Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)

Detalhes bibliográficos
Autor(a) principal: Alcântara, Enner [UNESP]
Data de Publicação: 2016
Outros Autores: Curtarelli, Marcelo, Stech, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/2150704X.2015.1137646
http://hdl.handle.net/11449/172872
Resumo: In this study, a quasi-analytical algorithm (QAA)-based model was parameterized using remote-sensing reflectance (Rrs, units in sr1), total absorption coefficient (at) and total suspended matter (TSM) concentration. The model was based on the particle backscattering at 561 nm (bbp(561)) and was derived from the QAA and TSM concentration. The aim of this work was to parameterize a QAA-based model to estimate the TSM concentration using the Landsat-8 Operational Land Imager (OLI) sensor in the Itumbiara hydroelectric reservoir, Brazil. The results demonstrated that the calibrated model, TSM = 0:907 + 5:479 × bbp(561) +, had a coefficient of determination of R2= 0.70 and that the validation had an R2= 0.82, RMSE = 41.39% and a mean bias of 0.074 mg l-1. The primary observation using the TSM and bbp(561) maps is that waters with lower bbp(561) values have lower TSM concentrations; there is a direct correlation between bbp(561) and TSM concentration.
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spelling Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)In this study, a quasi-analytical algorithm (QAA)-based model was parameterized using remote-sensing reflectance (Rrs, units in sr1), total absorption coefficient (at) and total suspended matter (TSM) concentration. The model was based on the particle backscattering at 561 nm (bbp(561)) and was derived from the QAA and TSM concentration. The aim of this work was to parameterize a QAA-based model to estimate the TSM concentration using the Landsat-8 Operational Land Imager (OLI) sensor in the Itumbiara hydroelectric reservoir, Brazil. The results demonstrated that the calibrated model, TSM = 0:907 + 5:479 × bbp(561) +, had a coefficient of determination of R2= 0.70 and that the validation had an R2= 0.82, RMSE = 41.39% and a mean bias of 0.074 mg l-1. The primary observation using the TSM and bbp(561) maps is that waters with lower bbp(561) values have lower TSM concentrations; there is a direct correlation between bbp(561) and TSM concentration.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Cartography São Paulo State University - UnespRemote Sensing Division National Institute for Space Research - INPEDepartment of Cartography São Paulo State University - UnespUniversidade Estadual Paulista (Unesp)National Institute for Space Research - INPEAlcântara, Enner [UNESP]Curtarelli, MarceloStech, José2018-12-11T17:02:30Z2018-12-11T17:02:30Z2016-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article397-406application/pdfhttp://dx.doi.org/10.1080/2150704X.2015.1137646Remote Sensing Letters, v. 7, n. 4, p. 397-406, 2016.2150-70582150-704Xhttp://hdl.handle.net/11449/17287210.1080/2150704X.2015.11376462-s2.0-849644333782-s2.0-84964433378.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing Letters0,752info:eu-repo/semantics/openAccess2024-06-18T15:01:52Zoai:repositorio.unesp.br:11449/172872Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:18:27.095033Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
title Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
spellingShingle Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
Alcântara, Enner [UNESP]
title_short Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
title_full Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
title_fullStr Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
title_full_unstemmed Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
title_sort Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
author Alcântara, Enner [UNESP]
author_facet Alcântara, Enner [UNESP]
Curtarelli, Marcelo
Stech, José
author_role author
author2 Curtarelli, Marcelo
Stech, José
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
National Institute for Space Research - INPE
dc.contributor.author.fl_str_mv Alcântara, Enner [UNESP]
Curtarelli, Marcelo
Stech, José
description In this study, a quasi-analytical algorithm (QAA)-based model was parameterized using remote-sensing reflectance (Rrs, units in sr1), total absorption coefficient (at) and total suspended matter (TSM) concentration. The model was based on the particle backscattering at 561 nm (bbp(561)) and was derived from the QAA and TSM concentration. The aim of this work was to parameterize a QAA-based model to estimate the TSM concentration using the Landsat-8 Operational Land Imager (OLI) sensor in the Itumbiara hydroelectric reservoir, Brazil. The results demonstrated that the calibrated model, TSM = 0:907 + 5:479 × bbp(561) +, had a coefficient of determination of R2= 0.70 and that the validation had an R2= 0.82, RMSE = 41.39% and a mean bias of 0.074 mg l-1. The primary observation using the TSM and bbp(561) maps is that waters with lower bbp(561) values have lower TSM concentrations; there is a direct correlation between bbp(561) and TSM concentration.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01
2018-12-11T17:02:30Z
2018-12-11T17:02:30Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1080/2150704X.2015.1137646
Remote Sensing Letters, v. 7, n. 4, p. 397-406, 2016.
2150-7058
2150-704X
http://hdl.handle.net/11449/172872
10.1080/2150704X.2015.1137646
2-s2.0-84964433378
2-s2.0-84964433378.pdf
url http://dx.doi.org/10.1080/2150704X.2015.1137646
http://hdl.handle.net/11449/172872
identifier_str_mv Remote Sensing Letters, v. 7, n. 4, p. 397-406, 2016.
2150-7058
2150-704X
10.1080/2150704X.2015.1137646
2-s2.0-84964433378
2-s2.0-84964433378.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing Letters
0,752
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 397-406
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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