Published on: April 2026
SOLAR SIGHT - SOLAR ENERGY POTENTIAL MAPPING USING SATELLITE IMAGERY AND GEOSPATIAL ANALYSIS
Palak Maurya Tanish Poddar Vijayakumaran C
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Abstract
SolarSight is an automated geospatial intelligence system which finds and ranks best rooftop sites to place solar photovoltaic systems on high-resolution satellite imagery and spatial tools. The system combines 10-meter Sentinel- 2 imagery that is available on Google Earth Engine with building footprint data retrieved on the OpenStreetMap to conduct building-scale solar potential assessment. A single line of pipeline processes multi-spectral imagery, mask clouds, calculates solar energy, calculates rooftop areas and predicts energy in the end year. The platform produces prioritized tabular reports, spatial GeoJson productions, and suitability maps of themes to support planning of renewable energy. The system is put in place in Python through the GeoPandas ecosystem; a monolithic architecture of batch-processing. Its ability to handle large datasets of urbanistic scale without manual processing and operate in prototype in an inescapable city setting demonstrates that it can be used to help make data-based decisions about solar infrastructure planning and sustainable energy implementation.
How to Cite this Paper
Maurya, P., Poddar, T. & C, V. (2026). Solar Sight - Solar Energy Potential Mapping using Satellite Imagery and Geospatial Analysis. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.772
Maurya, Palak, et al.. "Solar Sight - Solar Energy Potential Mapping using Satellite Imagery and Geospatial Analysis." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.772.
Maurya, Palak,Tanish Poddar, and Vijayakumaran C. "Solar Sight - Solar Energy Potential Mapping using Satellite Imagery and Geospatial Analysis." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.772.
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