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Estimating the CDOM absorption coefficient in tropical inland waters using OLI/Landsat-8 images

dc.contributor.authorAlcântara, Enner [UNESP]
dc.contributor.authorBernardo, Nariane [UNESP]
dc.contributor.authorWatanabe, Fernanda [UNESP]
dc.contributor.authorRodrigues, Thanan [UNESP]
dc.contributor.authorRotta, Luiz [UNESP]
dc.contributor.authorCarmo, Alisson [UNESP]
dc.contributor.authorShimabukuro, Milton [UNESP]
dc.contributor.authorGonçalves, Stela [UNESP]
dc.contributor.authorImai, Nilton [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:03:03Z
dc.date.available2018-12-11T17:03:03Z
dc.date.issued2016-07-02
dc.description.abstractColoured dissolved organic matter (CDOM) is the most abundant dissolved organic matter (DOM) in many natural waters and can affect the water quality, such as the light penetration and the thermal properties of water system. So the objective of this letter was to estimate the CDOM absorption coefficient at 440 nm, aCDOM(440), in Barra Bonita Reservoir (São Paulo State, Brazil) using operational land imager (OLI)/Landsat-8 images. For this two field campaigns were conducted in May and October 2014. During the field campaigns remote sensing reflectance (Rrs) were measured using a TriOS hyperspectral radiometer. Water samples were collected and analysed to obtain the aCDOM(440). To predict the aCDOM(440) from Rrs at two key wavelengths (650 and 480 nm) were regressed against laboratory-derived aCDOM(440) values. The validation using in situ data of aCDOM(440) algorithm indicated a goodness of fit, R2 = 0.70, with a root mean square error (RMSE) of 10.65%. The developed algorithm was applied to the OLI/Lansat-8 images. Distribution maps were created with OLI/Landsat-8 images based on the adjusted algorithm.en
dc.description.affiliationDepartment of Cartography São Paulo State University – Unesp
dc.description.affiliationDepartment of Mathematics and Computer Science São Paulo State University – Unesp
dc.description.affiliationUnespDepartment of Cartography São Paulo State University – Unesp
dc.description.affiliationUnespDepartment of Mathematics and Computer Science São Paulo State University – Unesp
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdCNPq: 400881/2013-6
dc.description.sponsorshipIdCNPq: 472131/2012-5
dc.format.extent661-670
dc.identifierhttp://dx.doi.org/10.1080/2150704X.2016.1177242
dc.identifier.citationRemote Sensing Letters, v. 7, n. 7, p. 661-670, 2016.
dc.identifier.doi10.1080/2150704X.2016.1177242
dc.identifier.issn2150-7058
dc.identifier.issn2150-704X
dc.identifier.lattes6691310394410490
dc.identifier.orcid0000-0002-8077-2865
dc.identifier.scopus2-s2.0-84970021824
dc.identifier.urihttp://hdl.handle.net/11449/172999
dc.language.isoeng
dc.relation.ispartofRemote Sensing Letters
dc.relation.ispartofsjr0,752
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.titleEstimating the CDOM absorption coefficient in tropical inland waters using OLI/Landsat-8 imagesen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.lattes6691310394410490[3]
unesp.author.orcid0000-0002-7777-2119[1]
unesp.author.orcid0000-0002-8077-2865[3]
unesp.departmentCartografia - FCTpt

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