Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme

Detalhes bibliográficos
Autor(a) principal: Bernardo, Nariane [UNESP]
Data de Publicação: 2019
Outros Autores: Carmo, Alisson do [UNESP], Park, Edward, Alcantara, Enner [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/rs11192283
http://hdl.handle.net/11449/196331
Resumo: Suspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the spatiotemporal dynamics of SPM in inland waters. In this paper, we present a novel and robust bio-optical model to retrieve SPM concentrations for inland waters with widely differing optical properties (the Tiete River Cascade System (TRCS) in Brazil). In this system, high levels of Chl-a concentration of up to 700 mg/m(3), turbidity up to 80 NTU and high CDOM absorption highly complicate the optical characteristics of the surface water, imposing an additional challenge in retrieving SPM concentration. Since K-d is not susceptible to the saturation issue encountered when using remote sensing reflectance (R-rs), we estimate SPM concentrations via K-d. K-d was derived analytically from inherent optical properties (IOPs) retrieved through a re-parameterized quasi-analytical algorithm (QAA) that yields relevant accuracy. Our model improved the estimates of the IOPs by up to 30% when compared to other existing QAAs. Our developed bio-optical model using K-d(655) was capable of describing 74% of SPM variations in the TRCS, with average error consistently lower than 30%.
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spelling Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Schemesemi-analytical modelinherent optical propertieslight attenuationwater quality monitoringSuspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the spatiotemporal dynamics of SPM in inland waters. In this paper, we present a novel and robust bio-optical model to retrieve SPM concentrations for inland waters with widely differing optical properties (the Tiete River Cascade System (TRCS) in Brazil). In this system, high levels of Chl-a concentration of up to 700 mg/m(3), turbidity up to 80 NTU and high CDOM absorption highly complicate the optical characteristics of the surface water, imposing an additional challenge in retrieving SPM concentration. Since K-d is not susceptible to the saturation issue encountered when using remote sensing reflectance (R-rs), we estimate SPM concentrations via K-d. K-d was derived analytically from inherent optical properties (IOPs) retrieved through a re-parameterized quasi-analytical algorithm (QAA) that yields relevant accuracy. Our model improved the estimates of the IOPs by up to 30% when compared to other existing QAAs. Our developed bio-optical model using K-d(655) was capable of describing 74% of SPM variations in the TRCS, with average error consistently lower than 30%.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Sao Paulo State Univ Unesp, Dept Cartog, BR-19063841 Presidente Prudente, SP, BrazilNanyang Technol Univ, Natl Inst Educ, Singapore 639798, SingaporeSao Paulo State Univ Unesp, Dept Environm Engn, BR-12247004 Sao Jose Dos Campos, SP, BrazilSao Paulo State Univ Unesp, Dept Cartog, BR-19063841 Presidente Prudente, SP, BrazilSao Paulo State Univ Unesp, Dept Environm Engn, BR-12247004 Sao Jose Dos Campos, SP, BrazilFAPESP: 2012/19821-1FAPESP: 2015/21586-9FAPESP: 2015/18525-8FAPESP: 2019/00259-0CNPq: 472131/2012-5CNPq: 482605/2013-8MdpiUniversidade Estadual Paulista (Unesp)Nanyang Technol UnivBernardo, Nariane [UNESP]Carmo, Alisson do [UNESP]Park, EdwardAlcantara, Enner [UNESP]2020-12-10T19:41:12Z2020-12-10T19:41:12Z2019-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article22http://dx.doi.org/10.3390/rs11192283Remote Sensing. Basel: Mdpi, v. 11, n. 19, 22 p., 2019.http://hdl.handle.net/11449/19633110.3390/rs11192283WOS:000496827100097Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensinginfo:eu-repo/semantics/openAccess2024-06-18T15:01:39Zoai:repositorio.unesp.br:11449/196331Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:14:14.273721Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
title Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
spellingShingle Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
Bernardo, Nariane [UNESP]
semi-analytical model
inherent optical properties
light attenuation
water quality monitoring
title_short Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
title_full Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
title_fullStr Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
title_full_unstemmed Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
title_sort Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme
author Bernardo, Nariane [UNESP]
author_facet Bernardo, Nariane [UNESP]
Carmo, Alisson do [UNESP]
Park, Edward
Alcantara, Enner [UNESP]
author_role author
author2 Carmo, Alisson do [UNESP]
Park, Edward
Alcantara, Enner [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Nanyang Technol Univ
dc.contributor.author.fl_str_mv Bernardo, Nariane [UNESP]
Carmo, Alisson do [UNESP]
Park, Edward
Alcantara, Enner [UNESP]
dc.subject.por.fl_str_mv semi-analytical model
inherent optical properties
light attenuation
water quality monitoring
topic semi-analytical model
inherent optical properties
light attenuation
water quality monitoring
description Suspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the spatiotemporal dynamics of SPM in inland waters. In this paper, we present a novel and robust bio-optical model to retrieve SPM concentrations for inland waters with widely differing optical properties (the Tiete River Cascade System (TRCS) in Brazil). In this system, high levels of Chl-a concentration of up to 700 mg/m(3), turbidity up to 80 NTU and high CDOM absorption highly complicate the optical characteristics of the surface water, imposing an additional challenge in retrieving SPM concentration. Since K-d is not susceptible to the saturation issue encountered when using remote sensing reflectance (R-rs), we estimate SPM concentrations via K-d. K-d was derived analytically from inherent optical properties (IOPs) retrieved through a re-parameterized quasi-analytical algorithm (QAA) that yields relevant accuracy. Our model improved the estimates of the IOPs by up to 30% when compared to other existing QAAs. Our developed bio-optical model using K-d(655) was capable of describing 74% of SPM variations in the TRCS, with average error consistently lower than 30%.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-01
2020-12-10T19:41:12Z
2020-12-10T19:41:12Z
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/10.3390/rs11192283
Remote Sensing. Basel: Mdpi, v. 11, n. 19, 22 p., 2019.
http://hdl.handle.net/11449/196331
10.3390/rs11192283
WOS:000496827100097
url http://dx.doi.org/10.3390/rs11192283
http://hdl.handle.net/11449/196331
identifier_str_mv Remote Sensing. Basel: Mdpi, v. 11, n. 19, 22 p., 2019.
10.3390/rs11192283
WOS:000496827100097
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 22
dc.publisher.none.fl_str_mv Mdpi
publisher.none.fl_str_mv Mdpi
dc.source.none.fl_str_mv Web of Science
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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