PCA4CD is a QGIS plugin that computes Principal Component Analysis (PCA) and can create a change detection layer using PCA's dimensionality reduction properties. Designed mainly with the goal of:
- Generate (or load) the principal components (PCA) of the input layers
- (optional) Build the change detection layer based on the dimensionality reduction properties of PCA.
Read more in: https://smbyc.github.io/PCA4CD
PCA4CD requires additional Python packages, that are generally not part of QGIS's Python, however the plugin has all the libs and dependencies inside, it must work on a 64bit system. The libraries are:
- Python-Dask
- PyQtGraph
Warning: This plugin only works in Qgis version >= 3.18
If you have issues with this try with the alternative installation below.
If you have problems with the dependencies, the best options to solve it is use conda and install Arosics and Qgis (from the conda shell):
conda install -c conda-forge dask pyqtgraph qgisAfter that open Qgis from the shell with qgis command. Then install the plugin.
Source code, issue tracker, QA and ideas: https://github.com/SMByC/PCA4CD The home plugin in plugins.qgis.org: https://plugins.qgis.org/plugins/pca4cd/
PCA4CD was developing, designed and implemented by the Group of Forest and Carbon Monitoring System (SMByC), operated by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) - Colombia.
Author and developer: Xavier C. Llano [email protected]
Theoretical support, tester and product verification: SMByC-PDI group
PCA4CD is a free/libre software and is licensed under the GNU General Public License.