = {2},
  isbn      = {0890061912},
  pages     = {608},
  abstract  = {Microwave Remote Sensing, Active and Passive, Volume II: Radar Remote Sensing and Surface Scattering and Emission Theory},
  booktitle = {Microwave Remote Sensing Active and Passive},
}

@Article{Ulander2004,
  author       = {Ulander, Lars M H},
  title        = {{VHF-Band SAR for Detection of Concealed Ground Targets}},
  journaltitle = {Sensors and Sensor Denial by Camouflage, Concealment and Deception},
  date         = {2004},
  pages        = {19--20},
  abstract     = {Airborne synthetic aperture radar (SAR) operating in the VHF band and used in conjunction with change detection has shown promising results for wide-area surveillance of ground targets. By using VHF-band frequencies, both targets in the open as well as concealed by foliage may be detected in a robust manner. VHF-band SAR is able to detect hidden targets because both foliage attenuation and clutter backscatter is small. The clutter is further suppressed through the use of change detection, thus significantly reducing the false alarms. VHF-band SAR is suitable for change detection since temporal decorrelation is small. An extensive data base of VHF-band SAR and target data was collected during the summer of 2002. The primary goal of this collection was to evaluate VHF-band SAR change detection performance under various operating conditions. In general, the results show that a VHF-band SAR employing change detection can reliably detect truck-sized targets hidden in foliage. However, the detection performance deteriorates under certain operating conditions, e.g. for near-grazing angles.},
  file         = {:home/baffelli/Library/Ulander - 2004 - VHF-Band SAR for Detection of Concealed Ground Targets.pdf:pdf},
}

@Article{Ulmer2017,
  author       = {Ulmer, Franz Georg and Adam, Nico},
  title        = {Characterisation and improvement of the structure function estimation for application in {PSI}},
  journaltitle = {ISPRS Journal of Photogrammetry and Remote Sensing},
  date         = {2017},
  volume       = {128},
  pages        = {40--46},
  issn         = {09242716},
  doi          = {10.1016/j.isprsjprs.2017.03.005},
  abstract     = {Numerical Weather Prediction (NWP) is becoming state of the art for the compensation of atmospheric effects in InSAR and especially in PSI. The structure function (variogram) estimated on the InSAR data and on the NWP data is a required statistical characteristic and very useful in the processing of the data. For example, the structure function (typically the semivariogram) estimated on InSAR data is fundamental for the Kriging of the atmospheric phase screen (APS) based on irregular PSI estimates. The required parameters are the nugget, the range and the slope of the structure function. The practical implementation has shown that the NWP predicted structure function and the InSAR estimated structure function based on the conventional semivariogram equation do not match. Straightforward explanations are wrongly estimated APSs due to an insufficient number of interferograms or hindcasts that fail to capture the turbulent water vapour signal. However, in this paper we explain the effects of noise in interferograms and coarse resolution in the NWP on the conventional structure function estimation resulting in the observed mismatch. In order to avoid the mismatch, an alternative implementation based on wavelets is suggested and demonstrated using real Sentinel-1 data. We show that the wavelet based structure function estimation outperforms the conventional structure function estimation based on a variogram. Application of the proposed structure function alternative based on NWP data are the master selection, the estimation of the effective NWP data resolution, and a statistical consistency check of the estimated InSAR APS. To support the understanding, we demonstrate the effects of noise and resolution using simulated fractals. An application of the proposed wavelet based structure function estimation is the estimation of the effective NWP data resolution, which is demonstrated using the same Sentinel-1 data test case.},
  file         = {:home/baffelli/Library/Ulmer, Adam - 2017 - Characterisation and improvement of the structure function estimation for application in PSI.pdf:pdf},
  keywords     = {DInSAR,Global Positioning System (GPS),Numerical Weather Prediction (NWP),Refraction,Weather Research and Forecasting model (WRF),Zenith Time Delay (ZTD)},
  publisher    = {The Author(s)},
}

@Article{Usai2003,
  author       = {Usai, Stefania},
  title        = {{A least squares database approach for SAR interferometric data}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2003},
  volume       = {41},
  pages        = {753--760},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2003.810675},
  abstract     = {This paper presents a least squares (LS) approach for the retrieval of a temporal deformation sequence from a set of interferometric synthetic aperture radar images. The method uses a database of interferograms spanning different long- and short-term intervals, and by solving all the deformations as a unique LS problem provides a chronologically ordered sequence, i.e., a picture of the development of the deformation pattern in time. The approach is illustrated in detail and discussed with respect to both the results of its application on a case study and to possible alternative methods.},
  file         = {:home/baffelli/Library/Usai - 2003 - A least squares database approach for SAR interferometric data.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Ground displacements,Least squares methods,Synthetic aperture radar (SAR) interferometry},
}

@Article{Vavriv2006,
  author = {Vavriv, D M and Vynogradov, V V and Volkov, V A and Kozhyn, R V and Bezvesilniy, O O and Alekseenkov, S V and Shevchenko, A V and Belikov, A A and Vasilevskiy, M P and Zaikin, D I},
  title  = {{Cost-Effective Airborne SAR}},
  date   = {2006},
  file   = {:home/baffelli/Library/Vavriv et al. - 2006 - Cost-Effective Airborne SAR.pdf:pdf},
}

@Article{Villasenor1993,
  author        = {Villasenor, J D and Fatland, D R and Hinzman, L D},
  title         = {{Change detection on Alaska's North Slope using repeat-pass ERS-1 SAR images}},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  date          = {1993-01},
  volume        = {31},
  pages         = {227--236},
  issn          = {0196-2892},
  doi           = {10.1109/36.210462},
  url           = {http://search.ebscohost.com/login.aspx?direct=true{\&}db=fih{\&}AN=fih-E03AE845-C2C5BED5{\&}site=ehost-live},
  abstract      = {Presents results of radar backscattering intensity comparisons in images of region in and around Imnavait watershed and Toolik Lake. Concludes that radar backscattering changes are due largely to changes in soil and vegetation liquid water content induced by freeze/thaw events (Copyright applies to all Abstracts.)},
  keywords      = {50 mm,Alaska,Area measurement,Backscattering,Botany,Brooks Range foothills,C-band,Correlation,ERS-1 SAR images,FROZEN ground,GEOPHYSICAL surveys,Geomorphology,IMAGE processing,LIFE sciences,MATTER -- Properties,North Slope,RADAR cross sections,REMOTE sensing,Radar detection,SOIL science,SPACE photography,SYNTHETIC aperture radar,Satellites,Soil,Spaceborne radar,Surfaces,USA,United States,Vegetation mapping,Wavelength measurement,backscatter,difference images,geophysical techniques,geophysics,hill-slope orientation,hydrological techniques,hydrology,ice,land surface,measurement,microwave,moisture,radar cross section,radar imaging,remote sensing,remote sensing by radar,rivers,synthetic aperture radar,technique,temporal changes,vegetation,water content},
  mendeley-tags = {50 mm,Alaska,Area measurement,Brooks Range foothills,C-band,ERS-1 SAR images,North Slope,Radar detection,Satellites,Soil,Spaceborne radar,USA,United States,Vegetation mapping,Wavelength measurement,backscatter,difference images,geophysical techniques,geophysics,hill-slope orientation,hydrological techniques,hydrology,ice,land surface,measurement,microwave,moisture,radar cross section,radar imaging,remote sensing,remote sensing by radar,rivers,synthetic aperture radar,technique,temporal changes,vegetation,water content},
}

@Article{Voytenko2015,
  author       = {Denis Voytenko and Timothy H. Dixon and Ian M. Howat and Noel Gourmelen and Chad Lembke and Charles L. Werner and Santiago De La Pe{\~{n}}a and Björn Oddsson},
  title        = {Multi-year observations of {B}rei{\dh}amerkurjökull, a marine-terminating glacier in southeastern {I}celand, using terrestrial radar interferometry},
  journal      = {Journal of Glaciology},
  journaltitle = {Journal of Glaciology},
  year         = {2015},
  date         = {2015},
  volume       = {61},
  pages        = {42--54},
  issn         = {00221430},
  doi          = {10.3189/2015JoG14J099},
  abstract     = {Terrestrial radar interferometry (TRI) is a new technique for studying ice motion and volume change of glaciers. TRI is especially useful for temporally and spatially dense measurements of highly dynamic glacial termini. We conducted a TRI survey of Breiðamerkurj{\"{o}}kull, a marine terminating glacier in Iceland, imaging its terminus near the end of the melt season in 2011, 2012 and 2013. The ice velocities were as high as 5md{\_}1, with the fastest velocities near the calving front. Retreat of the glacier over the 3 year observation period was accompanied by strong embayment formation. Iceberg tracking with the radar shows high current velocities near the embayment, probably indicating strong meltwater outflow and mixing with relatively warm lagoon water.},
  file         = {:home/baffelli/Library/Voytenko et al. - 2015 - Multi-year observations of Breioamerkurjokull, a marine-terminating glacier in southeastern Iceland, using terr.pdf:pdf},
  keywords     = {Glacier flow,Glaciological instruments and methods,Ice/ocean interactions,Remote sensing},
  publisher    = {Cambridge University Press ({CUP})},
}

@InProceedings{Voytenko2012,
  author       = {Denis Voytenko and Timothy H. Dixon and Charles Werner and Noel Gourmelen and Ian M. Howat and Phaedra C. Tinder and Andrew Hooper},
  title        = {Monitoring a glacier in southeastern {Iceland} with the portable Terrestrial Radar Interferometer},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2012},
  date         = {2012},
  publisher    = {{IEEE}},
  month        = {jul},
  isbn         = {9781467311595},
  pages        = {3230--3232},
  doi          = {10.1109/IGARSS.2012.6350736},
  file         = {:home/baffelli/Library/Voytenko et al. - 2012 - Monitoring a glacier in southeastern Iceland with the portable Terrestrial Radar Interferometer.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {geodesy,ice,radar interferometry},
}

@Article{Wahl1994,
  author        = {Wahl, D E and Eichel, P H and Ghiglia, D C and {Jakowatz C.V.}, Jr.},
  title         = {{Phase gradient autofocus-a robust tool for high resolution SAR phase correction}},
  journaltitle  = {Aerospace and Electronic Systems, IEEE Transactions on},
  date          = {1994-07},
  volume        = {30},
  pages         = {827--835},
  issn          = {0018-9251},
  doi           = {10.1109/7.303752},
  abstract      = {The phase gradient autofocus (PGA) technique for phase error correction of spotlight mode synthetic aperture radar (SAR) imagery is examined carefully in the context of four fundamental signal processing steps that constitute the algorithm. We demonstrate that excellent results over a wide variety of scene content, and phase error function structure are obtained if and only if all of these steps are included in the processing. Finally, we show that the computational demands of the fun PGA algorithm do not represent a large fraction of the total image formation problem, when mid to large size images are involved},
  isbn          = {0018-9251},
  keywords      = {Diffraction,Electronics packaging,Image resolution,Image restoration,Layout,Motion measurement,Parameter estimation,Robustness,SAR,SAR phase correction,Signal processing algorithms,circular shifting,computational complexity,computational demands,error correction,focusing,image processing,image resolution,parameter estimation,phase error correction,phase error function structure,phase gradient autofocus,phase gradient estimation,signal processing,spotlight mode synthetic aperture radar,synthetic aperture radar,total image formation,windowing},
  mendeley-tags = {Diffraction,Electronics packaging,Image restoration,Layout,Motion measurement,Parameter estimation,Robustness,SAR,SAR phase correction,Signal processing algorithms,circular shifting,computational complexity,computational demands,error correction,focusing,image processing,image resolution,phase error correction,phase error function structure,phase gradient autofocus,phase gradient estimation,signal processing,spotlight mode synthetic aperture radar,synthetic aperture radar,total image formation,windowing},
}

@Article{Walker1980,
  author       = {Walker, Jack L.},
  title        = {{Range-doppler imaging of rotating objects}},
  journaltitle = {IEEE Transactions on Aerospace and Electronic Systems},
  date         = {1980},
  volume       = {AES-16},
  pages        = {23--52},
  issn         = {00189251},
  doi          = {10.1109/TAES.1980.308875},
  abstract     = {During the integration time required to obtain fine Dopplerfrequency resolution in a range-Doppler imaging radar, a point on a rotating object may move through several range and Doppler resolution cells and produce a smeared image. This motion can be compensated by storing the appropriately processed return pulse, and the angular coordinates are determined by the angular coordinates of the radar antenna. The resulting stored data represents the three-dimensional Fourier transform of the object reflectivity density, and hence can be processed by an inverse Fourier transformation. Also included is an analysis of the three-dimensional radar/object geometry with separate source and receiver locations. The effects of various system aberrations are investigated and experimental results from a microwave test range which demonstrate the image improvement are presented.},
  file         = {:home/baffelli/Library/Walker - 1980 - Range-doppler imaging of rotating objects.pdf:pdf},
  isbn         = {0018-9251 VO - AES-16},
}

@Article{Wang2009,
  author       = {Wang, ZB and Moya, JC},
  title        = {{Range-Doppler image processing in linear FMCW radar and FPGA based real-time implementation}},
  journaltitle = {Journal of {\ldots}},
  date         = {2009},
  volume       = {6},
  pages        = {55--59},
  url          = {http://www.airitilibrary.com/Publication/alDetailedMesh?docid=15487709-200904-6-4-55-59-a},
  file         = {:home/baffelli/Library/Wang, Moya - 2009 - Range-Doppler image processing in linear FMCW radar and FPGA based real-time implementation.pdf:pdf},
  keywords     = {doppler,fpga implementation,integration of several frequency,lfmcw radar,process,range-doppler images can be,real-time system,sweepings,used later for},
}

@InProceedings{Wegmueller2012,
  author    = {Wegm{\"{u}}ller, Urs and Frey, Othmar and Werner, Charles L.},
  title     = {Point Density Reduction in Persistent Scatterer Interferometry},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  year      = {2012},
  date      = {2012},
  pages     = {673--676},
  url       = {http://ieeexplore.ieee.org/document/6217159/},
  file      = {:home/baffelli/Library/Wegm{"{u}}ller, Frey, Werner - 2012 - Point Density Reduction in Persistent Scatterer Interferometry.pdf:pdf},
}

@InProceedings{Wegmuller2000,
  author    = {Wegm{\"{u}}ller, Urs and Strozzi, Tazio and Tosi, Luigi},
  title     = {{Differential SAR interferometry for land subsidence monitoring: methodology and examples}},
  booktitle = {Sixth international symposium on Land subsidence},
  date      = {2000},
  publisher = {C.N.R., Gruppo nazionale per la difesa dalle catastrofi idrogeologiche},
  pages     = {93--105},
}

@Article{Wegmuller1995,
  author       = {Wegm{\"{u}}ller, Urs and Wegm{\"{u}}ller, Urs and Werner, Charles L. and Werner, Charles L.},
  title        = {{SAR interferometric signatures of forest}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {1995},
  volume       = {33},
  pages        = {1153--1161},
  issn         = {01962892},
  doi          = {10.1109/36.469479},
  abstract     = {he potential of SAR interferometry for forest map- ping and monitoring is discussed. It is shown that forest can clearly be discriminated from other land categories. Furthermore it is possible to distinguish a number of forest types. The pre- sented approach is based on the SAR interferometric correlation and the backscatter intensities using ERS-1 SAR repeat-pass data. Baseline, time interval, and seasonal dependences were analyzed, substantiating a wide applicability of the approach. Data over an Alaskan test site were used to extend the results found over temperate forest to boreal forest and to demonstrate the potential of the described technique over remote areas. In addition, repeat-pass SAR interferometry was found to be particularly sensitive to change. Examples for the recognition of freezing, mechanical cultivation of agricultural fields, and canopy growth are shown. I.},
  file         = {:home/baffelli/Library/Wegm{"{u}}ller et al. - 1995 - SAR interferometric signatures of forest.pdf:pdf},
  isbn         = {0196-2892},
}

