Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Thanan [UNESP]
Data de Publicação: 2017
Outros Autores: Alcântara, Enner [UNESP], Watanabe, Fernanda [UNESP], Imai, Nilton [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.rse.2017.06.018
http://hdl.handle.net/11449/174772
Resumo: The mechanistic model reported in Lee et al. (2015) estimating the Secchi disk depth (ZSD) was applied to an oligo- to mesotrophic reservoir in Brazil. The model was originally validated with data covering lake, oceanic, and coastal waters; however, the model used the quasi-analytical algorithm (QAA) designed for optically deep waters as input and was applied to oceanic and coastal waters to derive absorption [a] and backscattering [bb] coefficients. The hypothesis is that the use of QAAv5 (http://www.ioccg.org/groups/Software_OCA/QAA_v5.pdf) to estimate both a and bb (step M1) to retrieve Kd (step M2) and ZSD (step M3) will lead to errors caused by M1 preventing an accurate estimate in oligo- to mesotrophic water. To test this hypothesis, data collected in three field trips were used to apply the mechanistic model based on the spectral bands from OLI/Landsat-8, (often applied to oceanic and coastal waters), and multispectral instrument (MSI)/Sentinel-2 bands (applied to QAA designed for very turbid inland water). The impact of step M1 over steps M2 and M3 was analyzed by the error analysis. The mean absolute percentage error (MAPE) for Kd using QAAv5 ranged between 10.35% and 19.76%, while the error using QAAM14 varied between 12.68% and 28.29%. Regarding the errors of step M3 and applying QAAv5, the total root-mean-square difference (RMSD) varied from 0.55 to 1.18 m and MAPE ranged between 12.86% and 31.17%, while the RMSD ranged between 0.70 and 1.50 m and MAPE varied from 14.33% to 39.13% when using QAAM14. However, the result from QAAv5 showed a better correlation with in situ data, although underestimating Kd and ZSD. Therefore, a modified version of QAAv5 (QAAR17) was evaluated. The results showed an improvement of Kd (MAPE ranging between 8.89% to 18.76%) and ZSD (RMSD ranging between 0.32 and 0.90 m and MAPE ranging between 8.65 and 19.75%), bringing the values close to the 1:1 line. The largest error was observed for the data of the second field trip, where the bio-optical properties showed a horizontal gradient along the reservoir. In addition, the magnitude of the remote sensing reflectance (Rrs) also varied depending on the water quality. Thus, with respect to ZSD mapping, this research showed that environments with a high variability in Rrs can limit the accurate estimation of inherent optical properties (IOPs) based on QAAv5. Therefore, the limiting step of the model was attributed to M1, which means that the mechanistic model from Lee et al. (2015) can be considered an universal approach if M1 is modified based on the type of water.
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spelling Retrieval of Secchi disk depth from a reservoir using a semi-analytical schemeInland watersOptical propertiesTropical reservoirsWater clarityThe mechanistic model reported in Lee et al. (2015) estimating the Secchi disk depth (ZSD) was applied to an oligo- to mesotrophic reservoir in Brazil. The model was originally validated with data covering lake, oceanic, and coastal waters; however, the model used the quasi-analytical algorithm (QAA) designed for optically deep waters as input and was applied to oceanic and coastal waters to derive absorption [a] and backscattering [bb] coefficients. The hypothesis is that the use of QAAv5 (http://www.ioccg.org/groups/Software_OCA/QAA_v5.pdf) to estimate both a and bb (step M1) to retrieve Kd (step M2) and ZSD (step M3) will lead to errors caused by M1 preventing an accurate estimate in oligo- to mesotrophic water. To test this hypothesis, data collected in three field trips were used to apply the mechanistic model based on the spectral bands from OLI/Landsat-8, (often applied to oceanic and coastal waters), and multispectral instrument (MSI)/Sentinel-2 bands (applied to QAA designed for very turbid inland water). The impact of step M1 over steps M2 and M3 was analyzed by the error analysis. The mean absolute percentage error (MAPE) for Kd using QAAv5 ranged between 10.35% and 19.76%, while the error using QAAM14 varied between 12.68% and 28.29%. Regarding the errors of step M3 and applying QAAv5, the total root-mean-square difference (RMSD) varied from 0.55 to 1.18 m and MAPE ranged between 12.86% and 31.17%, while the RMSD ranged between 0.70 and 1.50 m and MAPE varied from 14.33% to 39.13% when using QAAM14. However, the result from QAAv5 showed a better correlation with in situ data, although underestimating Kd and ZSD. Therefore, a modified version of QAAv5 (QAAR17) was evaluated. The results showed an improvement of Kd (MAPE ranging between 8.89% to 18.76%) and ZSD (RMSD ranging between 0.32 and 0.90 m and MAPE ranging between 8.65 and 19.75%), bringing the values close to the 1:1 line. The largest error was observed for the data of the second field trip, where the bio-optical properties showed a horizontal gradient along the reservoir. In addition, the magnitude of the remote sensing reflectance (Rrs) also varied depending on the water quality. Thus, with respect to ZSD mapping, this research showed that environments with a high variability in Rrs can limit the accurate estimation of inherent optical properties (IOPs) based on QAAv5. Therefore, the limiting step of the model was attributed to M1, which means that the mechanistic model from Lee et al. (2015) can be considered an universal approach if M1 is modified based on the type of water.São Paulo State University (Unesp) Department of