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dc.contributor.authorPérez Álvarez, Rubén 
dc.contributor.authorSedano Cibrián, Javier 
dc.contributor.authorLuis Ruiz, Julio Manuel de 
dc.contributor.authorFernández Maroto, Gema 
dc.contributor.authorPereda García, Raúl 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2022-03-09T12:28:13Z
dc.date.available2022-03-09T12:28:13Z
dc.date.issued2022-01-25
dc.identifier.issn2075-163X
dc.identifier.urihttp://hdl.handle.net/10902/24182
dc.description.abstractThe depletion of natural resources implies the need for a constant search for new reserves to satisfy demand. In the mining sector, Unmanned Aerial Vehicles (UAVs) have revolutionised geo-information capture and modelling to allow the use of low-cost sensors for prospecting and exploration for potentially exploitable resources. A very powerful alternative for managing the huge volume of data is the Geographic Information System (GIS), which allows storage, visualisation, analysis, processing and map creation. The research in this paper validates a new quasi-automatic identification of mining resources using GIS thermal-image analysis obtained from UAVs and low-cost sensors. It was tested in a case that differentiated limestone from dolostone with varying iron content, and different thermal behaviour from solar radiation, thereby ensuring that the thermal image recorded these differences. The objective is to discriminate differences in an image in a quasi-automatic way using GIS tools and ultimately to determine outcrops that could contain mineralisation. The comparison between the proposed method with traditional precision alternatives offered differences of only 4.57%, a very small deviation at this early stage of exploration. Hence, it can be considered very suitablees_ES
dc.format.extent20 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution 4.0 International © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceMinerals 2022, 12(2), 140es_ES
dc.subject.otherProspectinges_ES
dc.subject.otherDronees_ES
dc.subject.otherPhotogrammetryes_ES
dc.subject.otherThermographyes_ES
dc.subject.otherReclassificationes_ES
dc.subject.otherThermal mappinges_ES
dc.titleMining exploration with UAV, low-cost thermal cameras and GIS tools. Application to the specific case of the complex sulfides hosted in carbonates of Udías (Cantabria, Spain)es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.3390/min12020140
dc.type.versionpublishedVersiones_ES


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Mostrar el registro sencillo

Attribution 4.0 International © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.