{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:25:56Z","timestamp":1774121156512,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2019,10,16]],"date-time":"2019-10-16T00:00:00Z","timestamp":1571184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The transition towards a new sustainable energy model\u2014replacing fossil fuels with renewable sources\u2014presents 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\u00b7m\u22121 or higher.<\/jats:p>","DOI":"10.3390\/rs11202403","type":"journal-article","created":{"date-parts":[[2019,10,17]],"date-time":"2019-10-17T04:46:06Z","timestamp":1571287566000},"page":"2403","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Detection of Geothermal Potential Zones Using Remote Sensing Techniques"],"prefix":"10.3390","volume":"11","author":[{"given":"David","family":"Lago Gonz\u00e1lez","sequence":"first","affiliation":[{"name":"Department of Mining Technology, Topography and Structures, Universidad de Le\u00f3n, 24401 Ponferrada, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2657-813X","authenticated-orcid":false,"given":"Pablo","family":"Rodr\u00edguez-Gonz\u00e1lvez","sequence":"additional","affiliation":[{"name":"Department of Mining Technology, Topography and Structures, Universidad de Le\u00f3n, 24401 Ponferrada, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,16]]},"reference":[{"key":"ref_1","unstructured":"International Energy Agency (IEA) (2019, August 18). World Energy Balances 2018. Available online: https:\/\/webstore.iea.org\/world-energy-balances-2018."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.enpol.2012.09.033","article-title":"The transition towards renewable energies: Physical limits and temporal conditions","volume":"52","author":"Mediavilla","year":"2013","journal-title":"Energy Policy"},{"key":"ref_3","unstructured":"Council of the European Commission (2009). Directive 2009\/28\/EC of the European Parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001\/77\/EC and 2003\/30\/EC. Off. J. Eur. Union, 140, 16\u201362."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.energy.2017.03.070","article-title":"Methodology for estimating the ground heat absorption rate of Ground Heat Exchangers","volume":"127","author":"Stylianou","year":"2017","journal-title":"Energy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1016\/j.rser.2015.09.032","article-title":"Potential of geothermal energy for electricity generation in Indonesia: A review","volume":"53","author":"Alhamid","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.geothermics.2004.11.005","article-title":"CO2 emissions from geothermal power plants and natural geothermal activity in Iceland","volume":"34","author":"Armannsson","year":"2005","journal-title":"Geothermics"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s40517-016-0048-6","article-title":"Pre-drilling assessments of average porosity and permeability in the geothermal reservoirs of the Danish area","volume":"4","author":"Kristensen","year":"2016","journal-title":"Geotherm. Energy"},{"key":"ref_8","first-page":"265","article-title":"Prospecting for geothermal energy through satellite based thermal data: Review and the way forward","volume":"1","author":"Howari","year":"2015","journal-title":"Glob. J. Environ. Sci. Manag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"254","DOI":"10.5897\/JGRP2017.0643","article-title":"Low cost geothermal energy indicators and exploration methods in Kenya","volume":"10","author":"Macharia","year":"2017","journal-title":"J. Geogr. Reg. Plan."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1016\/j.geothermics.2014.09.002","article-title":"Remote sensing of geothermal-related minerals for resource exploration in Nevada","volume":"53","author":"Calvin","year":"2015","journal-title":"Geothermics"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1016\/j.rse.2006.09.001","article-title":"Detection of geothermal anomalies using advanced spaceborne thermal emission and reflection radiometer (ASTER) thermal infrared images at Bradys Hot Springs, Nevada, USA","volume":"106","author":"Coolbaugh","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.rse.2014.03.022","article-title":"Potential of ESA\u2019s Sentinel-2 for geological applications","volume":"148","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_13","first-page":"552","article-title":"Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis\u2014A case study in Tengchong, China","volume":"13","author":"Qin","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/j.energy.2017.09.012","article-title":"GIS-supported certainty factor (CF) models for assessment of geothermal potential: A case study of Tengchong County, southwest China","volume":"140","author":"Li","year":"2017","journal-title":"Energy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1016\/j.enbuild.2010.04.006","article-title":"A decision tree method for building energy demand modeling","volume":"42","author":"Yu","year":"2010","journal-title":"Energy Build."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1016\/j.jclepro.2018.08.207","article-title":"Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees","volume":"203","author":"Ahmad","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_17","unstructured":"Congedo, L. (2019, August 18). Semi-Automatic Classification Plugin Documentation. Available online: http:\/\/semiautomaticclassificationmanual-v5.readthedocs.io\/en\/latest\/remote_sensing.html#dos1-correction."