This project explores the potential for rooftop solar photovoltaic (PV) deployment in South Carolina by using remote sensing (e.g. satellite imagery) and machine learning coupled with cyber GIS to identify suitable locations for rooftop solar across the state.
An initial assessment of Clemson's main campus has already been conducted, which identified a number of high-value locations. This project will expand on that analysis by using known building footprints on campus to conduct supervised image classification to identify and calculate suitable rooftop area across the state.
This project is being undertaken with help from Clemson Center for Geospatial Technologies. Results from this project will be coupled with the Center's Solar Radiation Analysis for South Carolina, to determine the performance characteristics of solar deployed across the state.