DeepSolar

We built a nearly complete solar installation database for the contiguous US utilizing a novel deep learning model applied to satellite imagery. The data are published as the first publicly available, high-fidelity solar installation database in the contiguous US. We plan to update it annually and add other countries and regions of the world. We demonstrated the value of this database by identifying key environmental and socioeconomic factors correlated with solar deployment. We also developed high-accuracy machine learning models to predict solar deployment density utilizing these factors as input. We hope the data produced by DeepSolar can aid researchers, policymakers, and the industry in gaining a better understanding of solar adoption and its impacts.

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