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Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters

dc.contributor.authorWatanabe, Fernanda [UNESP]
dc.contributor.authorAlcântara, Enner [UNESP]
dc.contributor.authorImai, Nilton [UNESP]
dc.contributor.authorRodrigues, Thanan
dc.contributor.authorBernardo, Nariane [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionScience and Technology from Pará
dc.date.accessioned2018-12-11T17:18:13Z
dc.date.available2018-12-11T17:18:13Z
dc.date.issued2018-02-01
dc.description.abstractThe high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.en
dc.description.affiliationDepartment of Cartography Faculty of Sciences and Technology São Paulo State University (UNESP), Rua Roberto Simonsen 305
dc.description.affiliationDepartment of Environmental Engineering Institute of Science and Technology São Paulo State University (UNESP), Rodovia Presidente Dutra Km 137.8
dc.description.affiliationFederal Institute of Education Science and Technology from Pará, Rodovia BR 316, km 61
dc.description.affiliationUnespDepartment of Cartography Faculty of Sciences and Technology São Paulo State University (UNESP), Rua Roberto Simonsen 305
dc.description.affiliationUnespDepartment of Environmental Engineering Institute of Science and Technology São Paulo State University (UNESP), Rodovia Presidente Dutra Km 137.8
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.identifierhttp://dx.doi.org/10.3390/rs10020227
dc.identifier.citationRemote Sensing, v. 10, n. 2, 2018.
dc.identifier.doi10.3390/rs10020227
dc.identifier.file2-s2.0-85042525466.pdf
dc.identifier.issn2072-4292
dc.identifier.lattes6691310394410490
dc.identifier.orcid0000-0002-8077-2865
dc.identifier.scopus2-s2.0-85042525466
dc.identifier.urihttp://hdl.handle.net/11449/175936
dc.language.isoeng
dc.relation.ispartofRemote Sensing
dc.relation.ispartofsjr1,386
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectOLCI Sentinel-3
dc.subjectProductive inland waters
dc.subjectSemi-analytical approach
dc.subjectTrophic state
dc.titleEstimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland watersen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.lattes6691310394410490[1]
unesp.author.orcid0000-0002-8077-2865[1]
unesp.departmentCartografia - FCTpt

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