Cartography, 305 Roberto Simonsen StreetSão Paulo State University (Unesp) Department of Environmental Engineering, Rodovia Presidente Dutra, Km 137.8São Paulo State University (Unesp) Department of Cartography, 305 Roberto Simonsen StreetSão Paulo State University (Unesp) Department of Environmental Engineering, Rodovia Presidente Dutra, Km 137.8Universidade Estadual Paulista (Unesp)Rodrigues, Thanan [UNESP]Alcântara, Enner [UNESP]Watanabe, Fernanda [UNESP]Imai, Nilton [UNESP]2018-12-11T17:12:47Z2018-12-11T17:12:47Z2017-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article213-228application/pdfhttp://dx.doi.org/10.1016/j.rse.2017.06.018Remote Sensing of Environment, v. 198, p. 213-228.0034-4257http://hdl.handle.net/11449/17477210.1016/j.rse.2017.06.0182-s2.0-850208948842-s2.0-85020894884.pdf66913103944104900000-0002-8077-2865Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing of Environment3,121info:eu-repo/semantics/openAccess2024-06-18T15:01:26Zoai:repositorio.unesp.br:11449/174772Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:53:29.707222Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
title Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
spellingShingle Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
Rodrigues, Thanan [UNESP]
Inland waters
Optical properties
Tropical reservoirs
Water clarity
title_short Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
title_full Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
title_fullStr Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
title_full_unstemmed Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
title_sort Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme
author Rodrigues, Thanan [UNESP]
author_facet Rodrigues, Thanan [UNESP]
Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Imai, Nilton [UNESP]
author_role author
author2 Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Imai, Nilton [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Rodrigues, Thanan [UNESP]
Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Imai, Nilton [UNESP]
dc.subject.por.fl_str_mv Inland waters
Optical properties
Tropical reservoirs
Water clarity
topic Inland waters
Optical properties
Tropical reservoirs
Water clarity
description The mechanistic model reported in Lee et al. (2015) estimating the Secchi disk depth (ZSD) was applied to an oligo- to mesotrophic reservoir in Brazil. The model was originally validated with data covering lake, oceanic, and coastal waters; however, the model used the quasi-analytical algorithm (QAA) designed for optically deep waters as input and was applied to oceanic and coastal waters to derive absorption [a] and backscattering [bb] coefficients. The hypothesis is that the use of QAAv5 (http://www.ioccg.org/groups/Software_OCA/QAA_v5.pdf) to estimate both a and bb (step M1) to retrieve Kd (step M2) and ZSD (step M3) will lead to errors caused by M1 preventing an accurate estimate in oligo- to mesotrophic water. To test this hypothesis, data collected in three field trips were used to apply the mechanistic model based on the spectral bands from OLI/Landsat-8, (often applied to oceanic and coastal waters), and multispectral instrument (MSI)/Sentinel-2 bands (applied to QAA designed for very turbid inland water). The impact of step M1 over steps M2 and M3 was analyzed by the error analysis. The mean absolute percentage error (MAPE) for Kd using QAAv5 ranged between 10.35% and 19.76%, while the error using QAAM14 varied between 12.68% and 28.29%. Regarding the errors of step M3 and applying QAAv5, the total root-mean-square difference (RMSD) varied from 0.55 to 1.18 m and MAPE ranged between 12.86% and 31.17%, while the RMSD ranged between 0.70 and 1.50 m and MAPE varied from 14.33% to 39.13% when using QAAM14. However, the result from QAAv5 showed a better correlation with in situ data, although underestimating Kd and ZSD. Therefore, a modified version of QAAv5 (QAAR17) was evaluated. The results showed an improvement of Kd (MAPE ranging between 8.89% to 18.76%) and ZSD (RMSD ranging between 0.32 and 0.90 m and MAPE ranging between 8.65 and 19.75%), bringing the values close to the 1:1 line. The largest error was observed for the data of the second field trip, where the bio-optical properties showed a horizontal gradient along the reservoir. In addition, the magnitude of the remote sensing reflectance (Rrs) also varied depending on the water quality. Thus, with respect to ZSD mapping, this research showed that environments with a high variability in Rrs can limit the accurate estimation of inherent optical properties (IOPs) based on QAAv5. Therefore, the limiting step of the model was attributed to M1, which means that the mechanistic model from Lee et al. (2015) can be considered an universal approach if M1 is modified based on the type of water.
publishDate 2017
dc.date.none.fl_str_mv 2017-09-01
2018-12-11T17:12:47Z
2018-12-11T17:12:47Z
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/10.1016/j.rse.2017.06.018
Remote Sensing of Environment, v. 198, p. 213-228.
0034-4257
http://hdl.handle.net/11449/174772
10.1016/j.rse.2017.06.018
2-s2.0-85020894884
2-s2.0-85020894884.pdf
6691310394410490
0000-0002-8077-2865
url http://dx.doi.org/10.1016/j.rse.2017.06.018
http://hdl.handle.net/11449/174772
identifier_str_mv Remote Sensing of Environment, v. 198, p. 213-228.
0034-4257
10.1016/j.rse.2017.06.018
2-s2.0-85020894884
2-s2.0-85020894884.pdf
6691310394410490
0000-0002-8077-2865
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing of Environment
3,121
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 213-228
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
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