Landsat-based remote sensing of the colored dissolved organic matter absorption coefficient in a tropical oligotrophic reservoir

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dc.contributor.authorWatanabe, Fernanda [UNESP]
dc.contributor.authorAlcântara, Enner [UNESP]
dc.contributor.authorCurtarelli, Marcelo
dc.contributor.authorKampel, Milton
dc.contributor.authorStech, José
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de Santa Catarina (UFSC)
dc.contributor.institutionINPE - National Institute for Space Research
dc.date.accessioned2018-12-11T17:19:10Z
dc.date.available2018-12-11T17:19:10Z
dc.date.issued2018-01-01
dc.description.abstractColored dissolved organic matter (CDOM) is a photoactive fraction of organic carbon that can be detected via remotely sensed data (proximal and satellite). The retrieval of the absorption coefficient of CDOM (aCDOM) in reservoirs is important because it is related to the carbon budget and is a possible source of greenhouse gas that is emitted from aquatic ecosystems. In this context, we divided this study into three steps: (1) evaluating four retrieval algorithms for aquatic CDOM proposed for different types of waters; (2) recalibrating the algorithms using field data; and (3) adjusting new algorithms based on Landsat 5 TM bands. This research aimed to evaluate the use of Landsat 5 TM images for retrieving aCDOM in oligotrophic inland waters. The best performing model in the literature exhibited a normalized root mean square error (NRMSE) value of 29.5% and a mean absolute percentage error (MAPE) value of 25.4%, showing that some models proposed for marine water may be applied to specific inland waters. After recalibration, the best result was NRMSE = 29.9% and MAPE = 24.8%. The Landsat 5 TM bands yielded accurate results (NRMSE = 26.2% and MAPE = 33.6%), which indicated the potential for using Landsat data to monitor the bio-optical properties in inland waters.en
dc.description.affiliationDepartment of Cartography UNESP - São Paulo State University, Rua Roberto Simonsen 305
dc.description.affiliationDepartment of Environmental Engineering UNESP - São P aulo State University, Rodovia Presidente Dutra Km. 137.8
dc.description.affiliationCERTI Foundation Green Economy Center. UFSC - Federal University of Santa Catarina
dc.description.affiliationRemote Sensing Division INPE - National Institute for Space Research, Avenida dos Astronautas 1758
dc.description.affiliationUnespDepartment of Cartography UNESP - São Paulo State University, Rua Roberto Simonsen 305
dc.description.affiliationUnespDepartment of Environmental Engineering UNESP - São P aulo State University, Rodovia Presidente Dutra Km. 137.8
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFAPESP: 07/08103-2
dc.description.sponsorshipIdFAPESP: 2015/18525-8
dc.format.extent82-90
dc.identifierhttp://dx.doi.org/10.1016/j.rsase.2017.12.004
dc.identifier.citationRemote Sensing Applications: Society and Environment, v. 9, p. 82-90.
dc.identifier.doi10.1016/j.rsase.2017.12.004
dc.identifier.issn2352-9385
dc.identifier.lattes6691310394410490
dc.identifier.orcid0000-0002-8077-2865
dc.identifier.scopus2-s2.0-85044846800
dc.identifier.urihttp://hdl.handle.net/11449/176126
dc.language.isoeng
dc.relation.ispartofRemote Sensing Applications: Society and Environment
dc.relation.ispartofsjr0,667
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.subjectBio-optical properties
dc.subjectInland water
dc.subjectRemote sensing
dc.subjectWater quality
dc.titleLandsat-based remote sensing of the colored dissolved organic matter absorption coefficient in a tropical oligotrophic reservoiren
dc.typeArtigo
unesp.author.lattes6691310394410490[1]
unesp.author.orcid0000-0002-8077-2865[1]

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