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dc.contributorEscuela Superior y Tecnica de Ingenieros de Minases_ES
dc.contributor.authorLago González, David
dc.contributor.authorRodríguez-Gonzálvez, Pablo
dc.contributor.otherIngeniería Cartografica, Geodesica y Fotogrametriaes_ES
dc.date2019-10-16
dc.date.accessioned2020-08-11T22:47:54Z
dc.date.available2020-08-11T22:47:54Z
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/10612/12345
dc.description21 p.es_ES
dc.description.abstractThe 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 higheres_ES
dc.languageenges_ES
dc.publisherMDPIes_ES
dc.subjectCartografíaes_ES
dc.subject.otherGeothermal energyes_ES
dc.subject.otherRemote Sensinges_ES
dc.subject.otherRenewable energyes_ES
dc.subject.otherGravimetric anomalieses_ES
dc.subject.otherRandom forestes_ES
dc.titleDetection of Geothermal Potential Zones Using Remote Sensing Techniqueses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doihttps://doi.org/10.3390/rs11202403
dc.description.peerreviewedSIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleRemote Sensinges_ES
dc.volume.number11es_ES
dc.issue.number20es_ES
dc.page.initial2403:1es_ES
dc.page.final2403:21es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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