},{"key":"ref_18","unstructured":"GDAL\/OGR contributors (2019, August 18). GDAL\/OGR Geospatial Data Abstraction software Library. Available online: http:\/\/gdal.org."},{"key":"ref_19","first-page":"1025","article-title":"Image-based atmospheric corrections-Revisited and improved","volume":"62","author":"Chavez","year":"1996","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/0034-4257(92)90076-V","article-title":"Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output","volume":"41","author":"Moran","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1016\/j.aqpro.2015.02.181","article-title":"Crop pattern mapping of Tumkur taluk using NDVI technique: A remote sensing and GIS approach","volume":"4","author":"Bharathkumar","year":"2015","journal-title":"Aquat. Procedia"},{"key":"ref_23","unstructured":"Jensen, J.R. (2015). Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice Hall Press."},{"key":"ref_24","unstructured":"Chuvieco Salinero, E. (2006). Teledetecci\u00f3n Ambiental: La Observaci\u00f3n de la TIERRA Desde el Espacio, Ariel."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Sauro, J., and Lewis, J.R. (2005, January 26\u201330). Estimating completion rates from small samples using binomial confidence intervals: Comparisons and recommendations. Proceedings of the human factors and ergonomics society annual meeting, Orlando, FL, USA.","DOI":"10.1037\/e577532012-007"},{"key":"ref_26","first-page":"136","article-title":"When 100% really isn\u2019t 100%: Improving the accuracy of small-sample estimates of completion rates","volume":"1","author":"Lewis","year":"2006","journal-title":"J. Usability Stud."},{"key":"ref_27","unstructured":"Measuring, U. (2019, August 18). Confidence Interval Calculator for a Completion Rate. Available online: https:\/\/measuringu.com\/wald\/."},{"key":"ref_28","unstructured":"Fridleifsson, I.B., Bertani, R., Huenges, E., Lund, J.W., Ragnarsson, A., and Rybach, L. (2008, January 20\u201325). The possible role and contribution of geothermal energy to the mitigation of climate change. Proceedings of the IPCC Scoping Meeting on Renewable Energy Sources, L\u00fcbeck, Germany."},{"key":"ref_29","first-page":"12","article-title":"Automatic surface temperature mapping in Arcgis using landsat-8 TIRS and ENVI tools, case study: Al Habbaniyah Lake","volume":"4","author":"Sameen","year":"2014","journal-title":"J. Environ. Earth Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/s12524-014-0373-9","article-title":"Estimation of the relationship between urban vegetation configuration and land surface temperature with remote sensing","volume":"43","author":"Zhibin","year":"2015","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/0034-4257(92)90096-3","article-title":"A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies","volume":"42","author":"Hook","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1080\/01431160050021358","article-title":"A new approach for temperature and emissivity separation","volume":"21","author":"Gillespie","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","unstructured":"Tarbuck, E.J., and Lutgens, F.K. (2005). Ciencias de la Tierra, Pearson Prentice Hall."},{"key":"ref_34","unstructured":"Spanish Geological Survey (2019, August 18). Vocabulary of Rocks, Sediments and Surface Formations. Available online: http:\/\/info.igme.es\/SidPDF\/167000\/386\/167386_0000001.pdf."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1046\/j.1365-246X.2003.01941.x","article-title":"Geodetic versus geophysical perspectives of the \u2018gravity anomaly\u2019","volume":"154","author":"Hackney","year":"2003","journal-title":"Geophys. J. Int."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1080\/02626667.2014.979174","article-title":"Geometry of the eastern Haouz and Tassaout aquifers, Western Morocco: Geophysical and hydrogeological approach","volume":"6","author":"Rochdane","year":"2015","journal-title":"Hydrol. Sci. J."},{"key":"ref_37","unstructured":"Hofmann-Wellenhof, B., and Moritz, H. (2006). Physical Geodesy, Springer Science & Business."},{"key":"ref_38","unstructured":"Pasteka, R., Mikuska, J., and Meurers, B. (2017). Understanding the Bouguer Anomaly: A Gravimetry Puzzle, Elsevier."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.jhydrol.2018.02.009","article-title":"Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification","volume":"559","author":"Goodall","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2011.11.002","article-title":"An assessment of the effectiveness of a random forest classifier for land-cover classification","volume":"67","author":"Ghimire","year":"2012","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s optical high-resolution mission for GMES operational services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1080\/014311600210326","article-title":"The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA\u2019s Terra platform","volume":"21","author":"Abrams","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_43","unstructured":"Spanish Geological Survey (2019, August 18). MAGNA 50-Geological Map of Spain, Scale 1:50.000. Available online: http:\/\/info.igme.es\/cartografiadigital\/geologica\/Magna50.aspx?language=en."