Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/183259 |
Resumo: | Remote estimation of chlorophyll-a in turbid and productive estuaries is difficult due to the optical complexity of Case 2 waters. Although recent advances have been obtained with the use of empirical approaches for estimating chlorophyll-a in these environments, the understanding of the relationship between spectral reflectance and chlorophyll-a is based mainly on temperate and subtropical estuarine systems. The potential to apply standard NIR-Red models to productive tropical estuaries remains underexplored. Therefore, the purpose of this study is to evaluate the performance of several approaches based on multispectral data to estimate chlorophyll-a in a productive tropical estuarine-lagoon system, using in situ measurements of remote sensing reflectance, Rrs. The possibility of applying algorithms using simulated satellite bands of modern and recent launched sensors was also evaluated. More accurate retrievals of chlorophyll-a (r2 > 0.80) based on field datasets were found using NIR-Red three-band models. In addition, enhanced chlorophyll-a retrievals were found using the two-band algorithm based on bands of recently launched satellites such as Sentinel-2/MSI and Sentinel-3/OLCI, indicating a promising application of these sensors to remotely estimate chlorophyll-a for coming decades in turbid inland waters. Our findings suggest that empirical models based on optical properties involving water constituents have strong potential to estimate chlorophyll-a using multispectral data from satellite, airborne or handheld sensors in productive tropical estuaries. |
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Lins, Regina CamaraMartinez, Jean-MichelMarques, David Manuel Lelinho da MottaCirilo, Jose AlmirFragoso Júnior, Carlos Ruberto2018-10-11T02:36:37Z20172072-4292http://hdl.handle.net/10183/183259001078055Remote estimation of chlorophyll-a in turbid and productive estuaries is difficult due to the optical complexity of Case 2 waters. Although recent advances have been obtained with the use of empirical approaches for estimating chlorophyll-a in these environments, the understanding of the relationship between spectral reflectance and chlorophyll-a is based mainly on temperate and subtropical estuarine systems. The potential to apply standard NIR-Red models to productive tropical estuaries remains underexplored. Therefore, the purpose of this study is to evaluate the performance of several approaches based on multispectral data to estimate chlorophyll-a in a productive tropical estuarine-lagoon system, using in situ measurements of remote sensing reflectance, Rrs. The possibility of applying algorithms using simulated satellite bands of modern and recent launched sensors was also evaluated. More accurate retrievals of chlorophyll-a (r2 > 0.80) based on field datasets were found using NIR-Red three-band models. In addition, enhanced chlorophyll-a retrievals were found using the two-band algorithm based on bands of recently launched satellites such as Sentinel-2/MSI and Sentinel-3/OLCI, indicating a promising application of these sensors to remotely estimate chlorophyll-a for coming decades in turbid inland waters. Our findings suggest that empirical models based on optical properties involving water constituents have strong potential to estimate chlorophyll-a using multispectral data from satellite, airborne or handheld sensors in productive tropical estuaries.application/pdfengRemote Sensing. Basel. Vol. 9 , n. 6 (2017), 19 p.EstuáriosEcossistema aquaticoFitoplânctonClorofilaMundaú, Lagoa (AL)Manguaba, Lagoa (AL)Sensoriamento remotoEstuáriosLagoas costeirasShallow productive estuaryChlorophyll-aRemote sensingSentinelAssessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon systemEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL001078055.pdfTexto completo (inglês)application/pdf6903756http://www.lume.ufrgs.br/bitstream/10183/183259/1/001078055.pdf16390cd9eb9040445282ad7f7344032bMD51TEXT001078055.pdf.txt001078055.pdf.txtExtracted Texttext/plain73975http://www.lume.ufrgs.br/bitstream/10183/183259/2/001078055.pdf.txtb94b6dcefc5a03b53751dcbaea5fefb0MD52THUMBNAIL001078055.pdf.jpg001078055.pdf.jpgGenerated Thumbnailimage/jpeg1818http://www.lume.ufrgs.br/bitstream/10183/183259/3/001078055.pdf.jpg0eb7c6c2e13a74eb0d524eb6a9fb28ecMD5310183/1832592022-07-27 04:47:07.94919oai:www.lume.ufrgs.br:10183/183259Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2022-07-27T07:47:07Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
