Spatiotemporally Characterized Ground-Mounted Solar PV Arrays Within California's Central Valley

When using this dataset, please cite the peer-reviewed publication found here: https://doi.org/10.1016/j.scitotenv.2022.155240Literature on PV array installations lacks important spatiotemporal details that could help inform future array installations and improve associated policies and incentive programs. Here, we used imagery from the National Agriculture Imagery Program for object based analysis (within eCognition Developer), and imagery from Landsat 5 TM, 7 ETM+ and 8 OLI for temporal analysis (using LandTrendr) to identify and characterize non-residential ground-mounted solar PV arrays in California's Central Valley installed between 2008 and 2018. This dataset includes 210,368 individually identified panels grouped by mount and installation year into 1006 PV arrays. The dataset (PV_ID_panels.shp, PV_ID_CV.csv, & PV_ID_CV.shp) contains the geospatial coordinates, boundaries, installation years, calculated capacity, modeled electricity generation, prior land use, packing factor, mount technology, and other derived attributes (50 in total) for these installations.Dataset applications include land cover analysis, information extraction from existing PV arrays, and training machine learning and object detection algorithms to acquire PV spatiotemporal attributes elsewhere and in updated imagery.