Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties

Detalhes bibliográficos
Autor(a) principal: Bernardo, Nariane [UNESP]
Data de Publicação: 2018
Outros Autores: Alcântara, Enner [UNESP], Watanabe, Fernanda [UNESP], Rodrigues, Thanan, Carmo, Alisson [UNESP], Gomes, Ana [UNESP], Andrade, Caroline [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/rs10101655
http://hdl.handle.net/11449/188252
Resumo: The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (r) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s-1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral r achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.
id UNSP_27276fc9d288ef06de1c783b17739914
oai_identifier_str oai:repositorio.unesp.br:11449/188252
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical PropertiesInland watersOptically complex systemsRemote sensing accuracyThe quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (r) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s-1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral r achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Cartography São Paulo State University-UNESPDepartment of Environmental Engineering São Paulo State University-UNESPFederal Institute of Education Science and Technology of Pará State-IFPADepartment of Cartography São Paulo State University-UNESPDepartment of Environmental Engineering São Paulo State University-UNESPFAPESP: 2012/19821-1Universidade Estadual Paulista (Unesp)Science and Technology of Pará State-IFPABernardo, Nariane [UNESP]Alcântara, Enner [UNESP]Watanabe, Fernanda [UNESP]Rodrigues, ThananCarmo, Alisson [UNESP]Gomes, Ana [UNESP]Andrade, Caroline [UNESP]2019-10-06T16:02:07Z2019-10-06T16:02:07Z2018-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/rs10101655Remote Sensing, v. 10, n. 10, 2018.2072-4292http://hdl.handle.net/11449/18825210.3390/rs101016552-s2.0-8505542851866913103944104900000-0002-8077-2865Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensinginfo:eu-repo/semantics/openAccess2024-06-18T15:01:27Zoai:repositorio.unesp.br:11449/188252Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:46:31.438261Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
title Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
spellingShingle Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
Bernardo, Nariane [UNESP]
Inland waters
Optically complex systems
Remote sensing accuracy
title_short Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
title_full Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
title_fullStr Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
title_full_unstemmed Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
title_sort Glint removal assessment to estimate the remote sensing reflectance in inland waters withwidely differing optical Properties
author Bernardo, Nariane [UNESP]
author_facet Bernardo, Nariane [UNESP]
Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Rodrigues, Thanan
Carmo, Alisson [UNESP]
Gomes, Ana [UNESP]
Andrade, Caroline [UNESP]
author_role author
author2 Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Rodrigues, Thanan
Carmo, Alisson [UNESP]
Gomes, Ana [UNESP]
Andrade, Caroline [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Science and Technology of Pará State-IFPA
dc.contributor.author.fl_str_mv Bernardo, Nariane [UNESP]
Alcântara, Enner [UNESP]
Watanabe, Fernanda [UNESP]
Rodrigues, Thanan
Carmo, Alisson [UNESP]
Gomes, Ana [UNESP]
Andrade, Caroline [UNESP]
dc.subject.por.fl_str_mv Inland waters
Optically complex systems
Remote sensing accuracy
topic Inland waters
Optically complex systems
Remote sensing accuracy
description The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (r) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s-1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral r achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.
publishDate 2018
dc.date.none.fl_str_mv 2018-10-01
2019-10-06T16:02:07Z
2019-10-06T16:02:07Z
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/rs10101655
Remote Sensing, v. 10, n. 10, 2018.
2072-4292
http://hdl.handle.net/11449/188252
10.3390/rs10101655
2-s2.0-85055428518
6691310394410490
0000-0002-8077-2865
url http://dx.doi.org/10.3390/rs10101655
http://hdl.handle.net/11449/188252
identifier_str_mv Remote Sensing, v. 10, n. 10, 2018.
2072-4292
10.3390/rs10101655
2-s2.0-85055428518
6691310394410490
0000-0002-8077-2865
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.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
_version_ 1808128855156719616