@InProceedings{Werner2008,
  author        = {Werner, Charles and Strozzi, Tazio and Wiesmann, Andreas and Wegm{\"{u}}ller, Urs},
  title         = {A Real-Aperture Radar for Ground-Based Differential Interferometry},
  booktitle     = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year          = {2008},
  date          = {2008-07},
  publisher     = {{IEEE}},
  isbn          = {9781424428083},
  pages         = {210--213},
  doi           = {10.1109/IGARSS.2008.4779320},
  abstract      = {Satellite interferometry has been used extensively for ground-motion monitoring with good success. In the case of landslides, for example, space-borne SAR interferometry has a good potential to get an overview on the slope stability. The role of a space-borne INSAR as an element in a landslide or rock fall warning system is constrained by the specific space-borne SAR imaging geometry, the typical multiple-week repeat-interval, and uncertainties in the data availability. Most of these limitations can be overcome with an in-situ radar imaging system. GAMMA has developed a portable radar interferometer that utilizes real-aperture antennas to obtain high azimuth resolution. Images are acquired line by line while rotating the transmitting and receiving antennas about a vertical axis. Phase differences between successive images acquired from the same location are used to determine line-of-sight displacements. The instrument operates at 17.2 GHz and has measurement sensitivity better than 1 mm. The instrument uses two receiving antennas with a short baseline to form an interferometer. Phase differences between simultaneous acquisitions by these antennas are used to calculate the precise look angle relative to the baseline, permitting derivation of the surface topography. Expected statistical noise in the height measurements is on the order of 1 meter. In this contribution the design, measurement principles and characteristics of GAMMA's Portable Radar Interferometer (GPRI) are presented.},
  journal       = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  journaltitle  = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords      = {Antenna measurements,GAMMA,GAMMA Portable Radar Interferometer,Glacier,Instruments,Interferometry,Landslide,Monitoring,RAR,Radar Interferometer,Radar antennas,Radari interferomete,Satellites,Spaceborne radar,Surface topography,Terrain factors,antennas,frequency 17.2 GHz,geomorphology,geophysical equipment,glacier,ground-based differential interferometry,height measurements,image acquisition,in-situ radar imaging system,l,landslide,landslides,line-of-sight displacements,phase differences,photogrammetry systems,radar imaging,radar interferometry,real-aperture radar,receiving antennas,remote sensing by radar,rock fall warning system,rocks,slope stability,space-borne INSAR,space-borne SAR interferometry,synthetic aperture radar},
  mendeley-tags = {Antenna measurements,GAMMA,GAMMA Portable Radar Interferometer,Instruments,Interferometry,Monitoring,RAR,Radar Interferometer,Radar antennas,Satellites,Spaceborne radar,Surface topography,Terrain factors,antennas,frequency 17.2 GHz,geomorphology,geophysical equipment,glacier,ground-based differential interferometry,height measurements,image acquisition,in-situ radar imaging system,l,landslide,landslides,line-of-sight displacements,phase differences,photogrammetry systems,radar imaging,radar interferometry,real-aperture radar,receiving antennas,remote sensing by radar,rock fall warning system,rocks,slope stability,space-borne INSAR,space-borne SAR interferometry,synthetic aperture radar},
}

@InProceedings{Werner2003,
  author       = {C. Werner and U. Wegmüller and T. Strozzi and A. Wiesmann},
  title        = {{Interferometric point target analysis for deformation mapping}},
  booktitle    = {Proceeding of the {IEEE} International Geoscience and Remote Sensing Symposium},
  date         = {2003},
  volume       = {7},
  publisher    = {{IEEE}},
  isbn         = {0-7803-7929-2},
  pages        = {4362--4364},
  doi          = {10.1109/IGARSS.2003.1295516},
  abstract     = {Interferometric Point Target Analysis (IPTA) is a method to exploit the temporal and spatial characteristics of interferometric signatures collected from point targets to accurately map surface deformation histories, terrain heights, and relative atmospheric path delays. In this contribution the IPTA concept is introduced, including the point selection criteria, the phase model and the iterative improvement of the model parameters. Intermediate and final results of an IPTA example using a stack of ERS-1 and ERS-2 data, confirm the validity of the concept and indicate a high accuracy of the resulting products.},
  file         = {:home/baffelli/Library/Werner et al. - 2003 - Interferometric point target analysis for deformation mapping.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  keywords     = {atmospheric path,interferometric point target analysis,ipta,subsidence,surface deformation,terrain heights},
}

@InProceedings{werner_gpri_2012,
  author    = {Charles L. Werner and Andreas Wiesmann and Tazio Strozzi and Andrew Kos and Rafael Caduff and Urs Wegm{\"{u}}ller},
  title     = {The {GPRI} multi-mode differential interferometric radar for ground-based observations},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date      = {2012},
  publisher = {VDE},
  isbn      = {VO -},
  pages     = {304--307},
  url       = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06217065},
  abstract  = {We describe the Gamma GPRI radar instrument and present examples using the different observational strategies based on differential interferometry to measure both slow and rapid motions along the line of sight. The measurment sensitivity of the GPRI instrument along the line of sight (LOS) is better than 0.20 mm. Using this capability is possible to generate DEMs, and measure mm-scale deformation on short and longer time-scales. Ground-based interferometric observations are complementary to spaceborne or airborne SAR based measurements because they can be acquired continuously and can be processed to mitigate the effects of temporal decorrelation and atmospheric phase variability.},
  file      = {:home/baffelli/Library/Werner et al. - 2012 - The GPRI multi-mode differential interferometric radar for ground-based observations.pdf:pdf},
}

@Article{Whitt1990,
  author       = {Whitt, MW and Ulaby, FT},
  title        = {{A polarimetric radar calibration technique with insensitivity to target orientation}},
  journaltitle = {Radio science},
  date         = {1990},
  volume       = {25},
  pages        = {1137--1143},
  issn         = {1944799X},
  doi          = {10.1029/RS025i006p01137},
  abstract     = {A convenient polarimetric radar calibration technique is presented and used to calibrate an X band polarimetric radar. The technique uses a distortion matrix model for the errors introduced by the transmitter and receiver, and it is applicable to any polarimetric radar system where the concept of an invariant distortion matrix is valid. A sphere and two arbitrary passive targets are used to calibrate the radar with respect to the unknown polarization transmitted when the v-polarized channel is energized. The unknown transmitted polarization is then recovered by measuring any nondepolar- izing target. Because knowledge of the scattering matrices for the two arbitrary targets is not required, the technique is insensitive to errors in the orientation of calibration targets. Experimental results are presented, and they indicate magnitude and relative phase measurement errors of less than 0.2 dB and 2 {\o}, respectively.},
  keywords     = {doi:10.1029/RS025i006p01137,http://dx.doi.org/10.1029/RS025i006p01137},
}

@Article{Wicks2006,
  author       = {Wicks, M C and Rangaswamy, M and Adve, R and Hale, T B},
  title        = {{Space-time adaptive processing: a knowledge-based perspective for airborne radar}},
  journaltitle = {IEEE Signal Processing Magazine},
  date         = {2006},
  volume       = {23},
  pages        = {51--65},
  issn         = {1053-5888},
  doi          = {10.1109/MSP.2006.1593337},
  url          = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1593337},
  abstract     = {This article provides a brief review of radar space-time adaptive processing (STAP) from its inception to state-of-the art developments. The topic is treated from both intuitive and theoretical aspects. A key requirement of STAP is knowledge of the spectral characteristics underlying the interference scenario of interest. Additional issues of importance in STAP include the computational cost of the adaptive algorithm as well as the ability to maintain a constant false alarm rate (CFAR) over widely varying interference statistics. This article addresses these topics, developing the need for a knowledge-based (KB) perspective. The focus here is on signal processing for radar systems using multiple antenna elements that coherently process multiple pulses. An adaptive array of spatially distributed sensors, which processes multiple temporal snapshots, overcomes the directivity and resolution limitations of a single sensor.},
  file         = {:home/baffelli/Library/Wicks et al. - 2006 - Space-time adaptive processing a knowledge-based perspective for airborne radar.pdf:pdf},
  isbn         = {1053-5888},
}

@InCollection{Wieczorek2009,
  author    = {Wieczorek, Gf and Snyder, Jb},
  title     = {{Monitoring slope movements}},
  booktitle = {Geololgical Monitoring},
  date      = {2009},
  pages     = {245--271},
  doi       = {10.1130/2009.monitoring(11).},
  url       = {http://books.google.com/books?hl=en{\&}lr={\&}id=qHrF2uqSlUEC{\&}oi=fnd{\&}pg=PA245{\&}dq=Monitoring+slope+movements{\&}ots=SIoBtwLIw-{\&}sig=79UQVfztbfargocGQJnmlJvyevE},
}

@Article{WiesmannAndreas;Gruener2011,
  author       = {{Wiesmann, Andreas; Gruener}, Ueli},
  title        = {{Radar-Interferometrie im Einsatz f{\"{u}}r die Stabilit{\"{a}}ts{\"{u}}berwachung von grossfl{\"{a}}chigen Felsw{\"{a}}nden}},
  journaltitle = {Swiss bulletin f{\"{u}}r angewandte Geologie},
  date         = {2011},
  volume       = {1},
  doi          = {10.5169/seals-327741},
  file         = {:home/baffelli/Library/Wiesmann, Andreas Gruener - 2011 - Radar-Interferometrie im Einsatz f{"{u}}r die Stabilit{"{a}}ts{"{u}}berwachung von grossfl{"{a}}chigen Felsw{"{a}}nden.pdf:pdf},
  keywords     = {radar interferometry,rock movement,terrestrial radar},
}

@Article{Greene2012,
  author    = {{William H. Greene}},
  title     = {{Econometric analysis}},
  date      = {2012},
  volume    = {97},
  pages     = {1189},
  doi       = {10.2307/2291031},
  edition   = {7},
  file      = {:home/baffelli/Library/William H. Greene - 2012 - Econometric analysis.pdf:pdf},
  isbn      = {978-0-273-75356-8},
  publisher = {Pearson},
}

@InBook{Greene2010,
  author     = {William H. Greene},
  title      = {The Generalized Regression Model and Heteroscedasticity},
  booktitle  = {Econometric Analysis},
  year       = {20},
  date       = {2010},
  bookauthor = {William H. Greene},
  edition    = {7},
  publisher  = {Pearson},
  isbn       = {9780273753568},
  chapter    = {9},
  file       = {:home/baffelli/Library/William H. Greene - 2001 - The Generalized Regression Model and Heteroscedasticity.pdf:pdf},
}

@Article{Williams1998,
  author       = {Simon Williams and Yehuda Bock and Peng Fang},
  title        = {Integrated satellite interferometry: Tropospheric noise, {GPS} estimates and implications for interferometric synthetic aperture radar products},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {1998},
  date         = {1998-11},
  volume       = {103},
  month        = {nov},
  pages        = {27051--27067},
  issn         = {01480227},
  doi          = {10.1029/98JB02794},
  file         = {:home/baffelli/Library/Williams, Bock, Fang - 1998 - Integrated satellite interferometry Tropospheric noise, GPS estimates and implications for interferometric.pdf:pdf},
  keywords     = {doi:10.1029/98JB02794,http://dx.doi.org/10.1029/98JB02794},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Xiong2007,
  author       = {Xiong, Weizu},
  title        = {{Polarimetric Calibration Using a Genetic Algorithm}},
  journaltitle = {{IEEE} Geoscience and Remote Sensing Letters},
  date         = {2007},
  volume       = {4},
  pages        = {421--425},
  issn         = {1545-598X},
  doi          = {10.1109/LGRS.2007.895725},
}

@Article{Yamaguchi2008,
  author = {Yamaguchi, Jun and Agency, Exploration and Kimura, Toshiyoshi and Agency, Exploration and Takano, Toshiaki and Takamura, Tamio and Nakanishi, Yuji and Takenaka, Hideaki and Agency, Exploration and Space, Tsukuba and Shape, Modulation and Range, Observation and Resolution, Temporal and Gain, Antenna and Beamwidth, Antenna and Resolution, Range and Velocity, Doppler and Amp, Solid-state and Cassegrain, Bistatic},
  title  = {GROUND-BASED W-BAND FMCW CPR FOR COORDINATED OBSERVATION WITH SPACEBOURNE CPRS},
  date   = {2008},
  file   = {:home/baffelli/Library/Yamaguchi et al. - 2008 - GROUND-BASED W-BAND FMCW CPR FOR COORDINATED OBSERVATION WITH SPACEBOURNE CPRS.pdf:pdf},
}

@Article{Yang2009,
  author       = {Yang, Junjun and Nie, Jiacai},
  title        = {{Doppler Effect of Mechanical Waves and Light}},
  journaltitle = {System},
  date         = {2009},
  volume       = {2},
  pages        = {1--3},
  file         = {:home/baffelli/Library/Yang, Nie - 2009 - Doppler Effect of Mechanical Waves and Light.pdf:pdf},
  keywords     = {doppler effect,light,sound,time dilation,wave vector},
}

@InProceedings{Yang2014,
  author    = {Yang, Shang-Te and Ling, Hao},
  title     = {Combining a frequency-scanned antenna and a short-pulse radar for {2-D} imaging},
  booktitle = {Proceedings of the {IEEE} International Symposium on Antennas and Propagation},
  year      = {2014},
  date      = {2014-07},
  publisher = {{IEEE}},
  month     = {jul},
  pages     = {137--138},
  doi       = {10.1109/APS.2014.6904400},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6904400},
  file      = {:home/baffelli/Library/Yang, Ling - 2014 - Combining a frequency-scanned antenna and a short-pulse radar for 2-D imaging.pdf:pdf},
}

@InProceedings{Yang2012,
  author    = {Yang, Shang-Te and Ling, Hao},
  title     = {{Range-azimuth tracking of humans using a microstrip leaky wave antenna}},
  booktitle = {Proceedings of the IEEE International Symposium on Antennas and Propagation},
  date      = {2012-07},
  publisher = {IEEE},
  isbn      = {978-1-4673-0462-7},
  pages     = {1--2},
  doi       = {10.1109/APS.2012.6347963},
  url       = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6347963},
  file      = {:home/baffelli/Library/Yang, Ling - 2012 - Range-azimuth tracking of humans using a microstrip leaky wave antenna.pdf:pdf},
}

@Article{Yi2010,
  author    = {Yi, Liang and Hongxian, Wang and Long, Zhang and Zheng, B A O},
  title     = {{An approach to forward looking FMCW radar imaging based on two-dimensional Chirp-Z transform}},
  journal   = {Science China Information Sciences},
  year      = {2010},
  date      = {2010},
  volume    = {53},
  month     = {jul},
  pages     = {1653--1665},
  doi       = {10.1007/s11432-010-4035-4},
  file      = {:home/baffelli/Library/Yi et al. - 2010 - An approach to forward looking FMCW radar imaging based on two-dimensional Chirp-Z transform.pdf:pdf},
  keywords  = {chirp-z transform,fmcw,forward looking radar imaging},
  publisher = {Springer Nature},
}

@Book{Yin2017,
  author = {Yin, Arbanas Yueping and Sassa, Kyoji and Technology, Landslide},
  title  = {{Advancing Culture of Living with Landslides}},
  date   = {2017},
  volume = {3},
  isbn   = {978-3-319-53500-5},
  doi    = {10.1007/978-3-319-59469-9},
  file   = {:home/baffelli/Library/Yin, Sassa, Technology - 2017 - Advancing Culture of Living with Landslides.pdf:pdf},
  issn   = {978-3-319-53484-8},
}

@InProceedings{Yitayew2014,
  author    = {Yitayew, Temesgen Gebrie},
  title     = {High resolution three-dimensional imaging of sea ice using ground- based tomographic {SAR} data},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  date      = {2014},
  isbn      = {9783800736072},
  pages     = {2--5},
  file      = {:home/baffelli/Library/Yitayew - 2014 - High resolution three-dimensional imaging of sea ice using ground- based tomographic SAR data.pdf:pdf},
}

@Misc{Zawadzki1973,
  author    = {Zawadzki, Isztar},
  title     = {{Statistical properties of precipitation patterns}},
  date      = {1973},
  doi       = {10.1175/1520-0450(1973)012<0459:SPOPP>2.0.CO;2},
  abstract  = {Space and time autocorrelation functions are defined for the precipitation process on a horizontal plane. An optical device was designed and used to measure these functions as well as the mean, the mean square, and the variance of the rainfall rate for a time sequence of precipitation patterns of a widespread convective storm. The input data were radar PPI records stored on film in which the transmittance was adjusted to be proportional to rainfall rate.},
  booktitle = {Journal of Applied Meteorology},
  file      = {:home/baffelli/Library/Zawadzki - 1973 - Statistical properties of precipitation patterns.pdf:pdf},
  isbn      = {0021-8952},
  issn      = {0021-8952},
  keywords  = {statistical methods},
  pages     = {459--472},
  volume    = {12},
}