title |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
spellingShingle |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system Lins, Regina Camara Estuários Ecossistema aquatico Fitoplâncton Clorofila Mundaú, Lagoa (AL) Manguaba, Lagoa (AL) Sensoriamento remoto Estuários Lagoas costeiras Shallow productive estuary Chlorophyll-a Remote sensing Sentinel |
title_short |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
title_full |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
title_fullStr |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
title_full_unstemmed |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
title_sort |
Assessment of chlorophyll-a remote sensing algorithms in a productive tropical estuarine-lagoon system |
author |
Lins, Regina Camara |
author_facet |
Lins, Regina Camara Martinez, Jean-Michel Marques, David Manuel Lelinho da Motta Cirilo, Jose Almir Fragoso Júnior, Carlos Ruberto |
author_role |
author |
author2 |
Martinez, Jean-Michel Marques, David Manuel Lelinho da Motta Cirilo, Jose Almir Fragoso Júnior, Carlos Ruberto |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Lins, Regina Camara Martinez, Jean-Michel Marques, David Manuel Lelinho da Motta Cirilo, Jose Almir Fragoso Júnior, Carlos Ruberto |
dc.subject.por.fl_str_mv |
Estuários Ecossistema aquatico Fitoplâncton Clorofila Mundaú, Lagoa (AL) Manguaba, Lagoa (AL) Sensoriamento remoto Estuários Lagoas costeiras |
topic |
Estuários Ecossistema aquatico Fitoplâncton Clorofila Mundaú, Lagoa (AL) Manguaba, Lagoa (AL) Sensoriamento remoto Estuários Lagoas costeiras Shallow productive estuary Chlorophyll-a Remote sensing Sentinel |
dc.subject.eng.fl_str_mv |
Shallow productive estuary Chlorophyll-a Remote sensing Sentinel |
description |
Remote estimation of chlorophyll-a in turbid and productive estuaries is difficult due to the optical complexity of Case 2 waters. Although recent advances have been obtained with the use of empirical approaches for estimating chlorophyll-a in these environments, the understanding of the relationship between spectral reflectance and chlorophyll-a is based mainly on temperate and subtropical estuarine systems. The potential to apply standard NIR-Red models to productive tropical estuaries remains underexplored. Therefore, the purpose of this study is to evaluate the performance of several approaches based on multispectral data to estimate chlorophyll-a in a productive tropical estuarine-lagoon system, using in situ measurements of remote sensing reflectance, Rrs. The possibility of applying algorithms using simulated satellite bands of modern and recent launched sensors was also evaluated. More accurate retrievals of chlorophyll-a (r2 > 0.80) based on field datasets were found using NIR-Red three-band models. In addition, enhanced chlorophyll-a retrievals were found using the two-band algorithm based on bands of recently launched satellites such as Sentinel-2/MSI and Sentinel-3/OLCI, indicating a promising application of these sensors to remotely estimate chlorophyll-a for coming decades in turbid inland waters. Our findings suggest that empirical models based on optical properties involving water constituents have strong potential to estimate chlorophyll-a using multispectral data from satellite, airborne or handheld sensors in productive tropical estuaries. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017 |
dc.date.accessioned.fl_str_mv |
2018-10-11T02:36:37Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/183259 |
dc.identifier.issn.pt_BR.fl_str_mv |
2072-4292 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001078055 |
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2072-4292 001078055 |
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http://hdl.handle.net/10183/183259 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Remote Sensing. Basel. Vol. 9 , n. 6 (2017), 19 p. |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
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