An enhanced and harmonized US ground-mounted solar array and panel-row dataset spanning commercial and utility scales

Solar energy generating systems are a critical component of net-zero infrastructure, yet comprehensive datasets characterizing systems remain incomplete or not publicly available, particularly at the sub-array level. Leveraging the best freely available existing solar datasets in the US with object-based image analysis and machine learning, we present the Ground-Mounted Solar Energy in the United States (GM-SEUS) dataset, a harmonized, open access, and regularly updated geospatial and temporal repository of solar energy arrays and panel-rows. GM-SEUS v1.0 includes nearly 15,000 commercial- and utility-scale ground-mounted solar photovoltaic and concentrating solar energy arrays (~115 GWDC) covering 2,900 km2 and includes 2.93 million unique solar panel-rows (471 km2) within those arrays. Importantly, we include commercial-scale (1 MW). We use these newly compiled and delineated solar panel-rows to fill gaps in, and contribute several value-added attributes to, existing datasets, enhancing consistency across spatiotemporal attributes. Value-added attributes include installation year, azimuth, mount technology, panel-row area and dimensions, inter-row spacing, ground cover ratio, tilt, and installed capacity. By estimating and harmonizing these spatial and temporal attributes of the distributed US solar energy landscape, GM-SEUS supports diverse applications in renewable energy modeling, ecosystem service assessment, and infrastructural planning.