So they get their off-grid hidey-holes all set up with solar power, and then researchers use satellites and AI to map all the panels in the United States. Now that someone can measure them, the next step will be to tax them to support the suffering power and petro companies, right? /s
DeepSolar: A Machine Learning Framework to Efficiently Construct a Solar Deployment Database in the United States
Highlights
- An accurate deep learning model for detecting solar panel on satellite imagery
- Built a nearly complete solar installation database for the contiguous US
- Identified key socioeconomic factors correlating with solar deployment density
- A predictive model to estimate solar deployment density at census tract level
Context & Scale
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.
