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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W/474P2K5
Repositóriosid.inpe.br/plutao/2022/06.15.12.50   (acesso restrito)
Última Atualização2022:06.20.16.52.06 (UTC) simone
Repositório de Metadadossid.inpe.br/plutao/2022/06.15.12.50.09
Última Atualização dos Metadados2023:01.03.16.52.55 (UTC) administrator
DOI10.3389/frsen.2022.834576
ISSN2673-6187
Rótulolattes: 1596449770636962 2 FloresJúniorBMNMLSC:2022:HySeAl
Chave de CitaçãoFloresJúniorBMNMLCC:2022:HySeAl
TítuloHybrid Semi-Analytical Algorithm for Estimating Chlorophyll-A Concentration in Lower Amazon Floodplain Waters
Ano2022
Data de Acesso17 jun. 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho3423 KiB
2. Contextualização
Autor1 Flores Júnior, Rogério
2 Barbosa, Cláudio Clemente Faria
3 Maciel, Daniel Andrade
4 Novo, Evlyn Márcia Leão de Moraes
5 Martins, Vitor Souza
6 Lobo, Felipe de Lucia
7 Carvalho, Lino Augusto Sander de
8 Carlos, Felipe Menino
Identificador de Curriculo1
2 8JMKD3MGP5W/3C9JGSB
3
4 8JMKD3MGP5W/3C9JH39
Grupo1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
2 DIOTG-CGCT-INPE-MCTI-GOV-BR
3 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
4 DIOTG-CGCT-INPE-MCTI-GOV-BR
5
6
7
8 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Mississippi State University
6 Universidade Federal de Pelotas (UFPel)
7 Universidade Federal Do Rio de Janeiro (UFRJ)
8 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 rogerio.floresjr@gmail.com DIOTG Asa São José dos Campos
2 claudio.barbosa@inpe.br
3 damaciel_maciel@hotmail.com
4 evlyn.leao@gmail.com
5
6
7
8 felipe.carlos@fatec.sp.gov.br
RevistaFrontiers in Remote Sensing
Volume3
Páginas1-20
Histórico (UTC)2022-06-15 13:39:15 :: lattes -> administrator :: 2022
2022-06-17 07:44:41 :: administrator -> lattes :: 2022
2022-06-20 16:52:09 :: lattes -> administrator :: 2022
2022-07-08 16:52:54 :: administrator -> simone :: 2022
2022-12-20 14:05:55 :: simone -> administrator :: 2022
2023-01-03 16:52:55 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveChlorophyll-a
water quality and clarity
Amazon Floodflain
inherent and apparent optical properties

turbid water
ResumoThe Amazon Basin is the largest on the planet, and its aquatic ecosystems affect and are affected by the Earths processes. Specifically, Amazon aquatic ecosystems have been subjected to severe anthropogenic impacts due to deforestation, mining, dam construction, and widespread agribusiness expansion. Therefore, the monitoring of these impacts has become crucial for conservation plans and environmental legislation enforcement. However, its continental dimensions, the high variability of Amazonian water mass constituents, and cloud cover frequency impose a challenge for developing accurate satellite algorithms for water quality retrieval such as chlorophyll-a concentration (Chl-a), which is a proxy for the trophic state. This study presents the first application of the hybrid semi-analytical algorithm (HSAA) for Chl-a retrieval using a Sentinel-3 OLCI sensor over five Amazonian floodplain lakes. Inherent and apparent optical properties (IOPs and AOPs), as well as limnological data, were collected at 94 sampling stations during four field campaigns along hydrological years spanning from 2015 to 2017 and used to parameterize the hybrid SAA to retrieve Chl-a in highly turbid Amazonian waters. We implemented a re-parametrizing approach, called the generalized stacked constraints model to the Amazonian waters (GSCMLAFW), and used it to decompose the total absorption αt(λ) into the absorption coefficients of detritus, CDOM, and phytoplankton (αphy(λ)). The estimated GSCMLAFW αphy(λ) achieved errors lower than 24% at the visible bands and 70% at NIR. The performance of HSAA-based Chl-a retrieval was validated with in situ measurements of Chl-a concentration, and then it was compared to literature Chl-a algorithms. The results showed a smaller mean absolute percentage error (MAPE) for HSAA Chl-a retrieval (36.93%) than empirical Rrs models (73.39%) using a 3-band algorithm, which confirms the better performance of the semi-analytical approach. Last, the calibrated HSAA model was used to estimate the Chl-a concentration in OLCI images acquired during 2017 and 2019 field campaigns, and the results demonstrated reasonable errors (MAPE = 57%) and indicated the potential of OLCI bands for Chl-a estimation. Therefore, the outcomes of this study support the advance of semianalytical models in highly turbid waters and highlight the importance of reparameterization with GSCM and the applicability of HSAA in Sentinel-3 OLCI data.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Hybrid Semi-Analytical Algorithm...
Arranjo 2urlib.net > BDMCI > Fonds > LabISA > Hybrid Semi-Analytical Algorithm...
Arranjo 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Hybrid Semi-Analytical Algorithm...
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvofrsen-03-834576.pdf
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Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
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5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/439EAFB
8JMKD3MGPCW/46KUATE
Lista de Itens Citandosid.inpe.br/mtc-m21/2012/07.13.14.43.57 5
sid.inpe.br/bibdigital/2022/04.03.22.23 4
sid.inpe.br/bibdigital/2013/10.18.22.34 4
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
Campos Vaziosalternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress format isbn lineage mark mirrorrepository month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url usergroup
7. Controle da descrição
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