@Article{Goldstein1986,
  author       = {Howard A. Zebker and Richard M. Goldstein},
  title        = {Topographic mapping from interferometric synthetic aperture radar observations},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research},
  year         = {1986},
  date         = {1986},
  volume       = {91},
  pages        = {4993},
  issn         = {0148-0227},
  doi          = {10.1029/JB091iB05p04993},
  file         = {:home/baffelli/Library/Zebker, Goldstein - 1986 - Topographic mapping from interferometric synthetic aperture radar observations.pdf:pdf},
  keywords     = {doi:10.,http://dx.doi.org/10.1029/JB091iB05p04993},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Zebker1994,
  author       = {Howard A. Zebker and Paul A. Rosen and Richard M. Goldstein and Andrew Gabriel and Charles L. Werner},
  title        = {On the derivation of coseismic displacement fields using differential radar interferometry: The {L}anders earthquake},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {1994},
  date         = {1994},
  volume       = {99},
  month        = {oct},
  pages        = {19617--19634},
  issn         = {0148-0227},
  doi          = {10.1029/94JB01179},
  abstract     = {We present a map of the coseismic displacement field resulting from the Landers, California, June 28, 1992, earthquake derived using data acquired from an orbiting high-resolution radar system. We achieve results more accurate than previous space studies and similar in accuracy to those obtained by conventional field survey techniques. Data from the ERS 1 synthetic aperture radar instrument acquired in April, July, and August 1992 are used to generate a high-resolution, wide area map of the displacements. The data represent the motion in the direction of the radar line of sight to centimeter level precision of each 30-m resolution element in a 113 km by 90 km image. Our coseismic displacement contour map gives a lobed pattern consistent with theoretical models of the displacement field from the earthquake. Fine structure observed as displacement tiling in regions several kilometers from the fault appears to be the result of local surface fracturing. Comparison of these data with Global Positioning System and electronic distance measurement survey data yield a correlation of 0.96; thus the radar measurements are a means to extend the point measurements acquired by traditional techniques to an area map format. The technique we use is (1) more automatic, (2) more precise, and (3) better validated than previous similar applications of differential radar interferometry. Since we require only remotely sensed satellite data with no additional requirements for ancillary information, the technique is well suited for global seismic monitoring and analysis.},
  isbn         = {0148-0227},
  keywords     = {http://dx.doi.org/10.1029/94JB01179, doi:10.1029/9},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Zebker1987,
  author       = {Zebker, Howard A and van Zyl, Jakob J. and Held, Daniel N},
  title        = {{Imaging radar polarimetry from wave synthesis}},
  journaltitle = {Journal of Geophysical Research},
  date         = {1987},
  volume       = {92},
  pages        = {683},
  issn         = {0148-0227},
  doi          = {10.1029/JB092iB01p00683},
  abstract     = {An imaging radar polarimeter measures the dependence of radar backscatter intensity and relative phase as a function of both the transmitted and received wave polarization states},
}

@Article{Zebker1997,
  author       = {Howard A. Zebker and Paul A. Rosen and Scott Hensley},
  title        = {Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps},
  journal      = {Journal of Geophysical Research: Solid Earth},
  journaltitle = {Journal of Geophysical Research: Solid Earth},
  year         = {1997},
  date         = {1997},
  volume       = {102},
  month        = {apr},
  pages        = {7547--7563},
  issn         = {01480227},
  doi          = {10.1029/96JB03804},
  file         = {:home/baffelli/Library/Zebker, Rosen, Hensley - 1997 - Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps.pdf:pdf},
  keywords     = {http://dx.doi.org/10.1029/96JB03804, doi:10.1029/9},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Zebker1992,
  author        = {H.A. Zebker and J. Villasenor},
  title         = {Decorrelation in interferometric radar echoes},
  journal       = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle  = {IEEE Transactions on Geoscience and Remote Sensing},
  year          = {1992},
  date          = {1992-09},
  volume        = {30},
  pages         = {950--959},
  issn          = {01962892},
  doi           = {10.1109/36.175330},
  url           = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=175330},
  abstract      = {A radar interferometric technique for topographic mapping of$\backslash$nsurfaces, implemented utilizing a single synthetic aperture radar (SAR)$\backslash$nsystem in a nearly repeating orbit, is discussed. The authors$\backslash$ncharacterize the various sources contributing to the echo correlation$\backslash$nstatistics, and isolate the term which most closely describes surficial$\backslash$nchange. They then examine the application of this approach to$\backslash$ntopographic mapping of vegetated surfaces which may be expected to$\backslash$npossess varying backscatter over time. It is found that there is$\backslash$ndecorrelation increasing with time but that digital terrain model$\backslash$ngeneration remains feasible. The authors present such a map of a$\backslash$nforested area in Oregon which also includes some nearly unvegetated lava$\backslash$nflows. Such a technique could provide a global digital terrain map},
  file          = {:home/baffelli/Library/Zebker, Villasenor - 1992 - Decorrelation in interferometric radar echoes.pdf:pdf},
  isbn          = {0196-2892},
  keywords      = {Digital elevation models,Noise level,Oregon,Propulsion,Radar antennas,Space technology,Spaceborne radar,Surface topography,Terrain mapping,United States,backscatter,decorrelation,digital terrain model generation,echo correlation statistics,forested area,geophysical techniques,global digital terrain map,interferometric radar echoes,radar interferometric technique,radiowave interferometry,remote sensing,remote sensing by radar,single synthetic aperture radar,surficial change,synthetic aperture radar,topographic mapping,topography (Earth),unvegetated lava flows,vegetated surfaces},
  mendeley-tags = {Digital elevation models,Noise level,Oregon,Propulsion,Radar antennas,Space technology,Spaceborne radar,Surface topography,Terrain mapping,United States,backscatter,decorrelation,digital terrain model generation,echo correlation statistics,forested area,geophysical techniques,global digital terrain map,interferometric radar echoes,radar interferometric technique,radiowave interferometry,remote sensing,remote sensing by radar,single synthetic aperture radar,surficial change,synthetic aperture radar,topographic mapping,topography (Earth),unvegetated lava flows,vegetated surfaces},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Zha2015,
  author       = {Zha, Yuebo and Zhang, Yin and Huang, Yulin and Yang, Jianyu},
  title        = {{Bayesian Angular Superresolution Algorithm for Real-Aperture Imaging in Forward-Looking Radar}},
  journaltitle = {Information},
  date         = {2015},
  volume       = {6},
  pages        = {650--668},
  issn         = {2078-2489},
  doi          = {10.3390/info6040650},
  url          = {http://www.mdpi.com/2078-2489/6/4/650/},
  file         = {:home/baffelli/Library/Zha et al. - 2015 - Bayesian Angular Superresolution Algorithm for Real-Aperture Imaging in Forward-Looking Radar.pdf:pdf},
  keywords     = {angular superresolution,bayesian framework,constraint,maximum a posteriori,real aperture radar,sparse},
}

@Misc{Zhang2011,
  author        = {Zhang, Lamei and Zou, Bin and Wenyan, Tang},
  title         = {{Polarimetric Interferometric Eigenvalue Similarity Parameter and Its Application in Target Detection}},
  date          = {2011},
  doi           = {10.1109/LGRS.2011.2116765},
  abstract      = {Polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) combines SAR polarimetry and SAR interferometry and is much more sensitive to the distribution of orientated scatterers compared with polarimetric or interferometric data alone. The polarimetric similarity parameter is an efficient parameter to analyze target characteristics using the similarity between a target and the canonical target. In this letter, the polarimetric interferometric eigenvalue similarity parameter (PIESP) is proposed based on the similarity between two polarimetric SAR images obtained by two interferometric antennas. The PIESP is defined by the eigenvalues of two polarimetric coherence matrices in the PolInSAR system, and the eigenvalues of polarimetric coherence matrix are independent on the target orientation angle; therefore, the PIESP is rotation invariant. PolInSAR systems use two antennas to measure the same ground area with slightly different image geometry. Thus, the PIESP can be used to distinguish the target based on coherence and similarity. Then, the target detection method using the PIESP is implemented with the DLR experimental SAR L-band full polarized image of the Oberpfaffenhofen test site of Germany obtained on September 30, 2000. The results confirmed that the proposed model is accurate and effective for the detection and the analysis of buildings in urban areas.},
  booktitle     = {Geoscience and Remote Sensing Letters, IEEE},
  isbn          = {1545-598X VO - 8},
  issn          = {1545-598X},
  keywords      = {Buildings,Coherence,Covariance matrix,Eigenvalues and eigenfunctions,Germany,Matrix decomposition,Oberpfaffenhofen test site,Object detection,PolInSAR system,Polarimetric interferometric eigenvalue similarity,Polarimetric synthetic aperture radar (SAR) interf,Radar antennas,Radar detection,SAR L-band full polarized imaging,SAR interferometry,SAR polarimetry,eigenvalues and eigenfunctions,image geometry,interferometric antennas,object detection,polarimetric coherence matrices,polarimetric interferometric eigenvalue similarity,radar antennas,radar detection,radar imaging,radar interferometry,radar polarimetry,synthetic aperture radar,target detection,urban areas},
  mendeley-tags = {Buildings,Coherence,Covariance matrix,Eigenvalues and eigenfunctions,Germany,Matrix decomposition,Oberpfaffenhofen test site,PolInSAR system,Polarimetric interferometric eigenvalue similarity,Polarimetric synthetic aperture radar (SAR) interf,Radar antennas,Radar detection,SAR L-band full polarized imaging,SAR interferometry,SAR polarimetry,image geometry,interferometric antennas,object detection,polarimetric coherence matrices,polarimetric interferometric eigenvalue similarity,radar imaging,radar interferometry,radar polarimetry,synthetic aperture radar,target detection,urban areas},
  pages         = {819--823},
  volume        = {8},
}

@Article{Zhang2014,
  author   = {Zhang, Siqian and Kuang, Gangyao},
  title    = {{Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm}},
  journal  = {IEEE Geoscience and Remote Sensing Letters},
  date     = {2014},
  volume   = {9243},
  pages    = {924312},
  doi      = {10.1117/12.2067025},
  url      = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2067025},
  file     = {:home/baffelli/Library/Zhang, Kuang - 2014 - Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm.pdf:pdf;:home/baffelli/Library/Zhang, Kuang - 2014 - Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm(2).pdf:pdf},
  keywords = {downward-looking,multiple signal classification,sar,three-dimensional spatial smoothing},
}

@Article{Zhou2004,
  author       = {Zheng-Shu Zhou and W.-M. Boerner and M. Sato},
  title        = {Development of a ground-based polarimetric broadband {SAR} system for noninvasive ground-truth validation in vegetation monitoring},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2004},
  date         = {2004},
  volume       = {42},
  month        = {sep},
  pages        = {1803--1810},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2004.832248},
  abstract     = {We have developed a ground-based polarimetric broadband synthetic aperture radar (SAR) system for noninvasive ground-truth validation in polarimetric SAR remote sensing of terrestrial vegetation cover. This system consists of a vector network analyzer, one dual-polarized antenna, and an antenna positioner. It can be operated in a frequency range from 50 MHz to 20 GHz, with a scanning aperture of 20 m in the horizontal and 1.5 m in the vertical direction. Tests carried out with standard reflectors showed that the polarimetric measurement capabilities of this system are satisfactory. Using the polarimetric ground-based SAR (GB-SAR) system, we carried out measurements on a specific vegetation cover pertinent to the remote sensing of forested regions within Sendai City, consisting of three different kinds of trees common within the Kawauchi Campus of Tohoku University. Measurements were collected in spring, summer, and autumn. Three-dimensional (3-D) polarization-sensitive images were reconstructed from the acquired data. Analysis of the 3-D polarimetric images of each measurement found differences (at times strong differences) among the polarization signatures. There were stronger reflections in all of the HH, VH, VV images in the second (summer) measurement, especially in the VH image, due to the substantial growth of branches and leaves in summer. This ground-truth validation system provided valuable information about the scattering mechanisms of the three trees selected for analysis in different seasons, which can be detected by broadband polarimetric ground-based SAR measurements. The experimental results demonstrate the excellent polarimetric performance of the newly developed SAR imaging system, which should find many useful and immediate applications in noninvasive ground-truth validation of diverse terrestrial vegetation covers.},
  file         = {:home/baffelli/Library/Zhou, Boerner, Sato - 2004 - Development of a ground-based polarimetric broadband SAR system for noninvasive ground-truth validation in.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Polarimetric calibration,Radar polarimetry,Synthetic aperture radar (SAR),Vegetation monitoring},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Zhu2008,
  author       = {Zhu, Feng and Wu, Yong and Feng, You-Qian and Bai, You-Qing and Zhang, Qun},
  title        = {{A New Method for Imaging Avian Based on Frequency-stepped Chirp Signal}},
  journaltitle = {PIERS Online},
  date         = {2008},
  volume       = {4},
  pages        = {866--870},
  issn         = {1931-7360},
  doi          = {10.2529/PIERS080822224905},
  url          = {http://piers.mit.edu/piersonline/piers.php?year=2008{\&}volume=4{\&}number=8{\&}page=866},
  file         = {:home/baffelli/Library/Zhu et al. - 2008 - A New Method for Imaging Avian Based on Frequency-stepped Chirp Signal.pdf:pdf},
}

@Article{Zwieback2016,
  author       = {Zwieback, Simon and Hajnsek, Irena},
  title        = {Influence of Vegetation Growth on the Polarimetric Zero-Baseline {DInSAR} Phase Diversity - Implications for Deformation Studies},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2016},
  date         = {2016},
  volume       = {54},
  pages        = {3070--3082},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2015.2511118},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7378478},
  abstract     = {The polarization diversity of the phase causes ambiguities in the estimation of displacements using differential interferometry. Over natural surfaces such as vegetated areas, the magnitude of these ambiguities is potentially related to complex dynamic processes such as vegetation growth. As the properties and possible origins of such diversity (besides noiselike influences) over changing vegetation canopies are virtually unknown, we propose to investigate them empirically using an L-band zero-baseline data set covering one growing season over different agricultural crops. We frequently observe HH–VV phase differences exceeding 0.5$\pi$, corresponding to a displacement discrepancy of 3 cm. The HH–VV phase difference and other properties of the polarimetric coherence regions (e.g., the shape and the relation to the in situ observed biomass) vary with the crop type. The observations over wheat and barley and, to a lesser extent, rape suggest the presence of birefringence within the canopy. By contrast, those over maize and sugar beet, while also showing phase diversity, cannot be explained by birefringence or similarly simple models. Irrespective of the origin of this dependence, its presence and systematic nature indicate the potential importance of vegetation effects in differential interferometry, which may limit the accuracy of the estimated deformations over vegetated areas.},
  file         = {:home/baffelli/Library/Zwieback, Hajnsek - 2016 - Influence of Vegetation Growth on the Polarimetric Zero-Baseline DInSAR Phase Diversity - Implications for De.pdf:pdf;:home/baffelli/Library/Zwieback, Hajnsek - 2016 - Influence of Vegetation Growth on the Polarimetric Zero-Baseline DInSAR Phase Diversity - Implications for De.pdf:pdf},
  keywords     = {Birefringence,radar interferometry,radar remote sensing,synthetic aperture radar,vegetation},
}

@Article{Zwieback2017,
  author    = {Zwieback, Simon and Hensley, Scott and Hajnsek, Irena},
  title     = {{Interferometry : Toward Separating Soil Moisture and Displacements}},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2017},
  date      = {2017},
  volume    = {55},
  month     = {sep},
  pages     = {1--15},
  doi       = {10.1109/TGRS.2017.2702099},
  file      = {:home/baffelli/Library/Zwieback, Hensley, Hajnsek - 2017 - Interferometry Toward Separating Soil Moisture and Displacements.pdf:pdf},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Zwieback2015,
  author       = {Zwieback, Simon and Hensley, Scott and Hajnsek, Irena},
  title        = {A Polarimetric First-Order Model of Soil Moisture Effects on the {DInSAR} Coherence},
  journal      = {Remote Sensing},
  journaltitle = {Remote Sensing},
  year         = {2015},
  date         = {2015-06},
  volume       = {7},
  month        = {jun},
  pages        = {7571--7596},
  issn         = {2072-4292},
  doi          = {10.3390/rs70607571},
  url          = {http://www.mdpi.com/2072-4292/7/6/7571/},
  file         = {:home/baffelli/Library/Zwieback, Hensley, Hajnsek - 2015 - A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence.pdf:pdf},
  publisher    = {{MDPI} {AG}},
}

