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Burned area detection based on time-series analysis in a cloud computing environment [Identificación de áreas quemadas mediante el análisis de series de tiempo en el ámbito de computación en la nube]

dc.creatorAnaya J.A.spa
dc.creatorSione W.F.spa
dc.creatorRodríguez-Montellano A.M.spa
dc.date.accessioned2018-10-31T13:09:07Z
dc.date.available2018-10-31T13:09:07Z
dc.date.created2018
dc.identifier.issn11330953
dc.identifier.urihttp://hdl.handle.net/11407/4844
dc.description"There are large omission errors in the estimation of burned area in map products that are generated at a global scale. This error is then inherited by other models, for instance, those used to report Greenhouse Gas Emissions using a ""bottom up"" approach. This study evaluates temporal methods to improve burned area detection using Landsat 5-TM and 8-OLI. In this process, the normalized burn ratio (NBR) was used to highlight burned areas and thresholds to classify burned and non-burned areas. In order to maximize the burned area detection two alternatives to the temporal dNBR method were evaluated: the relative form of the temporal difference RdNBR and the use of time series metrics. The processing, algorithm development and access to Landsat data was made on the Google Earth Engine GEE platform. Three regions of Latin America with large fire occurrence were selected: The Amazon Forest in Colombia, the transition from Chiquitano to Amazon Forest in Bolivia, and El Chaco Region in Argentina. The accuracy assessment of these new products was based on burned area protocols. The best model classified 85% of burned areas in the Chiquitano Forests of Bolivia, 63% of the burned areas of the Amazon Forests of Colombia and 69% of burned areas in El Chaco of Argentina. © 2018, Universitat Politecnica de Valencia. All rights reserved."spa
dc.language.isospa
dc.publisherUniversitat Politecnica de Valenciaspa
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85050281405&doi=10.4995%2fraet.2018.8618&partnerID=40&md5=f204a2cef210b2f82386251edbe0be7bspa
dc.sourceScopusspa
dc.subjectBurned areaspa
dc.subjectCloud computingspa
dc.subjectFiresspa
dc.subjectGEEspa
dc.subjectNBRspa
dc.titleBurned area detection based on time-series analysis in a cloud computing environment [Identificación de áreas quemadas mediante el análisis de series de tiempo en el ámbito de computación en la nube]spa
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería Ambientalspa
dc.contributor.affiliationAnaya, J.A., Universidad de Medellín;Sione, W.F., Universidad Autónoma de Entre Ríos;Rodríguez-Montellano, A.M., Fundación Amigos de la Naturaleza; Universidad Autónoma Gabriel René Morenospa
dc.identifier.doi10.4995/raet.2018.8618
dc.relation.citationvolume2018
dc.relation.citationissue51
dc.relation.citationstartpage61
dc.relation.citationendpage73
dc.publisher.facultyFacultad de Ingenieríasspa
dc.relation.ispartofesRevista de Teledeteccionspa
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dc.type.driverinfo:eu-repo/semantics/article


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