This repository contains Python and R code used to analyze spatio-temporal patterns of solar energy buildout within the Chesapeake Bay watershed. Python code was used to process solar array vector data and join geospatial covariate values to polygons. R code was used to fit hierarchical Bayesian models estimating the relationships between geospatial covariates (e.g. land cover, state, distance to transmission lines) and the rate of solar development.
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Repository containing code to analyze patterns of solar energy development in the Chesapeake Bay watershed
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- R 65.2%
- Python 17.9%
- Jupyter Notebook 16.9%