ArticleScientific reports2025
Satellite-based analysis uncovers uneven solar PV distribution across Japan and its consumption of forest and agricultural lands.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The recent development of solar photovoltaics (PV) has generated considerable interest in energy management, appropriate environmental impact assessment, and the seamless integration of PV technology into society. A critical first step in exploring these research opportunities is the creation of a comprehensive PV database that describes the locations and extents of existing PV installations. Automated solar PV detection in satellite remote sensing, based on a machine learning approach, is particularly suitable for studying the characteristics of national-scale solar PV distribution and its impact on the environment. In our study, we first proposed an XGBoost-based solar PV detection with post-processing procedures supported by a dedicated solar PV spectral index. This approach was applied to Sentinel-2 images acquired in 2022 to create a national solar PV database in Japan. The resulting solar PV map showed a high degree of accuracy, with an overall accuracy of 0.984. Our dataset revealed the presence of solar PVs covering a total area of 571 km
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