Detection of Geothermal Potential Zones Using Remote Sensing Techniques Lago González, David Rodríguez-Gonzálvez, Pablo Ingeniería Cartografica, Geodesica y Fotogrametria Escuela Superior y Tecnica de Ingenieros de Minas Cartografía Geothermal energy Remote Sensing Renewable energy Gravimetric anomalies Random forest 21 p. The transition towards a new sustainable energy model—replacing fossil fuels with renewable sources—presents a multidisciplinary challenge. One of the major decarbonization issues is the question of to optimize energy transport networks for renewable energy sources. Within the range of renewable energies, the location and evaluation of geothermal energy is associated with costly processes, such as drilling, which limit its use. Therefore, the present research is aimed at applying different geomatic techniques for the detection of geothermal resources. The workflow is based on free/open access geospatial data. More specifically, remote sensing information (Sentinel-2A and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), geological information, distribution of gravimetric anomalies, and geographic information systems have been used to detect areas of shallow geothermal potential in the northwest of the province of Orense, Spain. Due to the variety of parameters involved, and the complexity of the classification, a random forest classifier was employed, since this algorithm works well with large sets of data and can be used with categorical and numerical data. The results obtained allowed identifying a susceptible area to be operated on with a geothermal potential of 80 W·m−1 or higher SI 2019-10-16 2020-08-11T22:47:54Z 2020-08-11T22:47:54Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2072-4292 http://hdl.handle.net/10612/12345 https://doi.org/10.3390/rs11202403 eng info:eu-repo/semantics/openAccess MDPI https://buleria.unileon.es/bitstream/10612/12345/4/remotesensing-11-02403-v2.pdf.jpg Hispana TEXT http://rightsstatements.org/vocab/CNE/1.0/ BULERIA. Repositorio Institucional de la Universidad de León http://hdl.handle.net/10612/12345