For GIS professionals, obtaining high-precision, global distribution data for energy facilities—particularly emerging sources like photovoltaics (PV) and wind power—is often challenging. While open-source maps like OpenStreetMap provide some data, they frequently fall short in terms of timeliness, coverage, and attribute detail required for rigorous scientific research or commercial analysis. Recently, Microsoft, in collaboration with organizations like The Nature Conservancy (TNC), launched a significant open-source project on GitHub called the Global Renewables Watch (GRW). The research team utilized high-resolution satellite imagery and deep learning image segmentation models to conduct a quarterly analysis of global high-resolution satellite images from Q4 2017 to Q2 2024. This process automatically identified PV and wind power installations worldwide, accompanied by estimated construction dates and pre-construction land use information.
Data Overview
Coverage: Globally processed
Data Volume: Over 13 trillion pixels
Detections:
- PV Power Plants: 86,410
- Wind Turbines: 375,197
Data Format: gpkg (GeoPackage)
Temporal Range: Q4 2017 to Q2 2024