Satellite imagery is used for many activities in different areas of the planet, including searching for alternative and sustainable sources to meet growing energy demand to reduce greenhouse gas (GHG) emissions. One way to minimize these effects and expand energy parks is to encourage local generation through the use of renewable sources, such as solar energy, which is free and affordable in many regions of the planet, but that in Brazil is not yet a reality. In order to make an assertive decision when installing a solar power system, one needs to use tools that involve remote sensing and geographic information systems (GIS), and compile information and variables that are relevant to the subject of solar power generation and take into account the inherent geographic space. In this context, the main objective of this work is to develop a GIS model to identify areas with solar potential on a regional scale using active remote sensor images and previously available solar models. To validate the model, this study used an area on the island part of the city of Florianópolis in Santa Catarina State—Brazil, which suffers from repeated climatic events which cause long power cuts, as its distribution occurs by air all over the island. Through the “solar analist” function of ArcGIS and the matrix bases derived from the Digital Model of the Space Shuttle Topography Mission (SRTM) with 30 m of spatial resolution and the supervised classification of panthromatic and multispectral images fused from LandSat 8 satellite, were generates indicative maps of the areas with solar potential. The results pointed to a high solar potential in the all year and that could be better explored by public managers and also by individual consumers.
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