@Article{Zwieback2016b,
  author       = {Zwieback, Simon and Liu, Xingyu and Antonova, Sofia and Heim, Birgit and Bartsch, Annett and Boike, Julia and Hajnsek, Irena},
  title        = {A Statistical Test of Phase Closure to Detect Influences on {DInSAR} Deformation Estimates Besides Displacements and Decorrelation Noise: Two Case Studies in High-Latitude Regions},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2016},
  volume       = {54},
  pages        = {5588--5601},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2016.2569435},
  abstract     = {Displacements of the Earth's surface can be estimated using differential interferometric synthetic aperture radar. The estimates are derived from the phase difference between two radar acquisitions. When at least three such acquisitions are available, one can compute the displacement between the first and the third acquisition and compare it with the sum of the two intermediate displacements. These two are expected to be equal for a piston-like spatially uniform deformation. However, this is not necessarily the case in measured data. Such lack of phase closure can be due to decorrelation noise alone. It has also been attributed to complex scattering processes such as soil moisture changes or multiple scattering sources. However, the nature of these nonrandom effects is only poorly understood in cold regions, as the role of snow and freeze/thaw processes has not been studied to date. To distinguish the noise-like and the systematic effects, an asymptotic Wald significance test is proposed. It detects situations when the observed closure error cannot solely be explained by noise. Such situations with are observed at the Ku-band during snow metamorphism and melt and following a summer precipitation event in Sodankyl?, Finland. They can also be prevalent ({\textgreater} 25{\%}) in the X-band observations of ice-rich permafrost regions in the Lena Delta, Russia, indicating the presence of processes that can have systematic and deleterious impacts on the estimation of surface movements. Satellite-based monitoring of these displacements is thus possibly subject to complex error sources in high-latitude regions.},
  file         = {:home/baffelli/Library/Zwieback et al. - 2016 - A Statistical Test of Phase Closure to Detect Influences on DInSAR Deformation Estimates Besides Displacements.pdf:pdf},
}

@InProceedings{VanZyl2000,
  author       = {van Zyl, J.J. and Kim, Yunjin},
  title        = {{The relationship between radar polarimetric and interferometric phase}},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date         = {2000},
  volume       = {3},
  publisher    = {IEEE},
  isbn         = {0-7803-6359-0},
  pages        = {1301--1303},
  doi          = {10.1109/IGARSS.2000.858100},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=858100},
  file         = {:home/baffelli/Library/van Zyl, Kim - 2000 - The relationship between radar polarimetric and interferometric phase.pdf:pdf},
  journaltitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
}

@Article{VanZyl1987,
  author       = {Jakob J. van Zyl and Howard A. Zebker and Charles Elachi},
  title        = {Imaging radar polarization signatures: Theory and observation},
  journal      = {Radio Science},
  journaltitle = {Radio Science},
  year         = {1987},
  date         = {1987},
  volume       = {22},
  month        = {jul},
  pages        = {529--543},
  issn         = {1944-799X},
  doi          = {10.1029/RS022i004p00529},
  abstract     = {We have converted a conventional synthetic aperture radar system into an imaging radar polarimeter by employing two orthogonally polarized antennas and recording both the amplitude and absolute phase measurements of the received electric fields.},
  keywords     = {0669 Scattering and diffraction,0694 Electromagnetics: Instrumentation and techniq,6969 Remote sensing},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Zyl1990,
  author       = {Zyl, J J Van},
  title        = {{Calibration of polarimetric radar images using only image parameters and trihedral corner reflector responses}},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {1990},
  volume       = {28},
  pages        = {337--348},
}

@Article{Roethlisberger1987,
  author       = {H. R{\"{o}}thlisberger},
  title        = {Sliding phenomena in a steep section of {Balmhorngletscher}, {Switzerland}},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research},
  year         = {1987},
  date         = {1987},
  volume       = {92},
  pages        = {8999},
  doi          = {10.1029/jb092ib09p08999},
  publisher    = {American Geophysical Union ({AGU})},
}

@Article{Tommaso2017,
  author       = {Paolo {Di Tommaso} and Maria Chatzou and Evan W Floden and Pablo Prieto Barja and Emilio Palumbo and Cedric Notredame},
  title        = {Nextflow enables reproducible computational workflows},
  journal      = {Nature Biotechnology},
  journaltitle = {Nature Biotechnology},
  year         = {2017},
  date         = {2017-04},
  volume       = {35},
  month        = {apr},
  pages        = {316--319},
  doi          = {10.1038/nbt.3820},
  publisher    = {Springer Nature},
}

@Article{Samiei-Esfahany2016,
  author       = {Sami Samiei-Esfahany and Joana Esteves Martins and Freek van Leijen and Ramon F. Hanssen},
  title        = {Phase Estimation for Distributed Scatterers in {InSAR} Stacks Using Integer Least Squares Estimation},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2016},
  date         = {2016-10},
  volume       = {54},
  month        = {oct},
  pages        = {5671--5687},
  doi          = {10.1109/tgrs.2016.2566604},
  file         = {:Samiei-Esfahany2016 - Phase Estimation for Distributed Scatterers in InSAR Stacks Using Integer Least Squares Estimation.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Taylor1938,
  author       = {Taylor, Geoffrey Ingram},
  title        = {The spectrum of turbulence},
  journaltitle = {Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences},
  date         = {1938},
  pages        = {476--490},
  file         = {:476.full.pdf:PDF},
  publisher    = {JSTOR},
  timestamp    = {2018-03-23},
}

@Article{Fuentes2006a,
  author       = {Fuentes, Montserrat},
  title        = {Testing for separability of spatial--temporal covariance functions},
  journaltitle = {Journal of statistical planning and inference},
  date         = {2006},
  volume       = {136},
  pages        = {447--466},
  file         = {:1-s2.0-S0378375804003210-main.pdf:PDF},
  publisher    = {Elsevier},
  timestamp    = {2018-03-23},
}

@Article{Cao2018,
  author       = {Cao, Yunmeng and Li, Zhiwei and Wei, Jianchao and Hu, Jun and Duan, Meng and Feng, Guangcai},
  title        = {Stochastic modeling for time series {InSAR}: with emphasis on atmospheric effects},
  journaltitle = {Journal of Geodesy},
  date         = {2018-02-01},
  volume       = {92},
  pages        = {185--204},
  issn         = {1432-1394},
  doi          = {10.1007/s00190-017-1055-5},
  abstract     = {Despite the many applications of time series interferometric synthetic aperture radar (TS-InSAR) techniques in geophysical problems, error analysis and assessment have been largely overlooked. Tropospheric propagation error is still the dominant error source of InSAR observations. However, the spatiotemporal variation of atmospheric effects is seldom considered in the present standard TS-InSAR techniques, such as persistent scatterer interferometry and small baseline subset interferometry. The failure to consider the stochastic properties of atmospheric effects not only affects the accuracy of the estimators, but also makes it difficult to assess the uncertainty of the final geophysical results. To address this issue, this paper proposes a network-based variance--covariance estimation method to model the spatiotemporal variation of tropospheric signals, and to estimate the temporal variance--covariance matrix of TS-InSAR observations. The constructed stochastic model is then incorporated into the TS-InSAR estimators both for parameters (e.g., deformation velocity, topography residual) estimation and uncertainty assessment. It is an incremental and positive improvement to the traditional weighted least squares methods to solve the multitemporal InSAR time series. The performance of the proposed method is validated by using both simulated and real datasets.},
  day          = {01},
  file         = {:10.1007%2Fs00190-017-1055-5.pdf:PDF},
  timestamp    = {2018-03-28},
}

@Electronic{SFSO2010,
  author    = {{Swiss Federal Statistical Office}},
  title     = {Land use statistics 2004/09 based on the land coverage nomenclature {NOLC04}},
  date      = {2010},
  url       = {https://www.geocat.ch/geonetwork/srv/eng/catalog.search#/metadata/b53c03bb-a168-491f-b266-c7e9ec0af320
},
  timestamp = {2018-04-17},
}

@InProceedings{Cloude2002,
  author       = {Cloude, Shane R and Pottier, Eric and Boerner, Wolfgang M},
  title        = {Unsupervised image classification using the entropy/alpha/anisotropy method in radar polarimetry},
  booktitle    = {NASA-JPL, AIRSAR-02 Workshop},
  date         = {2002},
  organization = {Double Tree Hotel},
  pages        = {04--06},
  timestamp    = {2018-04-18},
}

@Article{Wagner2008,
  author       = {Wolfgang Wagner and Carsten Pathe and Marcela Doubkova and Daniel Sabel and Annett Bartsch and Stefan Hasenauer and Günter Blöschl and Klaus Scipal and Jos{\'{e}} Mart{\'{\i}}nez-Fern{\'{a}}ndez and Alexander Löw},
  title        = {Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar ({ASAR})},
  journal      = {Sensors},
  journaltitle = {Sensors},
  year         = {2008},
  date         = {2008},
  volume       = {8},
  month        = {feb},
  pages        = {1174--1197},
  doi          = {10.3390/s80201174},
  publisher    = {Molecular Diversity Preservation International},
  timestamp    = {2018-04-19},
}

@Article{Susan_Moran_2000,
  author       = {M Susan Moran},
  title        = {Soil moisture evaluation using multi-temporal synthetic aperture radar ({SAR}) in semiarid rangeland},
  journaltitle = {Agricultural and Forest Meteorology},
  date         = {2000-11},
  volume       = {105},
  pages        = {69--80},
  doi          = {10.1016/s0168-1923(00)00189-1},
  publisher    = {Elsevier {BV}},
}
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@Article{Engman_1995,
  author       = {Edwin T. Engman and Narinder Chauhan},
  title        = {Status of microwave soil moisture measurements with remote sensing},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {1995},
  date         = {1995-01},
  volume       = {51},
  month        = {jan},
  pages        = {189--198},
  doi          = {10.1016/0034-4257(94)00074-w},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-04-19},
}

@Article{Licciardi2014,
  author       = {Licciardi, Giorgio and Avezzano, Ruggero Giuseppe and Del Frate, Fabio and Schiavon, Giovanni and Chanussot, Jocelyn},
  title        = {A novel approach to polarimetric SAR data processing based on Nonlinear PCA},
  journaltitle = {Pattern recognition},
  date         = {2014},
  volume       = {47},
  pages        = {1953--1967},
  publisher    = {Elsevier},
  timestamp    = {2018-04-23},
}

@InProceedings{Latini2014,
  author       = {Latini, Daniele and Del Frate, Fabio and Jones, Cathleen E},
  title        = {Oil spill analysis by means of full polarimetric UAVSAR (L-band) and Radarsat-2 (C-band) products acquired during Deepwater Horizon Disaster},
  booktitle    = {SAR Image Analysis, Modeling, and Techniques XIV},
  date         = {2014},
  volume       = {9243},
  organization = {International Society for Optics and Photonics},
  pages        = {92430S},
  timestamp    = {2018-04-23},
}

@Article{Lee1999a,
  author       = {Jong-Sen Lee and M.R. Grunes and G. de Grandi},
  title        = {Polarimetric {SAR} speckle filtering and its implication for classification},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and remote sensing},
  year         = {1999},
  date         = {1999},
  volume       = {37},
  pages        = {2363--2373},
  doi          = {10.1109/36.789635},
  publisher    = {IEEE},
  timestamp    = {2018-04-24},
}

@Article{Alonso-Gonzalez2013,
  author       = {Alberto Alonso-Gonz{\'{a}}lez and Carlos L{\'{o}}pez-Mart{\'{\i}}nez and Philippe Salembier and Xinping Deng},
  title        = {Bilateral Distance Based Filtering for Polarimetric {SAR} Data},
  journal      = {Remote Sensing},
  journaltitle = {Remote Sensing},
  year         = {2013},
  date         = {2013},
  volume       = {5},
  month        = {oct},
  pages        = {5620--5641},
  doi          = {10.3390/rs5115620},
  publisher    = {Multidisciplinary Digital Publishing Institute},
  timestamp    = {2018-04-24},
}

@Article{Piermattei2017,
  author       = {Piermattei, Livia and Hollaus, Markus and Milenkovi{\'c}, Milutin and Pfeifer, Norbert and Quast, Raphael and Chen, Yuwei and Hakala, Teemu and Karjalainen, Mika and Hyypp{\"a}, Juha and Wagner, Wolfgang},
  title        = {An Analysis of Ku-Band Profiling Radar Observations of Boreal Forest},
  journaltitle = {Remote Sensing},
  date         = {2017},
  volume       = {9},
  pages        = {1252},
  doi          = {10.3390/rs9121252},
  file         = {:remotesensing-09-01252.pdf:PDF},
  publisher    = {Multidisciplinary Digital Publishing Institute},
  timestamp    = {2018-04-24},
}

@Article{Willatt2011,
  author       = {Rosemary Willatt and Seymour Laxon and Katharine Giles and Robert Cullen and Christian Haas and Veit Helm},
  title        = {{Ku}-band radar penetration into snow cover on Arctic sea ice using airborne data},
  journal      = {Annals of Glaciology},
  journaltitle = {Annals of Glaciology},
  year         = {2011},
  date         = {2011},
  volume       = {52},
  pages        = {197--205},
  doi          = {10.3189/172756411795931589},
  file         = {:5aa766fd452272d2276a853a70daf41bb4b2.pdf:PDF},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2018-04-24},
}

@Article{Yueh2009,
  author       = {Yueh, Simon H and Dinardo, Steve J and Akgiray, Ahmed and West, Richard and Cline, Donald W and Elder, Kelly},
  title        = {Airborne Ku-band polarimetric radar remote sensing of terrestrial snow cover},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  date         = {2009},
  volume       = {47},
  pages        = {3347--3364},
  file         = {:05204221 (1).pdf:PDF},
  publisher    = {IEEE},
  timestamp    = {2018-04-24},
}

@InProceedings{Shi2006,
  author       = {Shi, Jiancheng},
  title        = {Snow water equivalence retrieval using {X} and {Ku} band dual-polarization radar},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2006},
  date         = {2006},
  organization = {IEEE},
  publisher    = {{IEEE}},
  month        = {jul},
  pages        = {2183--2185},
  doi          = {10.1109/IGARSS.2006.564},
  file         = {:04241711.pdf:PDF},
  timestamp    = {2018-04-24},
}

@PhdThesis{Tse2009,
  author      = {Tse, Ka-ki},
  title       = {Multiple scattering of waves by dense random distributions of particles for applications in light scattering by noble metal nanoparticles and microwave scattering by terrestrial snow},
  institution = {{City University of Hong Kong}},
  date        = {2009},
  timestamp   = {2018-04-24},
}

@Article{Liu1988,
  author       = {Liu, HL and Fung, AK},
  title        = {An empirical model for polarized and cross-polarized scattering from a vegetation layer},
  journaltitle = {Remote Sensing of Environment},
  date         = {1988},
  volume       = {25},
  pages        = {23--36},
  publisher    = {Elsevier},
  timestamp    = {2018-04-24},
}

@Article{Ito1995,
  author       = {Ito, Shigeo and Oguchi, Tomohiro and Iguchi, Toshio and Kumagai, Hiroshi and Meneghini, Robert},
  title        = {Depolarization of radar signals due to multiple scattering in rain},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE transactions on geoscience and remote sensing},
  year         = {1995},
  date         = {1995},
  volume       = {33},
  number       = {4},
  month        = {jul},
  pages        = {1057--1062},
  doi          = {10.1109/36.406691},
  publisher    = {IEEE},
  timestamp    = {2018-04-24},
}

@Article{Fung1982,
  author       = {Fung, AK},
  title        = {A review of volume scatter theories for modeling applications},
  journaltitle = {Radio Science},
  date         = {1982},
  volume       = {17},
  pages        = {1007--1017},
  publisher    = {Wiley Online Library},
  timestamp    = {2018-04-24},
}

@Article{Attema1978,
  author       = {E. P. W. Attema and Fawwaz T. Ulaby},
  title        = {Vegetation modeled as a water cloud},
  journal      = {Radio Science},
  journaltitle = {Radio science},
  year         = {1978},
  date         = {1978},
  volume       = {13},
  month        = {mar},
  pages        = {357--364},
  doi          = {10.1029/RS013i002p00357},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-04-25},
}

