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Identification and Solar Potential Estimation Using Machine Learning and Sentinel-2 Satellite Imagery in Rural Regions of Colombia and Chile

DOI: 10.4236/epe.2026.1810029, PP. 635-650

Keywords: Sentinel-2, MaxEnt, Copernicus, Machine Learning, Photovoltaic Tool, Remote Sensing, Rooftop Solar PV, Distributed Generation, Energy Transition, Colombia, Chile

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Abstract:

This paper applies a MaxEnt classification workflow to Sentinel-2 spectral bands and derived indices to map rooftops, non-intervened land, and intervened land across selected rural areas in Colombia and Chile. The study compares detected rooftop counts with housing-census counts and links the classification output to a photovoltaic screening tool. It identifies cloud cover, snow-related spectral confusion, and roof geometry as important constraints on wider application.

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