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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/474P2K5
Repositorysid.inpe.br/plutao/2022/06.15.12.50   (restricted access)
Last Update2022:06.20.16.52.06 (UTC) simone
Metadata Repositorysid.inpe.br/plutao/2022/06.15.12.50.09
Metadata Last Update2023:01.03.16.52.55 (UTC) administrator
DOI10.3389/frsen.2022.834576
ISSN2673-6187
Labellattes: 1596449770636962 2 FloresJúniorBMNMLSC:2022:HySeAl
Citation KeyFloresJúniorBMNMLCC:2022:HySeAl
TitleHybrid Semi-Analytical Algorithm for Estimating Chlorophyll-A Concentration in Lower Amazon Floodplain Waters
Year2022
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size3423 KiB
2. Context
Author1 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
Resume Identifier1
2 8JMKD3MGP5W/3C9JGSB
3
4 8JMKD3MGP5W/3C9JH39
Group1 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
Affiliation1 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)
Author e-Mail Address1 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
JournalFrontiers in Remote Sensing
Volume3
Pages1-20
History (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. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsChlorophyll-a
water quality and clarity
Amazon Floodflain
inherent and apparent optical properties

turbid water
AbstractThe 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.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Hybrid Semi-Analytical Algorithm...
Arrangement 2urlib.net > BDMCI > Fonds > LabISA > Hybrid Semi-Analytical Algorithm...
Arrangement 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Hybrid Semi-Analytical Algorithm...
doc Directory Contentaccess
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4. Conditions of access and use
Languageen
Target Filefrsen-03-834576.pdf
Reader Groupadministrator
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simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/439EAFB
8JMKD3MGPCW/46KUATE
Citing Item Listsid.inpe.br/bibdigital/2013/10.18.22.34 3
sid.inpe.br/bibdigital/2022/04.03.22.23 2
sid.inpe.br/mtc-m21/2012/07.13.14.43.57 2
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
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