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dc.creatorClerici, Nicola 
dc.creatorCalderón, Cesar Augusto Valbuena 
dc.creatorPosada, Juan M. 
dc.date.accessioned2020-05-25T23:56:18Z
dc.date.available2020-05-25T23:56:18Z
dc.date.created2017
dc.identifier.issn17445647
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22391
dc.description.abstract"Land cover–land use (LCLU) classification tasks can take advantage of the fusion of radar and optical remote sensing data, leading generally to increase mapping accuracy. Here we propose a methodological approach to fuse information from the new European Space Agency Sentinel-1 and Sentinel-2 imagery for accurate land cover mapping of a portion of the Lower Magdalena region, Colombia. Data pre-processing was carried out using the European Space Agency’s Sentinel Application Platform and the SEN2COR toolboxes. LCLU classification was performed following an object-based and spectral classification approach, exploiting also vegetation indices. A comparison of classification performance using three commonly used classification algorithms was performed. The radar and visible-near infrared integrated dataset classified with a Support Vector Machine algorithm produce the most accurate LCLU map, showing an overall classification accuracy of 88.75%, and a Kappa coefficient of 0.86. The proposed mapping approach has the main advantages of combining the all-weather capability of the radar sensor, spectrally rich information in the visible-near infrared spectrum, with the short revisit period of both satellites. The mapping results represent an important step toward future tasks of aboveground biomass and carbon estimation in the region. © 2017 The Author(s)."
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.relation.ispartofJournal of Maps, ISSN:17445647, Vol.13, No.2 (2017); pp. 718-726
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85038228468&doi=10.1080%2f17445647.2017.1372316&partnerID=40&md5=b095970f6a068cdebb7d84290bad8366
dc.sourceinstname:Universidad del Rosario
dc.sourcereponame:Repositorio Institucional EdocUR
dc.title"Fusion of sentinel-1a and sentinel-2A data for land cover mapping: A case study in the lower Magdalena region, Colombia"
dc.typearticle
dc.publisherTaylor and Francis Ltd.
dc.subject.keywordColombia
dc.subject.keywordData fusion
dc.subject.keywordLand cover mapping
dc.subject.keywordSegmentation
dc.subject.keywordSentinel-1
dc.subject.keywordSentinel-2
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.type.spaArtículo
dc.rights.accesoAbierto (Texto Completo)
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doihttps://doi.org/10.1080/17445647.2017.1372316
dc.relation.citationEndPage726
dc.relation.citationIssueNo. 2
dc.relation.citationStartPage718
dc.relation.citationTitleJournal of Maps
dc.relation.citationVolumeVol. 13


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