@Article{Emmerik2015,
  author       = {Tim van Emmerik and Susan C. Steele-Dunne and Jasmeet Judge and Nick van de Giesen},
  title        = {Impact of Diurnal Variation in Vegetation Water Content on Radar Backscatter From Maize During Water Stress},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2015},
  date         = {2015},
  volume       = {53},
  month        = {jul},
  pages        = {3855--3869},
  doi          = {10.1109/TGRS.2014.2386142},
  file         = {:07015583.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-04-25},
}

@Article{Stiles1980,
  author       = {William H. Stiles and Fawwaz T. Ulaby},
  title        = {The active and passive microwave response to snow parameters: 1. Wetness},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research: Oceans},
  year         = {1980},
  date         = {1980},
  volume       = {85},
  pages        = {1037},
  doi          = {10.1029/JC085iC02p01037},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-04-25},
}

@Article{Ulaby1980,
  author       = {Fawwaz T. Ulaby and William H. Stiles},
  title        = {The active and passive microwave response to snow parameters: 2. Water equivalent of dry snow},
  journal      = {Journal of Geophysical Research},
  journaltitle = {Journal of Geophysical Research: Oceans},
  year         = {1980},
  date         = {1980},
  volume       = {85},
  pages        = {1045--1049},
  doi          = {10.1029/JC085iC02p01045},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-04-25},
}

@Article{Shi_2016,
  author       = {JianCheng Shi and Chuan Xiong and LingMei Jiang},
  title        = {Review of snow water equivalent microwave remote sensing},
  journal      = {Science China Earth Sciences},
  journaltitle = {Science China Earth Sciences},
  year         = {2016},
  date         = {2016-01},
  volume       = {59},
  month        = {jan},
  pages        = {731--745},
  doi          = {10.1007/s11430-015-5225-0},
  publisher    = {Springer Nature},
  timestamp    = {2018-04-25},
}

@Article{Maetzler1987,
  author       = {Christian Mätzler},
  title        = {Applications of the interaction of microwaves with the natural snow cover},
  journal      = {Remote Sensing Reviews},
  journaltitle = {Remote sensing reviews},
  year         = {1987},
  date         = {1987},
  volume       = {2},
  month        = {jan},
  pages        = {259--387},
  doi          = {10.1080/02757258709532086},
  file         = {:Applications of the interaction of microwaves with the natural snow cover.pdf:PDF},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2018-04-25},
}

@InProceedings{Koeniguer2015,
  author    = {{Koeniguer Colin}, Elise and Weissgerber, Flora and Trouv{\'e}, Nicolas and Nicolas, JM},
  title     = {A New Light on Origins of Polarimetric Misclassification of the {SOMA} district, Due to the Difficulty to Predict Entropy},
  booktitle = {Proceedings of PolInSAR},
  year      = {2015},
  date      = {2015},
  volume    = {729},
  file      = {:317967fd6e4fbb78b4f914a47ed12ff91b8a.pdf:PDF},
  timestamp = {2018-04-26},
}

@InProceedings{Lee2007,
  author       = {Jong-Sen Lee and Thomas L. Ainsworth and John Kelly and Carlos Lopez-Martinez},
  title        = {Evaluation and bias removal of multi-look effect on entropy/alpha/anisotropy},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2007},
  date         = {2007},
  organization = {IEEE},
  publisher    = {{IEEE}},
  pages        = {172--175},
  doi          = {10.1109/IGARSS.2007.4422757},
  timestamp    = {2018-04-26},
}

@InProceedings{Angelliaume2009,
  author       = {S. Angelliaume and P. Dubois-Fernandez and Ph. Dreuillet and H. Oriot and C. Coulombeix},
  title        = {{SETHI}, the {ONERA} airborne {SAR} sensor, and his low frequency capability},
  booktitle    = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year         = {2009},
  date         = {2009},
  volume       = {4},
  organization = {IEEE},
  publisher    = {{IEEE}},
  pages        = {IV--177},
  doi          = {10.1109/IGARSS.2009.5417343},
  file         = {:Angelliaume2009 - SETHI, the ONERA Airborne SAR Sensor, and His Low Frequency Capability.pdf:PDF},
  timestamp    = {2018-05-14},
}

@InProceedings{Cantalloube2006,
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  year         = {1988},
  date         = {1988-03},
  volume       = {23},
  month        = {mar},
  pages        = {163--170},
  doi          = {10.1029/rs023i002p00163},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-05-31},
}

@InCollection{Bozza2003,
  author    = {Silvia Bozza and Anthony O'Hagan},
  title     = {A Bayesian Approach for the Estimation of the Covariance Structure of Separable Spatio-Temporal Stochastic Processes},
  booktitle = {Between Data Science and Applied Data Analysis},
  date      = {2003},
  publisher = {Springer Berlin Heidelberg},
  pages     = {165--172},
  doi       = {10.1007/978-3-642-18991-3_19},
  timestamp = {2018-05-31},
}

@Article{Vasile2006,
  author       = {G. Vasile and E. Trouve and Jong-Sen Lee and V. Buzuloiu},
  title        = {Intensity-driven adaptive-neighborhood technique for polarimetric and interferometric {SAR} parameters estimation},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2006},
  date         = {2006-06},
  volume       = {44},
  month        = {jun},
  pages        = {1609--1621},
  doi          = {10.1109/tgrs.2005.864142},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-06-13},
}

@Article{Martino2014,
  author       = {Gerardo Di Martino and Antonio Iodice and Daniele Riccio and Giuseppe Ruello},
  title        = {Equivalent Number of Scatterers for {SAR} Speckle Modeling},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  date         = {2014-05},
  volume       = {52},
  pages        = {2555--2564},
  doi          = {10.1109/tgrs.2013.2262770},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-06-18},
}

@Article{BRISCO1990,
  author       = {B. Brisco and R.J Brown and J., Koehler and G. Sofko and M. Mckibben},
  title        = {The diurnal pattern of microwave backscattering by wheat},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {1990},
  date         = {1990-10},
  volume       = {34},
  month        = {oct},
  pages        = {37--47},
  doi          = {10.1016/0034-4257(90)90082-W},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-06-20},
}

@Article{Satake2004,
  author       = {M. Satake and H. Hanado},
  title        = {Diurnal change of {Amazon} rain forest {$\sigma^0$} observed by {Ku}-band spaceborne radar},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2004},
  date         = {2004-06},
  volume       = {42},
  month        = {jun},
  pages        = {1127--1134},
  doi          = {10.1109/tgrs.2004.825589},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-06-20},
}

@Proceedings{2018,
  title     = {Geostatistical Analysis and Mitigation of Atmosphere Induced Phase in Terrestrial Radar Interferometric Observations of an Alpine Glacier},
  date      = {2018},
  timestamp = {2018-06-26},
}

@InProceedings{Baffelli2018a,
  author    = {Simone Baffelli and Othmar Frey and Irena Hajnsek},
  title     = {Geostatistical Analysis and Mitigation Of Atmosphere Induced Phase In Terrestrial Radar Interferometric Observations Of An Alpine Glacier},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  year      = {2018},
  date      = {2018-06},
  abstract  = {Terrestrial Radar Interferometry can be used to maps surface displacement
velocites of alpine glaciers with high temporal resolution irrespective of
sunlight and cloud cover. A limiting factor for the estimation accuracy are
variations in the atmospheric refractive index, observed as an atmospheric
phase screen (APS). A method to estimate and mitigate the APS contribution
is presented, assuming a separable spatio-temporal correlation structure of
the APS, allowing to estimate it from a set of persitent scatterers (PS)
using regression-Kirging, followed by a temporal low-pass filter weighted
by an estimate of the temporal correlation function. The validity of
assuming separability and the performance of the correction are evaluated
using a Ku-Band radar data timeseries of Bisgletscher, a steep glacier in
the Southwestern Swiss Alps.},
  days      = {4},
}

@InProceedings{Lopez-Sanchez2011,
  author    = {J. M. Lopez-Sanchez and J. D. Ballester-Berman and S. R. Cloude},
  title     = {Monitoring and retrieving rice phenology by means of satellite {SAR} polarimetry at {X}-band},
  booktitle = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year      = {2011},
  date      = {2011-07},
  publisher = {{IEEE}},
  month     = {jul},
  doi       = {10.1109/igarss.2011.6049781},
  timestamp = {2018-07-03},
}

@Article{Pichierri2018,
  author       = {Manuele Pichierri and Irena Hajnsek and Simon Zwieback and Bernhard Rabus},
  title        = {On the potential of Polarimetric {SAR} Interferometry to characterize the~biomass, moisture and structure of agricultural crops at {L}-, {C}- and {X}-Bands},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {2018},
  date         = {2018-01},
  volume       = {204},
  month        = {jan},
  pages        = {596--616},
  doi          = {10.1016/j.rse.2017.09.039},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-07-04},
}

@Article{McNairn2002,
  author       = {Heather {McNairn} and Claude Duguay and Brian Brisco and Terry J. Pultz},
  title        = {The effect of soil and crop residue characteristics on polarimetric radar response},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {2002},
  date         = {2002-05},
  volume       = {80},
  month        = {may},
  pages        = {308--320},
  doi          = {10.1016/s0034-4257(01)00312-1},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-07-04},
}

@Article{Evans1988,
  author       = {D.L. Evans and T.G. Farr and J.J. van Zyl and H.A. Zebker},
  title        = {Radar polarimetry: analysis tools and applications},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {1988},
  date         = {1988},
  volume       = {26},
  pages        = {774--789},
  doi          = {10.1109/36.7709},
  file         = {:00007709.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-04},
}

@Book{Born1999,
  author    = {Max Born and Emil Wolf and A. B. Bhatia and P. C. Clemmow and D. Gabor and A. R. Stokes and A. M. Taylor and P. A. Wayman and W. L. Wilcock},
  title     = {Principles of Optics},
  year      = {1999},
  date      = {1999},
  publisher = {Cambridge University Press},
  doi       = {10.1017/cbo9781139644181},
  timestamp = {2018-07-20},
}

@Book{Mott2006,
  author    = {Harold Mott},
  title     = {Remote Sensing with Polarimetric Radar},
  date      = {2006-04},
  publisher = {John Wiley {\&} Sons, Inc.},
  doi       = {10.1002/0470079819},
  timestamp = {2018-07-20},
}

@Article{Whitney1971,
  author       = {Cynthia Whitney},
  title        = {Pauli-Algebraic Operators in Polarization Optics},
  journal      = {Journal of the Optical Society of America},
  journaltitle = {Journal of the Optical Society of America},
  year         = {1971},
  date         = {1971-09},
  volume       = {61},
  month        = {sep},
  pages        = {1207},
  doi          = {10.1364/josa.61.001207},
  file         = {:josa-61-9-1207.pdf:PDF},
  publisher    = {The Optical Society},
  timestamp    = {2018-07-21},
}

@Article{McMaster1954,
  author       = {William H. McMaster},
  title        = {Polarization and the Stokes Parameters},
  journaltitle = {American Journal of Physics},
  date         = {1954-09},
  volume       = {22},
  pages        = {351--362},
  doi          = {10.1119/1.1933744},
  publisher    = {American Association of Physics Teachers ({AAPT})},
  timestamp    = {2018-07-21},
}

@Book{Collett2005,
  author    = {Edward Collett},
  title     = {Field Guide to Polarization},
  date      = {2005-09},
  publisher = {{SPIE}},
  doi       = {10.1117/3.626141},
  timestamp = {2018-07-21},
}

@Article{Kostinski1986,
  author       = {A. Kostinski and W. Boerner},
  title        = {On foundations of radar polarimetry},
  journal      = {{IEEE} Transactions on Antennas and Propagation},
  journaltitle = {{IEEE} Transactions on Antennas and Propagation},
  year         = {1986},
  date         = {1986-12},
  volume       = {34},
  month        = {dec},
  pages        = {1395--1404},
  doi          = {10.1109/tap.1986.1143771},
  file         = {:01143771.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-21},
}

@Book{Boerner1992,
  author    = {Boerner, Wolfgang Martin},
  title     = {Direct and Inverse Methods in Radar Polarimetry},
  date      = {1992},
  publisher = {Springer Netherlands},
  doi       = {10.1007/978-94-010-9243-2},
  timestamp = {2018-07-21},
}

@InCollection{Boerner1992a,
  author    = {Wolfgang-M. Boerner and Wei-Ling Yan and An-Qing Xi and Yoshio Yamaguchi},
  title     = {Basic Concepts of Radar Polarimetry},
  booktitle = {Direct and Inverse Methods in Radar Polarimetry},
  year      = {1992},
  date      = {1992},
  publisher = {Springer Netherlands},
  pages     = {155--245},
  doi       = {10.1007/978-94-010-9243-2_8},
  file      = {:1992_Book_DirectAndInverseMethodsInRadar.pdf:PDF},
  timestamp = {2018-07-21},
}

@Article{Bickel1965,
  author       = {S.H. Bickel and R.H.T. Bates},
  title        = {Effects of magneto-ionic propagation on the polarization scattering matrix},
  journal      = {Proceedings of the {IEEE}},
  journaltitle = {Proceedings of the {IEEE}},
  year         = {1965},
  date         = {1965},
  volume       = {53},
  pages        = {1089--1091},
  doi          = {10.1109/proc.1965.4097},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-21},
}

@InProceedings{Meyer2010,
  author    = {Franz Meyer},
  title     = {A review of ionospheric effects in low-frequency {SAR} Signals, correction methods, and performance requirements},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year      = {2010},
  date      = {2010-07},
  publisher = {{IEEE}},
  month     = {jul},
  doi       = {10.1109/igarss.2010.5654258},
  timestamp = {2018-07-21},
}

@Book{JohnC.Curlander1991,
  author    = {John C. Curlander and Robert N. Mcdonough},
  title     = {Synthetic Aperture Radar},
  year      = {1991},
  date      = {1991-11-12},
  publisher = {John Wiley \& Sons},
  isbn      = {047185770X},
  url       = {https://www.ebook.de/de/product/3597624/john_c_curlander_robert_n_mcdonough_synthetic_aperture_radar.html},
  ean       = {9780471857709},
  timestamp = {2018-07-21},
}

@Article{Tilley1989,
  author       = {D.G. Tilley and K.S. Bonwit},
  title        = {Reduction of layover distortion in {SAR} imagery},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {1989},
  date         = {1989-03},
  volume       = {27},
  month        = {mar},
  pages        = {211--220},
  doi          = {10.1016/0034-4257(89)90083-7},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-07-21},
}

@Article{Pepe2017,
  author       = {Antonio Pepe and Fabiana Cal{\`{o}}},
  title        = {A Review of Interferometric Synthetic Aperture {RADAR} ({InSAR}) Multi-Track Approaches for the Retrieval of {Earth}'s Surface Displacements},
  journal      = {Applied Sciences},
  journaltitle = {Applied Sciences},
  year         = {2017},
  date         = {2017-12},
  volume       = {7},
  month        = {dec},
  pages        = {1264},
  doi          = {10.3390/app7121264},
  publisher    = {{MDPI} {AG}},
  timestamp    = {2018-07-21},
}

@Article{Reale2013,
  author       = {Diego Reale and Gianfranco Fornaro and Antonio Pauciullo},
  title        = {Extension of {4-D} {SAR} Imaging to the Monitoring of Thermally Dilating Scatterers},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2013},
  date         = {2013-12},
  volume       = {51},
  month        = {dec},
  pages        = {5296--5306},
  doi          = {10.1109/tgrs.2012.2233205},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-21},
}

@Article{Siddique2016,
  author       = {Muhammad Adnan Siddique and Urs Wegmüller and Irena Hajnsek and Othmar Frey},
  title        = {Single-Look {SAR} Tomography as an Add-On to {PSI} for Improved Deformation Analysis in Urban Areas},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2016},
  date         = {2016-10},
  volume       = {54},
  month        = {oct},
  pages        = {6119--6137},
  doi          = {10.1109/tgrs.2016.2581261},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-21},
}

@Article{Giuli1986,
  author       = {D. Giuli},
  title        = {Polarization diversity in radars},
  journal      = {Proceedings of the {IEEE}},
  journaltitle = {Proceedings of the {IEEE}},
  year         = {1986},
  date         = {1986},
  volume       = {74},
  pages        = {245--269},
  doi          = {10.1109/proc.1986.13457},
  file         = {:01457725.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-28},
}

@Book{Zyl2011,
  author    = {Jakob van Zyl and Yunjin Kim},
  title     = {Synthetic Aperture Radar Polarimetry},
  year      = {2011},
  date      = {2011-10},
  publisher = {John Wiley {\&} Sons, Inc.},
  doi       = {10.1002/9781118116104},
  file      = {:9781118116104.pdf:PDF},
  timestamp = {2018-07-28},
}

