Analyzing Solar Photovoltaic Farm Suitability for Properties in North Carolina & South Carolina
| dc.contributor.author | Durham, Brian | |
| dc.date.accessioned | 2019-08-15T15:11:13Z | |
| dc.date.available | 2019-08-15T15:11:13Z | |
| dc.date.issued | 2019-05 | |
| dc.description.abstract | As we witness the impacts of the climate crisis continue to become more severe, it is essential for the public and private sectors of the United States to begin rapidly transitioning to clean energy sources to meet its commitments of the Paris Climate Accord (“USA | Climate Action Tracker,” 2019). This study uses Multi-Criteria Decision Making (MCDM) with the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) to locate land and property owners within North and South Carolina most suitable for solar photovoltaic (PV) farm development. A geoprocessing model was built using ESRI’s ArcGIS software to assign levels of importance to various GIS layers of the natural and built environment. The model successfully identifies existing solar PV farms as ideal sites for development while locating thousands of additional acres suitable for solar PV farm development throughout both states. This suitability dataset should help solar development teams works more efficiently. Ideally, more efficient solar development teams will be able to complete more projects, leading to more clean energy on the grid and a faster reduction of our greenhouse gas emissions. | en_US |
| dc.identifier.uri | http://jhir.library.jhu.edu/handle/1774.2/61837 | |
| dc.language.iso | en_US | en_US |
| dc.subject | GIS | en_US |
| dc.subject | solar | en_US |
| dc.subject | suitability | en_US |
| dc.subject | development | en_US |
| dc.title | Analyzing Solar Photovoltaic Farm Suitability for Properties in North Carolina & South Carolina | en_US |
| dc.type | Other | en_US |