},{"key":"ref_44","unstructured":"Llopis, G., and Rodrigo, V. (2008). Gu\u00eda de la Energ\u00eda Geot\u00e9rmica, Direcci\u00f3n general de la industria energ\u00eda, y minas, consejer\u00eda de econom\u00eda y consumo."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/S0377-0273(03)00418-9","article-title":"Heat flow, deep temperatures and extensional structures in the Larderello Geothermal Field (Italy): Constraints on geothermal fluid flow","volume":"132","author":"Bellani","year":"2004","journal-title":"J. Volcanol. Geotherm. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"8190109","DOI":"10.1155\/2017\/8190109","article-title":"Fault-related controls on upward hydrothermal flow: An integrated geological study of the T\u00eat fault system, Eastern Pyr\u00e9n\u00e9es (France)","volume":"2017","author":"Taillefer","year":"2017","journal-title":"Geofluids"},{"key":"ref_47","unstructured":"(2019, October 16). Bureau Gravimetrique International (BGI). Available online: http:\/\/bgi.omp.obs-mip.fr\/data-products\/Gravity-Databases\/Land-Gravity-data."},{"key":"ref_48","first-page":"159","article-title":"The International Renewable Energy Agency: A success story in institutional innovation?","volume":"15","author":"Urpelainen","year":"2015","journal-title":"Int. Environ. Agreem. Pol. Law Econ."},{"key":"ref_49","unstructured":"(2019, August 18). International Renewable Energy Agency (IRENA). Available online: https:\/\/irena.masdar.ac.ae\/geoserver\/ows?service=wms&version=1.3.0&request=GetCapabilities."},{"key":"ref_50","unstructured":"(2019, August 18). Spanish Institute for the Diversification and Saving of Energy (IDEA). Available online: http:\/\/www.idae.es\/."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/j.rser.2015.11.070","article-title":"The geothermal potential in Spain","volume":"56","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_52","unstructured":"European Space Agency (ESA) (2019, August 18). Copernicus Open Access Hub. Available online: https:\/\/scihub.copernicus.eu\/."},{"key":"ref_53","unstructured":"National Aeronautics and Space Administration (NASA) (2019, August 18). Earth Observation Data, Available online: https:\/\/earthdata.nasa.gov\/."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Bakar, Z.A., Mohemad, R., Ahmad, A., and Deris, M.M. (2006, January 7\u20139). A comparative study for outlier detection techniques in data mining. Proceedings of the 2006 IEEE Conference on Cybernetics and Intelligent Systems, Bangkok, Thailand.","DOI":"10.1109\/ICCIS.2006.252287"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/0377-0273(86)90015-6","article-title":"Gravity fields and the interpretation of volcanic structures: Geological discrimination and temporal evolution","volume":"27","author":"Rymer","year":"1986","journal-title":"J. Volcanol. Geotherm. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.jafrearsci.2019.02.005","article-title":"Assessing the geothermal potential of the Shahin Dezh Region, based on the geological, geochemical and geophysical evidence","volume":"152","author":"Ebrahimi","year":"2019","journal-title":"J. Afr. Earth Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.rse.2017.10.003","article-title":"Detecting geotermal anomalies and evaluating LST geotermal component by combining termal remote sensing time series and land Surface model data","volume":"204","author":"Romaguera","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.2517-6161.1974.tb00994.x","article-title":"Cross-validatory choice and assessment of statistical predictions","volume":"3","author":"Stone","year":"1974","journal-title":"J. R. Stat. Soc."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","article-title":"The use of the area under the ROC curve in the evaluation of machine learning algorithms","volume":"30","author":"Bradley","year":"1997","journal-title":"Pattern Recognit."},{"key":"ref_60","unstructured":"Hempstalk, K., Frank, E., and Witten, I.H. (2008, January 15\u201319). One-class classification by combining density and class probability estimation. Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Antwerp, Belgium."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"3137","DOI":"10.1080\/01431160701442120","article-title":"Harshness in image classification accuracy assessment","volume":"29","author":"Foody","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"14714","DOI":"10.1109\/ACCESS.2019.2891367","article-title":"Weld Bead Detection Based on 3D Geometric Features and Machine Learning Approaches","volume":"7","year":"2019","journal-title":"IEEE Access"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Del Pozo, S., Lindenbergh, R., Rodr\u00edguez-Gonz\u00e1lvez, P., Blom, J.K., and Gonz\u00e1lez-Aguilera, D. (2015). Discrimination between sedimentary rocks from close-range visible and very-near-infrared images. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0132471"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/20\/2403\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:27:00Z","timestamp":1760189220000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/20\/2403"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,16]]},"references-count":63,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["rs11202403"],"URL":"https:\/\/doi.org\/10.3390\/rs11202403","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,16]]}}}