@InProceedings{Cloude2001,
  author    = {S.R. Cloude},
  title     = {A new method for characterizing depolarization effects in radar and optical remote sensing},
  booktitle = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  date      = {0201},
  publisher = {{IEEE}},
  doi       = {10.1109/igarss.2001.976677},
  file      = {:00976677.pdf:PDF},
  timestamp = {2018-07-28},
}

@Article{Parke1949,
  author       = {Nathan Grieb Parke},
  title        = {Optical Algebra},
  journaltitle = {Journal of Mathematics and Physics},
  date         = {1949-04},
  volume       = {28},
  pages        = {131--139},
  doi          = {10.1002/sapm1949281131},
  file         = {:Parke-1949-Journal_of_Mathematics_and_Physics.pdf:PDF},
  publisher    = {Wiley},
  timestamp    = {2018-07-28},
}

@Book{Hovenier2004,
  author    = {Joop W. Hovenier and Cornelis Van Der Mee and Helmut Domke},
  title     = {Transfer of Polarized Light in Planetary Atmospheres},
  date      = {2004},
  publisher = {Springer Netherlands},
  doi       = {10.1007/978-1-4020-2856-4},
  file      = {:154.pdf:PDF},
  timestamp = {2018-07-28},
}

@Article{Hovenier1994,
  author       = {J. W. Hovenier},
  title        = {Structure of a general pure {Mueller} matrix},
  journal      = {Applied Optics},
  journaltitle = {Applied Optics},
  year         = {1994},
  date         = {1994-12},
  volume       = {33},
  month        = {dec},
  pages        = {8318},
  doi          = {10.1364/ao.33.008318},
  publisher    = {The Optical Society},
  timestamp    = {2018-07-28},
}

@InProceedings{Giuli1990,
  author    = {D. Giuli and L. Facheris and M. Fossi and A. Rossettini},
  title     = {Simultaneous scattering matrix measurement through signal coding},
  booktitle = {Proceddins of the {IEEE} International Conference on Radar},
  date      = {1990},
  publisher = {{IEEE}},
  doi       = {10.1109/radar.1990.201173},
  timestamp = {2018-07-30},
}

@Article{Giuli1993,
  author       = {D. Giuli and M. Fossi and L. Facheris},
  title        = {Radar target scattering matrix measurement through orthogonal signals},
  journal      = {{IEE} Proceedings F Radar and Signal Processing},
  journaltitle = {{IEE} Proceedings F Radar and Signal Processing},
  year         = {1993},
  date         = {1993},
  volume       = {140},
  pages        = {233},
  doi          = {10.1049/ip-f-2.1993.0033},
  publisher    = {Institution of Engineering and Technology ({IET})},
  timestamp    = {2018-07-30},
}

@Article{Freeman1992a,
  author       = {A. Freeman},
  title        = {{SAR} calibration: an overview},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {1992},
  date         = {1992},
  volume       = {30},
  pages        = {1107--1121},
  doi          = {10.1109/36.193786},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@Article{Zebker1987a,
  author       = {Howard A. Zebker and Jakob J. van Zyl and Daniel N. Held},
  title        = {Imaging radar polarimetry from wave synthesis},
  journaltitle = {Journal of Geophysical Research},
  date         = {1987},
  volume       = {92},
  pages        = {683},
  doi          = {10.1029/jb092ib01p00683},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-30},
}

@Article{Sherwin1962,
  author       = {C. W. Sherwin and J. P. Ruina and R. D. Rawcliffe},
  title        = {Some Early Developments in Synthetic Aperture Radar Systems},
  journal      = {{IRE} Transactions on Military Electronics},
  journaltitle = {{IRE} Transactions on Military Electronics},
  year         = {1962},
  date         = {1962-04},
  volume       = {{MIL}-6},
  month        = {apr},
  pages        = {111--115},
  doi          = {10.1109/iret-mil.1962.5008415},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@Article{Cutrona1962,
  author       = {L. J. Cutrona and G. O. Hall},
  title        = {A Comparison of Techniques for Achieving Fine Azimuth Resolution},
  journal      = {{IRE} Transactions on Military Electronics},
  journaltitle = {{IRE} Transactions on Military Electronics},
  year         = {1962},
  date         = {1962-04},
  volume       = {{MIL}-6},
  month        = {apr},
  pages        = {119--121},
  doi          = {10.1109/iret-mil.1962.5008417},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@InProceedings{Munder2003,
  author    = {J. Munder and D. Miller},
  title     = {{TerraSAR}-{X}, {G}erman {X}-band remote sensing system},
  booktitle = {Proceeding of the International Conference on Recent Advances in Space Technologies,{RAST}},
  year      = {2003},
  date      = {2003},
  publisher = {{IEEE}},
  doi       = {10.1109/rast.2003.1303383},
  timestamp = {2018-07-30},
}

@InProceedings{Duchossois1981,
  author    = {G. Duchossois and C. Honvault},
  title     = {The First {ESA} Remote Sensing Satellite ({ERS})--The Programme and the System},
  booktitle = {{OCEANS} 81},
  year      = {1981},
  date      = {1981},
  publisher = {{IEEE}},
  doi       = {10.1109/oceans.1981.1151522},
  timestamp = {2018-07-30},
}

@Article{Gillespie1961,
  author       = {N. R. Gillespie and J. B. Higley and N. MacKinnon},
  title        = {The Evolution and Application of Coherent Radar Systems},
  journal      = {{IRE} Transactions on Military Electronics},
  journaltitle = {{IRE} Transactions on Military Electronics},
  year         = {1961},
  date         = {1961-04},
  volume       = {{MIL}-5},
  month        = {apr},
  pages        = {131--139},
  doi          = {10.1109/iret-mil.1961.5008331},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@Article{Graham1974,
  author       = {L.C. Graham},
  title        = {Synthetic interferometer radar for topographic mapping},
  journaltitle = {Proceedings of the {IEEE}},
  date         = {1974},
  volume       = {62},
  pages        = {763--768},
  doi          = {10.1109/proc.1974.9516},
  file         = {:01451446.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@Article{Graham1974a,
  author        = {L.C. Graham},
  title         = {Synthetic interferometer radar for topographic mapping},
  journaltitle  = {Proceedings of the {IEEE}},
  date          = {1974},
  volume        = {62},
  pages         = {763--768},
  doi           = {10.1109/proc.1974.9516},
  __markedentry = {[baffelli:]},
  publisher     = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp     = {2018-07-30},
}

@Article{Emardson1998,
  author       = {T. Ragne Emardson and Gunnar Elgered and Jan M. Johansson},
  title        = {Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers},
  journaltitle = {Journal of Geophysical Research: Atmospheres},
  date         = {1998-01},
  volume       = {103},
  pages        = {1807--1820},
  doi          = {10.1029/97jd03015},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-30},
}

@Article{Li2006,
  author       = {Z. Li and J.-P. Muller and P. Cross and P. Albert and J. Fischer and R. Bennartz},
  title        = {Assessment of the potential of {MERIS} near-infrared water vapour products to correct {ASAR} interferometric measurements},
  journal      = {International Journal of Remote Sensing},
  journaltitle = {International Journal of Remote Sensing},
  year         = {2006},
  date         = {2006-01},
  volume       = {27},
  month        = {jan},
  pages        = {349--365},
  doi          = {10.1080/01431160500307342},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2018-07-30},
}

@Article{Wadge2002,
  author       = {G. Wadge and P. W. Webley and I. N. James and R. Bingley and A. Dodson and S. Waugh and T. Veneboer and G. Puglisi and M. Mattia and D. Baker and S. C. Edwards and S. J. Edwards and P. J. Clarke},
  title        = {Atmospheric models, {GPS} and {InSAR} measurements of the tropospheric water vapour field over Mount {Etna}},
  journal      = {Geophysical Research Letters},
  journaltitle = {Geophysical Research Letters},
  year         = {2002},
  date         = {2002-10},
  volume       = {29},
  month        = {oct},
  pages        = {11--1--11--4},
  doi          = {10.1029/2002gl015159},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-30},
}

@InProceedings{Roedelsperger2014,
  author    = {Sabine Rödelsperger and Adriano Meta},
  title     = {{MetaSensing}{\textquotesingle}s {FastGBSAR}: ground based radar for deformation monitoring},
  booktitle = {{SAR} Image Analysis, Modeling, and Techniques {XIV}},
  year      = {2014},
  date      = {2014-10},
  publisher = {{SPIE}},
  month     = {oct},
  doi       = {10.1117/12.2067243},
  timestamp = {2018-07-30},
}

@Article{Lohman2005,
  author       = {Rowena B. Lohman and Mark Simons},
  title        = {Some thoughts on the use of {InSAR} data to constrain models of surface deformation: Noise structure and data downsampling},
  journal      = {Geochemistry, Geophysics, Geosystems},
  journaltitle = {Geochemistry, Geophysics, Geosystems},
  year         = {2005},
  date         = {2005-01},
  volume       = {6},
  month        = {jan},
  doi          = {10.1029/2004gc000841},
  file         = {:Lohman_et_al-2005-Geochemistry%2C_Geophysics%2C_Geosystems.pdf:PDF},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-31},
}

@Article{Zhou2014,
  author       = {X Zhou and Y M Xu and P Wang and C Xing},
  title        = {Research on Atmospheric Disturbance Correction method of ground-based radar interferometry},
  journal      = {{IOP} Conference Series: Earth and Environmental Science},
  journaltitle = {{IOP} Conference Series: Earth and Environmental Science},
  year         = {2014},
  date         = {2014-03},
  volume       = {17},
  month        = {mar},
  pages        = {012244},
  doi          = {10.1088/1755-1315/17/1/012244},
  file         = {:Zhou_2014_IOP_Conf._Ser.%3A_Earth_Environ._Sci._17_012244.pdf:PDF},
  publisher    = {{IOP} Publishing},
  timestamp    = {2018-07-31},
}

@Article{Hooper2004,
  author       = {Andrew Hooper and Howard Zebker and Paul Segall and Bert Kampes},
  title        = {A new method for measuring deformation on volcanoes and other natural terrains using {InSAR} persistent scatterers},
  journal      = {Geophysical Research Letters},
  journaltitle = {Geophysical Research Letters},
  year         = {2004},
  date         = {2004-12},
  volume       = {31},
  month        = {dec},
  doi          = {10.1029/2004gl021737},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-31},
}

@Article{Wei2010,
  author       = {Meng Wei and David T Sandwell},
  title        = {Decorrelation of {L}-Band and {C}-Band Interferometry Over Vegetated Areas in California},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2010},
  date         = {2010-07},
  volume       = {48},
  month        = {jul},
  pages        = {2942--2952},
  doi          = {10.1109/tgrs.2010.2043442},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-31},
}

@InProceedings{Nesti1995,
  author    = {G. Nesti and D. Tarchi and J.-P. Rudant},
  title     = {Decorrelation of backscattered signal due to soil moisture changes},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date      = {1995},
  publisher = {{IEEE}},
  doi       = {10.1109/igarss.1995.524098},
  timestamp = {2018-07-31},
}

@Article{Luo2000,
  author       = {X. Luo and J. Askne and G. Smith and P. Dammert},
  title        = {Coherence Characteristics of Radar Signals From Rough Soil - Abstract},
  journal      = {Journal of Electromagnetic Waves and Applications},
  journaltitle = {Journal of Electromagnetic Waves and Applications},
  year         = {2000},
  date         = {2000-01},
  volume       = {14},
  month        = {jan},
  pages        = {1555--1557},
  doi          = {10.1163/156939300x00310},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2018-07-31},
}

@Article{Zebker2000,
  author       = {H.A. Zebker and E. Weber Hoen},
  title        = {Penetration depths inferred from interferometric volume decorrelation observed over the {Greenland Ice Sheet}},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2000},
  date         = {2000},
  volume       = {38},
  pages        = {2571--2583},
  doi          = {10.1109/36.885204},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-31},
}

@Article{Zebker1998,
  author       = {Howard A. Zebker and Yanping Lu},
  title        = {Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms},
  journal      = {Journal of the Optical Society of America A},
  journaltitle = {Journal of the Optical Society of America A},
  year         = {1998},
  date         = {1998-03},
  volume       = {15},
  month        = {mar},
  pages        = {586},
  doi          = {10.1364/josaa.15.000586},
  publisher    = {The Optical Society},
  timestamp    = {2018-07-31},
}

@Article{Hocine2014,
  author       = {Faiza Hocine and Mohamed Fekir and Afifa Haddoud and Sawssen Belhadj-aissa and Aichouche Belhadj-aissa},
  title        = {A new {2D/3D} Phase Unwrapping Strategy of Differential Interferograms {SAR}},
  journal      = {Journal of the Indian Society of Remote Sensing},
  journaltitle = {Journal of the Indian Society of Remote Sensing},
  year         = {2014},
  date         = {2014-08},
  volume       = {43},
  month        = {aug},
  pages        = {199--212},
  doi          = {10.1007/s12524-014-0398-0},
  publisher    = {Springer Nature},
  timestamp    = {2018-07-31},
}

@Article{Mora2003,
  author       = {O. Mora and J.J. Mallorqui and A. Broquetas},
  title        = {Linear and nonlinear terrain deformation maps from a reduced set of interferometric {SAR} images},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2003},
  date         = {2003-10},
  volume       = {41},
  month        = {oct},
  pages        = {2243--2253},
  doi          = {10.1109/tgrs.2003.814657},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-31},
}

@Article{Goldstein1988,
  author       = {Richard M. Goldstein and Howard A. Zebker and Charles L. Werner},
  title        = {Satellite radar interferometry: Two-dimensional phase unwrapping},
  journal      = {Radio Science},
  journaltitle = {Radio Science},
  year         = {1988},
  date         = {1988-07},
  volume       = {23},
  month        = {jul},
  pages        = {713--720},
  doi          = {10.1029/rs023i004p00713},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-31},
}

@Article{Osmanoglu2016,
  author       = {Batuhan Osmano{\u{g}}lu and Filiz Sunar and Shimon Wdowinski and Enrique Cabral-Cano},
  title        = {Time series analysis of {InSAR} data: Methods and trends},
  journal      = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  journaltitle = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  year         = {2016},
  date         = {2016-05},
  volume       = {115},
  month        = {may},
  pages        = {90--102},
  doi          = {10.1016/j.isprsjprs.2015.10.003},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-07-31},
}

@Article{Hooper2007,
  author       = {Andrew Hooper and Howard A. Zebker},
  title        = {Phase unwrapping in three dimensions with application to {InSAR} time series},
  journaltitle = {Journal of the Optical Society of America A},
  date         = {2007},
  volume       = {24},
  pages        = {2737},
  doi          = {10.1364/josaa.24.002737},
  publisher    = {The Optical Society},
  timestamp    = {2018-07-31},
}

@InProceedings{Costantini2002,
  author    = {M. Costantini and F. Malvarosa and F. Minati and L. Pietranera and G. Milillo},
  title     = {A three-dimensional phase unwrapping algorithm for processing of multitemporal {SAR} interferometric measurements},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date      = {2002},
  publisher = {{IEEE}},
  doi       = {10.1109/igarss.2002.1026239},
  timestamp = {2018-07-31},
}

@InProceedings{Wiesmann2008,
  author    = {Andreas Wiesmann and Charles Werner and Christian Mätzler and Martin Schneebeli and Tazio Strozzi and Urs Wegmüller},
  title     = {Mobile {X-} to {Ku-}band Scatterometer in Support of the {CoRe-H2O} Mission},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  year      = {2008},
  date      = {2008},
  publisher = {{IEEE}},
  doi       = {10.1109/igarss.2008.4780073},
  file      = {:04780073.pdf:PDF},
  timestamp = {2018-08-02},
}

@Article{Pasquale2018,
  author       = {Andrea Di Pasquale and Giovanni Nico and Alfredo Pitullo and Giuseppina Prezioso},
  title        = {Monitoring Strategies of Earth Dams by Ground-Based Radar Interferometry: How to Extract Useful Information for Seismic Risk Assessment},
  journal      = {Sensors},
  journaltitle = {Sensors},
  year         = {2018},
  date         = {2018-01},
  volume       = {18},
  month        = {jan},
  pages        = {244},
  doi          = {10.3390/s18010244},
  publisher    = {{MDPI} {AG}},
  timestamp    = {2018-08-02},
}

