Estimating total suspended matter using the particle backscattering coefficient: Results from the Itumbiara hydroelectric reservoir (Goiás State, Brazil)
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1808129307218804736 |