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Solo Metadatos
Fusion of sentinel-1a and sentinel-2A data for land cover mapping: A case study in the lower Magdalena region, Colombia
dc.creator | Clerici, Nicola | |
dc.creator | Calderón, Cesar Augusto Valbuena | spa |
dc.creator | Posada Hostettler, Juan Manuel Roberto | |
dc.date.accessioned | 2020-05-25T23:56:18Z | |
dc.date.available | 2020-05-25T23:56:18Z | |
dc.date.created | 2017 | spa |
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). | eng |
dc.format.mimetype | application/pdf | |
dc.identifier.doi | https://doi.org/10.1080/17445647.2017.1372316 | |
dc.identifier.issn | 17445647 | |
dc.identifier.uri | https://repository.urosario.edu.co/handle/10336/22391 | |
dc.language.iso | eng | spa |
dc.publisher | Taylor and Francis Ltd. | spa |
dc.relation.citationEndPage | 726 | |
dc.relation.citationIssue | No. 2 | |
dc.relation.citationStartPage | 718 | |
dc.relation.citationTitle | Journal of Maps | |
dc.relation.citationVolume | Vol. 13 | |
dc.relation.ispartof | Journal of Maps, ISSN:17445647, Vol.13, No.2 (2017); pp. 718-726 | spa |
dc.relation.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038228468&doi=10.1080%2f17445647.2017.1372316&partnerID=40&md5=b095970f6a068cdebb7d84290bad8366 | spa |
dc.rights.accesRights | info:eu-repo/semantics/openAccess | |
dc.rights.acceso | Abierto (Texto Completo) | spa |
dc.source.instname | instname:Universidad del Rosario | spa |
dc.source.reponame | reponame:Repositorio Institucional EdocUR | spa |
dc.subject.keyword | Colombia | spa |
dc.subject.keyword | Data fusion | spa |
dc.subject.keyword | Land cover mapping | spa |
dc.subject.keyword | Segmentation | spa |
dc.subject.keyword | Sentinel-1 | spa |
dc.subject.keyword | Sentinel-2 | spa |
dc.title | Fusion of sentinel-1a and sentinel-2A data for land cover mapping: A case study in the lower Magdalena region, Colombia | spa |
dc.type | article | eng |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | |
dc.type.spa | Artículo | spa |