@InProceedings{Tarchi1999,
  author    = {D. Tarchi and H. Rudolf and G. Luzi and L. Chiarantini and P. Coppo and A.J. Sieber},
  title     = {{SAR} interferometry for structural changes detection: a demonstration test on a dam},
  booktitle = {Proceedings of the IEEE International Geoscience and Remote Sensing Symposium},
  date      = {1999},
  publisher = {{IEEE}},
  doi       = {10.1109/igarss.1999.772006},
  file      = {:00772006.pdf:PDF},
  timestamp = {2018-08-02},
}

@Article{Moore1978,
  author       = {R. Moore},
  title        = {Active microwave sensing of the {Earth}{\textquotesingle}s surface--A mini review},
  journal      = {{IEEE} Transactions on Antennas and Propagation},
  journaltitle = {{IEEE} Transactions on Antennas and Propagation},
  year         = {1978},
  date         = {1978-11},
  volume       = {26},
  number       = {6},
  month        = {nov},
  pages        = {843--849},
  doi          = {10.1109/tap.1978.1141950},
  file         = {:01141950.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-08-02},
}

@Article{Moore1971,
  author       = {R. Moore and G. Thomann},
  title        = {Imaging Radars for Geoscience Use},
  journal      = {{IEEE} Transactions on Geoscience Electronics},
  journaltitle = {{IEEE} Transactions on Geoscience Electronics},
  year         = {1971},
  date         = {1971-07},
  volume       = {9},
  month        = {jul},
  pages        = {155--164},
  doi          = {10.1109/tge.1971.271488},
  file         = {:04043481.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-08-02},
}

@Article{Bekaert2015,
  author       = {D.P.S. Bekaert and R.J. Walters and T.J. Wright and A.J. Hooper and D.J. Parker},
  title        = {Statistical comparison of {InSAR} tropospheric correction techniques},
  journal      = {Remote Sensing of Environment},
  journaltitle = {Remote Sensing of Environment},
  year         = {2015},
  date         = {2015-12},
  volume       = {170},
  month        = {dec},
  pages        = {40--47},
  doi          = {10.1016/j.rse.2015.08.035},
  file         = {:1-s2.0-S0034425715301231-main.pdf:PDF},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018-08-06},
}

@Article{Li2012a,
  author    = {Z. W. Li and W. B. Xu and G. C. Feng and J. Hu and C. C. Wang and X. L. Ding and J. J. Zhu},
  title     = {Correcting atmospheric effects on {InSAR} with {MERIS} water vapour data and elevation-dependent interpolation model},
  journal   = {Geophysical Journal International},
  year      = {2012},
  volume    = {189},
  month     = {mar},
  pages     = {898--910},
  doi       = {10.1111/j.1365-246x.2012.05432.x},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018-09-18},
}

@Article{Baker1983,
  author    = {P. W. Baker},
  title     = {Atmospheric water vapor differential absorption measurements on vertical paths with a CO2 lidar},
  journal   = {Applied Optics},
  year      = {1983},
  volume    = {22},
  month     = {aug},
  pages     = {2257},
  doi       = {10.1364/ao.22.002257},
  publisher = {The Optical Society},
  timestamp = {2018-09-18},
}

@Article{Basili2004,
  author    = {P. Basili and S. Bonafoni and V. Mattioli and P. Ciotti and N. Pierdicca},
  title     = {Mapping the atmospheric water vapor by integrating microwave radiometer and {GPS} measurements},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2004},
  volume    = {42},
  month     = {aug},
  pages     = {1657--1665},
  doi       = {10.1109/tgrs.2004.830943},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-10-10},
}

@Article{Li2009,
  author    = {Zhenhong Li and E. J. Fielding and P. Cross and R. Preusker},
  title     = {Advanced {InSAR} atmospheric correction: {MERIS}/{MODIS} combination and stacked water vapour models},
  journal   = {International Journal of Remote Sensing},
  year      = {2009},
  volume    = {30},
  month     = {jul},
  pages     = {3343--3363},
  doi       = {10.1080/01431160802562172},
  publisher = {Informa {UK} Limited},
  timestamp = {2018-10-10},
}

@Article{Webley2004,
  author    = {P.W. Webley and G. Wadge and I.N. James},
  title     = {Determining radio wave delay by non-hydrostatic atmospheric modelling of water vapour over mountains},
  journal   = {Physics and Chemistry of the Earth, Parts A/B/C},
  year      = {2004},
  volume    = {29},
  month     = {jan},
  pages     = {139--148},
  doi       = {10.1016/j.pce.2004.01.013},
  publisher = {Elsevier {BV}},
  timestamp = {2018-10-10},
}

@Article{Iglesias2014,
  author       = {Ruben Iglesias and Albert Aguasca and Xavier Fabregas and Jordi J. Mallorqui and Dani Monells and Carlos Lopez-Martinez and Luca Pipia},
  title        = {Ground-Based Polarimetric {SAR} Interferometry for the Monitoring of Terrain Displacement Phenomena{\textendash}Part {I}: Theoretical Description},
  journal      = {{IEEE} Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  journaltitle = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year         = {2014},
  date         = {2014},
  volume       = {8},
  pages        = {1--1},
  issn         = {1939-1404},
  doi          = {10.1109/JSTARS.2014.2360040},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6981929 http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6982213},
  file         = {:home/baffelli/Library/Iglesias et al. - 2014 - Ground-based polarimetric SAR interferometry for the monitoring of terrain displacement phenomena-part I theore.pdf:pdf},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InCollection{Gneiting2007,
  author    = {Gneiting, Tilmann and Genton, Marc and Guttorp, Peter},
  title     = {{Geostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry}},
  booktitle = {Statistical Methods for Spatio-Temporal Systems},
  date      = {2006-10},
  publisher = {Chapman and Hall},
  isbn      = {978-1-58488-593-1},
  pages     = {151--175},
  doi       = {10.1201/9781420011050.ch4},
  abstract  = {Geostatistical approaches to modeling spatio-temporal data rely on parametric covariance models and rather stringent assumptions, such as stationarity, separability and full symmetry. This paper reviews recent advances in the literature on space-time covariance functions in light of the aforementioned notions, which are illustrated using wind data from Ireland. Experiments with time-forward kriging predictors suggest that the use of more complex and more realistic covariance models results in improved predictive performance.},
  file      = {:home/baffelli/Library/Gneiting, Genton, Guttorp - 2006 - Geostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry.pdf:pdf},
  keywords  = {bochner,correlation function,gaussian random field,gian,kriging,lagran-,positive definite,s hypothesis,s theorem,spatio-temporal prediction,taylor,variogram},
}

@Book{Wackernagel2003,
  author    = {Hans Wackernagel},
  title     = {Multivariate Geostatistics},
  year      = {2003},
  date      = {2003},
  publisher = {Springer},
  isbn      = {978-3-642-07911-5},
  doi       = {10.1007/978-3-662-05294-5},
  file      = {:home/baffelli/Library/Wackernagel - 2003 - Multivariate Geostatistics.pdf:pdf},
}

@Article{Christensen1990,
  author       = {Ronald Christensen},
  title        = {The equivalence of predictions from universal {Kriging} and intrinsic random-function {Kriging}},
  journal      = {Mathematical Geology},
  journaltitle = {Mathematical Geology},
  year         = {1990},
  date         = {1990},
  volume       = {22},
  month        = {aug},
  pages        = {655--664},
  issn         = {08828121},
  doi          = {10.1007/BF00890514},
  abstract     = {A proof is provided that the predictions obtained from kriging based on intrinsic random functions of order k are identical to those obtained from anappropriate universal kriging model. This is a theoretical result based on known variability measures. It does not imply that people performing traditional universal kriging will get the same predictions as those using intrinsic random functions, because traditionally these methods differ in how variability is modeled. For intrinsic random functions, the same proof shows that predictions do not depend on the specific choice of the generalized covariance function. It is argued that the choice between these methods is really one of modeling and estimating the variability in the data.},
  file         = {:home/baffelli/Library/Christensen - 1990 - The equivalence of predictions from universal kriging and intrinsic random-function kriging.pdf:pdf},
  keywords     = {best linear unbiased prediction,covariance,linear models,semivariogram,variogram},
  publisher    = {Springer Nature},
}

@Article{Baffelli2018,
  author       = {Simone Baffelli and Othmar Frey and Charles Werner and Irena Hajnsek},
  title        = {Polarimetric Calibration of the {Ku}-Band Advanced Polarimetric Radar Interferometer},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2018},
  date         = {2018-04},
  volume       = {56},
  pages        = {1--17},
  issn         = {0196-2892},
  doi          = {10.1109/tgrs.2017.2778049},
  url          = {http://ieeexplore.ieee.org/document/8226855/},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Beutel2011,
  author       = {Jan Beutel and B. Buchli and F. Ferrari and M. Keller and M. Zimmerling and Lothar Thiele},
  title        = {X-{SENSE}: Sensing in extreme environments},
  booktitle    = {Design, Automation {\&} Test in Europe},
  year         = {2011},
  date         = {2011-03},
  publisher    = {{IEEE}},
  month        = {mar},
  isbn         = {9783981080179},
  pages        = {1--6},
  doi          = {10.1109/DATE.2011.5763236},
  url          = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5763236 http://ieeexplore.ieee.org/search/srchabstract.jsp?tp={\&}arnumber=5763236{\&}queryText{\%}3D{\%}28sensing+in+extreme+environments{\%}29{\%}26openedRefinements{\%}3D*{\%}26matchBoolean{\%}3Dtrue{\%}26rowsPerPage{\%}3D3},
  abstract     = {The field of Wireless Sensor Networks (WSNs) is now in a stage where serious applications of societal and economical importance are in reach. For example, it is well known that the global climate change dramatically influences the visual appearance of mountain areas like the European Alps. Very destructive geological processes may be triggered or intensified, impacting the stability of slopes, possibly inducing landslides. Unfortunately, the interactions between these complex processes is poorly understood. Therefore, one needs to develop wireless sensing technology as a new scientific instrument for environmental sensing under extreme conditions. Large variations in temperature, humidity, mechanical forces, snow coverage, and unattended operation play a crucial role in long-term deployments. We argue that, in order to significantly advance the application domain, it is inevitable that sensor networks be created as a quality scientific instrument with known and predictable properties, and not as a research toy delivering average observations at best. In this paper, key techniques for achieving highly reliable, yet resource efficient wireless sensor networks are discussed on the basis of productive wireless sensor networks measuring permafrost processes in the Swiss Alps.},
  file         = {:home/baffelli/Library/Beutel et al. - 2011 - X-SENSE Sensing in extreme environments.pdf:pdf},
  issn         = {1530-1591},
  journaltitle = {Design, Automation Test in Europe Conference Exhibition (DATE), 2011},
  keywords     = {Batteries,Meteorology,Protocols,Swiss Alps,Temperature distribution,Temperature sensors,Wireless communication,Wireless sensor networks,X-SENSE project,climatology,destructive geological process,environmental monitoring (geophysics),environmental sensing,extreme environment sensing,geology,global climate change,mountain,permafrost process measurement,scientific instrument,wireless sensor network,wireless sensor networks},
  shorttitle   = {X-SENSE},
}

@Article{Monserrat2014,
  author        = {O. Monserrat and M. Crosetto and G. Luzi},
  title         = {A review of ground-based {SAR} interferometry for deformation measurement},
  journal       = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  journaltitle  = {ISPRS Journal of Photogrammetry and Remote Sensing},
  year          = {2014},
  date          = {2014},
  volume        = {93},
  month         = {jul},
  pages         = {40--48},
  issn          = {09242716},
  doi           = {10.1016/j.isprsjprs.2014.04.001},
  abstract      = {This paper provides a review of ground-based SAR (GBSAR) interferometry for deformation measurement. In the first part of the paper the fundamentals of this technique are provided. Then the main data processing and analysis stages needed to estimate deformations starting from the GBSAR observations are described. This section introduces the two types of GBSAR acquisition modes, i.e., continuous and discontinuous GBSAR, and reviews the different GBSAR processing and analysis methods published in the literature. This is followed by a discussion of the specific technical aspects of GBSAR deformation measurement. A section then summarizes the pros and cons of GBSAR for deformation monitoring. The last part of the paper includes two reviews: one concerning the GBSAR systems described in the literature, including non-strictly SAR systems and a second one addresses the main GBSAR applications. {\textcopyright} 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).},
  file          = {:home/baffelli/Library/Monserrat, Crosetto, Luzi - 2014 - A review of ground-based SAR interferometry for deformation measurement.pdf:pdf},
  isbn          = {0924-2716},
  keywords      = {Deformation,Interferometry,Monitoring,Review,SAR,Terrestrial},
  mendeley-tags = {Review},
  publisher     = {International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)},
}

@Article{Butt2016,
  author       = {Jemil Butt and Andreas Wieser and Stefan Conzett},
  title        = {Intrinsic random functions for mitigation of atmospheric effects in terrestrial radar interferometry},
  journal      = {Journal of Applied Geodesy},
  journaltitle = {Proceedings of JISDM 2016 Vienna},
  year         = {2017},
  date         = {2016},
  volume       = {11},
  month        = {jan},
  pages        = {89--98},
  issn         = {1862-9024},
  doi          = {10.1515/jag-2016-0042},
  file         = {:home/baffelli/Library/Butt, Wieser, Conzett - 2016 - Intrinsic random functions for mitigation of atmospheric effects in ground based radar interferometry.pdf:pdf},
  keywords     = {atmospheric correction,ferometry,ground based radar inter-,intrinsic,monitoring in alpine environment,random functions},
  publisher    = {Walter de Gruyter {GmbH}},
}

@Article{Weissgerber2016,
  author       = {Flora Weissgerber and Elise Colin-Koeniguer and Nicolas Trouve and Jean-Marie Nicolas},
  title        = {A Temporal Estimation of Entropy and Its Comparison With Spatial Estimations on {PolSAR} Images},
  journal      = {{IEEE} Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  journaltitle = {{IEEE} Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year         = {2016},
  date         = {2016-08},
  volume       = {9},
  month        = {aug},
  pages        = {3809--3820},
  doi          = {10.1109/jstars.2016.2555243},
  file         = {:FWeissgerber_JSTARS2016_article.pdf:PDF},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-30},
}

@Article{Colesanti2003,
  author       = {Colesanti, Carlo and Ferretti, Alessandro and Novali, Fabrizio and Prati, Claudio and Rocca, Fabio},
  title        = {{SAR} monitoring of progressive and seasonal ground deformation using the permanent scatterers technique},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  date         = {2003},
  volume       = {41},
  pages        = {1685--1701},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2003.813278},
  abstract     = {Spaceborne differential radar interferometry has proven a remarkable potential for mapping ground deformation phenomena (e.g., urban subsidence, volcano dynamics, coseismic and postseismic displacements along faults, as well as slope instability). However, a full operational capability has not been achieved yet due to atmospheric disturbances and phase decorrelation phenomena. These drawbacks can often be-at least partially-overcome by carrying out measurements on a subset of image pixels corresponding to natural or artificial stable reflectors [permanent scatterers (PS)] and exploiting long temporal series of interferometric data. This approach allows one to push the measurement precision very close to its theoretical limit (in the order of similar to1 mm for C-band European Remote Sensing (ERS)-like sensors). In this paper, the detection of both time-uniform and seasonal deformation phenomena is addressed, and a first assessment of the precision achievable by means of the PS Technique is discussed. Results highlighting deformation phenomena occurring in two test sites in California are reported (Fremont in the Southern Bay Area and San Jose in the Santa Clara Valley).},
  file         = {:home/baffelli/Library/Colesanti et al. - 2003 - SAR monitoring of progressive and seasonal ground deformation using the permanent scatterers technique.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Differential synthetic aperture radar (SAR) interf,Ground deformation monitoring,Permanent scatters},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-07-21},
}

@Article{Goldstein1995,
  author       = {Richard Goldstein},
  title        = {Atmospheric limitations to repeat-track radar interferometry},
  journaltitle = {Geophysical Research Letters},
  date         = {1995},
  volume       = {22},
  pages        = {2517--2520},
  issn         = {19448007},
  doi          = {10.1029/95GL02475},
  abstract     = {In its recent radar imaging mission, the Shuttle Imaging Radar satellite (SIR-C) devoted three days to repeat- track interferometry. We have analyzed the data from a test site in the Mojave desert of California. Although good topography (+10 m on 21 m postings) was obtained, most of the error was caused by turbulent water vapor in the lower atmosphere. Spatial structure of 6 km and all smaller sizes was observed. The RMS, one-way time delay was found to be 0.24 cm. Essentially identical results were obtained at two wavelengths, 24 and 5.7 cm},
  file         = {:home/baffelli/Library/Goldstein - 1995 - Atmospheric limitations to repeat track radar interferometry.pdf:pdf},
  isbn         = {0094-8276},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-07-30},
}

@Article{Kristensen2013,
  author       = {Kristensen, Lene and Rivolta, Carlo and Dehls, John and Blikra, Lars H},
  title        = {{GB InSAR} measurement at the {{\AA}knes} rockslide, {Norway}},
  journaltitle = {Italian Journal of Engineering Geology and Environment},
  date         = {2013},
  volume       = {2013},
  pages        = {339--348},
  issn         = {20355688},
  doi          = {10.4408/IJEGE.2013-06.B-32},
  url          = {www.ijege.uniroma1.it},
  file         = {:home/baffelli/Library/Kristensen et al. - Unknown - GB InSAR Measurement At The {AA}knes Rockslide, Norway.pdf:pdf},
  keywords     = {GB InSAR,Landslide,Monitoring,Rockslide,{\AA}knes},
}

@Article{Boogaart2001,
  author       = {van den Boogaart, Karl Gerald and Brenning, Alexander},
  title        = {Why Universal {Kriging} is better than {IRFk}-{Kriging} : Estimation of Variograms in the Presence of Trend},
  journaltitle = {Journal of Earth System Science},
  date         = {2001},
  pages        = {1--15},
  file         = {:home/baffelli/Library/Boogaart, Brenning - 2001 - Why Universal Kriging is better than IRFk-Kriging Estimation of Variograms in the Presence of Trend.pdf:pdf},
}

@InProceedings{Baffelli2016,
  author    = {Baffelli, Simone and Frey, Othmar and Hajnsek, Irena},
  title     = {System Characterization and Polarimetric Calibration of the {Ku}-Band Advanced Polarimetric Interferometer},
  booktitle = {Proceedings of the European Conference on Synthetic Aperture Radar},
  year      = {2016},
  date      = {2016},
  isbn      = {9783800742288},
  pages     = {2--5},
  abstract  = {{\textcopyright} VDE VERLAG GMBH {\textperiodcentered} Berlin {\textperiodcentered} Offenbach.This paper addresses the system characterization and the polarimetric calibration of the Ku-Band Advanced Polarimetric Interferometer (KAPRI). KAPRI is an FMCW ground-based real aperture radar system that uses slotted waveguide antennas. The rotation of the antennas introduces undesired phase ramps in azimuth. We present a geometrical model to account for this phase, and propose a method to correct it. Experimental data with a set of trihedral corner reflectors (TCR) in the scene was acquired with the system. A linear phase variation of 30 degrees was observed over the TCR which was geometrically modeled and successfully corrected.},
  file      = {:home/baffelli/Library/Baffelli, Frey, Hajnsek - 2016 - System Characterization and Polarimetric Calibration of the Ku- Band Advanced Polarimetric Interferomet.pdf:pdf},
}

@Article{Boerner1987,
  author       = {{Wolfgang-M.} Boerner and Bing-yuen Foo and Hyo Eom},
  title        = {Interpretation of the Polarimetric Co-Polarization Phase Term in Radar Images Obtained with the {JPL} Airborne {L}-Band {SAR} System},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {1987},
  volume       = {{GE}-25},
  month        = {jan},
  pages        = {77--82},
  doi          = {10.1109/tgrs.1987.289783},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-10-17},
}

@Article{Luzi2004,
  author       = {G. Luzi and M. Pieraccini and D. Mecatti and L. Noferini and G. Guidi and F. Moia and C. Atzeni},
  title        = {Ground-based radar interferometry for landslides monitoring: atmospheric and instrumental decorrelation sources on experimental data},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {IEEE Transactions on Geoscience and Remote Sensing},
  year         = {2004},
  date         = {2004},
  volume       = {42},
  month        = {nov},
  pages        = {2454--2466},
  issn         = {01962892},
  doi          = {10.1109/TGRS.2004.836792},
  abstract     = {The application of ground-based radar interferometry for landslide monitoring is analyzed: a case study based on an experimental campaign carried out in Italy during 2002 is discussed. Interferometric data obtained from coherent synthetic aperture radar (SAR) images acquired by means of C-band ground-based equipment are analyzed. The campaign was aimed at retrieving potential terrain movements of a small landslide observed hundreds of meters away. Critical aspects related to spatial and temporal decorrelation are discussed: the use of optical photogrammetry as a technique for evaluating mechanical stability and correcting geometric distortion is presented. Results also confirmed that the application of ground-based radar interferometry can be attractive and effective if the acquired SAR images maintain an adequate coherence on different dates.},
  file         = {:home/baffelli/Library/Luzi et al. - 2004 - Ground-based radar interferometry for landslides monitoring Atmospheric and instrumental decorrelation sources on e.pdf:pdf},
  isbn         = {0196-2892},
  keywords     = {Decorrelation,Differential interferometry,Ground-based synthetic aperture radar,Phase stability,Synthetic aperture radar (SAR)},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-08-02},
}

@Article{Touzi1999,
  author    = {R. Touzi and A. Lopes and J. Bruniquel and P.W. Vachon},
  title     = {Coherence estimation for {SAR} imagery},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {1999},
  volume    = {37},
  pages     = {135--149},
  doi       = {10.1109/36.739146},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-10-19},
}

@InProceedings{Pipia2009b,
  author    = {Luca Pipia and Xavier Fabregas and Albert Aguasca and Carlos Lopez-Martinez and Jordi J. Mallorqui},
  title     = {Polarimetric coherence optimization for interferometric differential applications},
  booktitle = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year      = {2009},
  date      = {2009},
  publisher = {{IEEE}},
  month     = {jul},
  doi       = {10.1109/igarss.2009.5417712},
  timestamp = {2018-10-20},
}

@InProceedings{Baffelli2018b,
  author    = {Simone Baffelli and Othmar Frey and Irena Hajnsek},
  title     = {Geostatistical analysis and mitigation of atmospheric phase screens in {Ku}-band terrestrial radar interferometry},
  booktitle = {Proceedings of the {IEEE} International Geoscience and Remote Sensing Symposium},
  year      = {2018},
  date      = {2018},
  doi       = {10.1109/IGARSS.2018.8517479},
  timestamp = {2018-10-25},
}

@InProceedings{,
  timestamp = {2018-10-25},
}

@InProceedings{Baffelli2017,
  author    = {Simone Baffelli and Othmar Frey and and Irena Hajnsek},
  title     = {Improved polarimetric calibration of {KAPRI}, a {Ku}-band ground-based polarimetric radar interferometer},
  booktitle = {Proceedings of PolInSAR},
  year      = {2017},
  date      = {2017},
  timestamp = {2018-10-25},
}

@Article{Baffelli2018d,
  author       = {Simone Baffelli and Othmar Frey and Irena Hajnsek},
  title        = {Polarimetric Analysis of Natural Terrain Observed With a {Ku}-Band Terrestrial Radar},
  journal      = {{IEEE} Journal of Selected Topics in Applied Earth Observation and Remote Sensing},
  journaltitle = {{IEEE} Journal of Selected Topics in Applied Earth Observation and Remote Sensing},
  year         = {2018},
  date         = {2018},
  note         = {submission {ID} {JSTARS-2018-00992}},
  timestamp    = {2018-10-25},
}

@InBook{Legendre1998,
  author    = {Pierre Legendre and Loic Legendre},
  title     = {Spatial Analysis},
  booktitle = {Numerical ecology 2nd English Edition},
  year      = {1998},
  editor    = {Elsevier},
  pages     = {712-738},
  timestamp = {2018-10-27},
}

@Article{Freeman1998,
  author    = {A. Freeman and S.L. Durden},
  title     = {A three-component scattering model for polarimetric {SAR} data},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {1998},
  volume    = {36},
  number    = {3},
  month     = {may},
  pages     = {963--973},
  doi       = {10.1109/36.673687},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-11-02},
}

@Article{Park2009,
  author    = {Sang-Eun Park and Wooil M. Moon and {Duk-jin} Kim},
  title     = {Estimation of Surface Roughness Parameter in Intertidal Mudflat Using Airborne Polarimetric {SAR} Data},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2009},
  volume    = {47},
  number    = {4},
  month     = {apr},
  pages     = {1022--1031},
  doi       = {10.1109/tgrs.2008.2008908},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-11-02},
}

@Article{Kim2018,
  author    = {Seung-Bum Kim and Huanting Huang and Tien-Hao Liao and Andreas Colliander},
  title     = {Estimating Vegetation Water Content and Soil Surface Roughness Using Physical Models of {L}-Band Radar Scattering for Soil Moisture Retrieval},
  journal   = {Remote Sensing},
  year      = {2018},
  volume    = {10},
  number    = {4},
  month     = {apr},
  pages     = {556},
  doi       = {10.3390/rs10040556},
  publisher = {{MDPI} {AG}},
  timestamp = {2018-11-02},
}

@Article{Shi1997,
  author    = {Jiancheng Shi and J. Wang and A.Y. Hsu and P.E. O{\textquotesingle}Neill and E.T. Engman},
  title     = {Estimation of bare surface soil moisture and surface roughness parameter using {L}-band {SAR} image data},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {1997},
  volume    = {35},
  number    = {5},
  pages     = {1254--1266},
  doi       = {10.1109/36.628792},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-11-02},
}

@Article{Lee2002,
  author       = {Jong-Sen Lee and D.L. Schuler and T.L. Ainsworth and E. Krogager and D. Kasilingam and W.-M. Boerner},
  title        = {On the estimation of radar polarization orientation shifts induced by terrain slopes},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2002},
  volume       = {40},
  number       = {1},
  pages        = {30--41},
  doi          = {10.1109/36.981347},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-11-03},
}

@Article{Turner2012,
  author       = {Dean Turner and Iain H. Woodhouse},
  title        = {An Icon-Based Synoptic Visualization of Fully Polarimetric Radar Data},
  journal      = {Remote Sensing},
  journaltitle = {Remote Sensing},
  year         = {2012},
  volume       = {4},
  number       = {3},
  month        = {mar},
  pages        = {648--660},
  doi          = {10.3390/rs4030648},
  publisher    = {{MDPI} {AG}},
  timestamp    = {2018-11-03},
}

@Article{Galletti2005,
  author       = {M. Galletti and M. Chandra and E. Pottier and A. Ghorbani},
  title        = {Application of the {Cloude-Pottier} decomposition to weather radar signatures},
  journal      = {Advances in Radio Science},
  journaltitle = {Advances in Radio Science},
  year         = {2005},
  volume       = {3},
  month        = {may},
  pages        = {413--420},
  doi          = {10.5194/ars-3-413-2005},
  publisher    = {Copernicus {GmbH}},
  timestamp    = {2018-11-03},
}

@Article{Shin1981,
  author    = {R. T. Shin and J. A. Kong},
  title     = {Radiative transfer theory for active remote sensing of a homogenous layer containing spherical scatterers},
  journal   = {Journal of Applied Physics},
  year      = {1981},
  volume    = {52},
  number    = {6},
  month     = {jun},
  pages     = {4221--4230},
  doi       = {10.1063/1.329271},
  publisher = {{AIP} Publishing},
  timestamp = {2018-11-05},
}

@Article{Bicout1992,
  author    = {Dominique Bicout and Christian Brosseau},
  title     = {Multiply scattered waves through a spatially random medium : entropy production and depolarization},
  journal   = {Journal de Physique {I}},
  year      = {1992},
  volume    = {2},
  number    = {11},
  month     = {nov},
  pages     = {2047--2063},
  doi       = {10.1051/jp1:1992266},
  publisher = {{EDP} Sciences},
  timestamp = {2018-11-05},
}

@Article{Frey2013,
  author       = {Othmar Frey and Maurizio Santoro and Charles L. Werner and Urs Wegmuller},
  title        = {{DEM}-Based {SAR} Pixel-Area Estimation for Enhanced Geocoding Refinement and Radiometric Normalization},
  journal      = {{IEEE} Geoscience and Remote Sensing Letters},
  journaltitle = {{IEEE} Geoscience and Remote Sensing Letters},
  year         = {2013},
  volume       = {10},
  number       = {1},
  month        = {jan},
  pages        = {48--52},
  doi          = {10.1109/lgrs.2012.2192093},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-11-05},
}

@Book{Massonnet2008,
  author    = {Didier Massonnet and Jean-Claude Souyris},
  title     = {Imaging with Synthetic Aperture Radar},
  year      = {2008},
  publisher = {{EPFL} Press},
  isbn      = {9780849382390},
  timestamp = {2018-11-05},
}

@Article{Lopez-Sanchez2000,
  author    = {J.M. Lopez-Sanchez and J. Fortuny-Guasch and S.R. Cloude and A.J. Sieber},
  title     = {Indoor Polarimetric Radar Measurements On Vegetation Samples At {L}, {S}, {C} and {X} band},
  journal   = {Journal of Electromagnetic Waves and Applications},
  year      = {2000},
  volume    = {14},
  number    = {2},
  month     = {jan},
  pages     = {205--231},
  doi       = {10.1163/156939300x00734},
  publisher = {Informa {UK} Limited},
  timestamp = {2018-11-05},
}

@Article{Delacourt1998,
  author       = {C. Delacourt and P. Briole and J. A. Achache},
  title        = {Tropospheric corrections of {SAR} interferograms with strong topography. Application to {Etna}},
  journal      = {Geophysical Research Letters},
  journaltitle = {Geophysical Research Letters},
  year         = {1998},
  volume       = {25},
  number       = {15},
  month        = {aug},
  pages        = {2849--2852},
  doi          = {10.1029/98gl02112},
  publisher    = {American Geophysical Union ({AGU})},
  timestamp    = {2018-11-06},
}

@Article{Touzi2007,
  author       = {R. Touzi},
  title        = {Target Scattering Decomposition in Terms of Roll-Invariant Target Parameters},
  journal      = {{IEEE} Transactions on Geoscience and Remote Sensing},
  journaltitle = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year         = {2007},
  volume       = {45},
  number       = {1},
  month        = {jan},
  pages        = {73--84},
  doi          = {10.1109/tgrs.2006.886176},
  publisher    = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp    = {2018-11-06},
}

@Article{Knospe2010,
  author    = {S. Knospe and S. Jonsson},
  title     = {Covariance Estimation for {dInSAR} Surface Deformation Measurements in the Presence of Anisotropic Atmospheric Noise},
  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
  year      = {2010},
  volume    = {48},
  number    = {4},
  month     = {apr},
  pages     = {2057--2065},
  doi       = {10.1109/tgrs.2009.2033937},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
  timestamp = {2018-12-08},
}

@Article{rothlisberger1981,
  author = {R{\"o}thlisberger, H and Kasser, P},
  title  = {Gletscher und Klima--glaciers et climat, Jahrbuch der Schweizerischen Naturforschenden Gesellschaft, wissenschaftlicher Teil 1978},
  year   = {1981},
}

@Article{Haeberli2004,
  author    = {Wilfried Haeberli and Christian Huggel and Andreas Kääb and Sonja Zgraggen-Oswald and Alexander Polkvoj and Igor Galushkin and Igor Zotikov and Nikolay Osokin},
  title     = {The Kolka-Karmadon rock/ice slide of 20 September 2002: an extraordinary event of historical dimensions in North Ossetia, Russian Caucasus},
  journal   = {Journal of Glaciology},
  year      = {2004},
  volume    = {50},
  number    = {171},
  pages     = {533--546},
  doi       = {10.3189/172756504781829710},
  publisher = {Cambridge University Press ({CUP})},
  timestamp = {2018-12-08},
}

@Article{Gringarten2001,
  author    = {Emmanuel Gringarten and Clayton V. Deutsch},
  title     = {Teacher's Aide Variogram Interpretation and Modeling},
  journal   = {Mathematical Geology},
  year      = {2001},
  volume    = {33},
  number    = {4},
  pages     = {507--534},
  doi       = {10.1023/a:1011093014141},
  publisher = {Springer Nature},
  timestamp = {2018-12-08},
}

@Comment{jabref-meta: databaseType:biblatex;}

@Comment{jabref-meta: fileDirectory:/home/baffelli/Library;}