Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements

Detalhes bibliográficos
Autor(a) principal: do Carmo, Alisson Fernando Coelho [UNESP]
Data de Publicação: 2020
Outros Autores: Bernardo, Nariane Marselhe Ribeiro [UNESP], Imai, Nilton Nobuhiro [UNESP], Shimabukuro, Milton Hirokazu [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/2150704X.2019.1692383
http://hdl.handle.net/11449/199730
Resumo: Empirical line methods are frequently used to correct images from remote sensing. This method is performed in two steps: the first stage finds the calibration equation representing the data interval and the second step transforms the image data into the quantity established from the equation. Several works have been successfully applied empirical lines over land areas, but it is still a great challenge to correct images from waterbodies. Remote sensing of aquatic environments captures only a small amount of energy because the water absorbs much of it. The response signal of the water is smaller than the signal from other land surface targets. This work presents a new approach to calibrate empirical lines combining reference panels with a water point. For this purpose, we evaluated several combinations of targets using both linear and exponential fit. The best matching was provided with an exponential fit using a single grey reference panel combined with a water point resulting in a coefficient of determination about 0.87, a root-mean-squared error of 0.002 sr−1 and a mean absolute percentage error of 18%. This approach presented suitable results to derive reflectance data from the raw digital numbers from images.
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spelling Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurementsEmpirical line methods are frequently used to correct images from remote sensing. This method is performed in two steps: the first stage finds the calibration equation representing the data interval and the second step transforms the image data into the quantity established from the equation. Several works have been successfully applied empirical lines over land areas, but it is still a great challenge to correct images from waterbodies. Remote sensing of aquatic environments captures only a small amount of energy because the water absorbs much of it. The response signal of the water is smaller than the signal from other land surface targets. This work presents a new approach to calibrate empirical lines combining reference panels with a water point. For this purpose, we evaluated several combinations of targets using both linear and exponential fit. The best matching was provided with an exponential fit using a single grey reference panel combined with a water point resulting in a coefficient of determination about 0.87, a root-mean-squared error of 0.002 sr−1 and a mean absolute percentage error of 18%. This approach presented suitable results to derive reflectance data from the raw digital numbers from images.São Paulo State University (UNESP) Faculty of Sciences and Technology (FCT) Graduate Program of Cartographic Sciences (PPGCC) Campus Presidente Prudente–BrazilSão Paulo State University (UNESP) Faculty of Sciences and Technology (FCT) Graduate Program of Cartographic Sciences (PPGCC) Campus Presidente Prudente–BrazilUniversidade Estadual Paulista (Unesp)do Carmo, Alisson Fernando Coelho [UNESP]Bernardo, Nariane Marselhe Ribeiro [UNESP]Imai, Nilton Nobuhiro [UNESP]Shimabukuro, Milton Hirokazu [UNESP]2020-12-12T01:47:47Z2020-12-12T01:47:47Z2020-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article186-194http://dx.doi.org/10.1080/2150704X.2019.1692383Remote Sensing Letters, v. 11, n. 2, p. 186-194, 2020.2150-70582150-704Xhttp://hdl.handle.net/11449/19973010.1080/2150704X.2019.16923832-s2.0-85075729612118419553681480629857711025053300000-0003-0516-0567Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing Lettersinfo:eu-repo/semantics/openAccess2024-06-18T15:01:26Zoai:repositorio.unesp.br:11449/199730Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-18T15:01:26Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
title Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
spellingShingle Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
do Carmo, Alisson Fernando Coelho [UNESP]
title_short Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
title_full Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
title_fullStr Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
title_full_unstemmed Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
title_sort Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
author do Carmo, Alisson Fernando Coelho [UNESP]
author_facet do Carmo, Alisson Fernando Coelho [UNESP]
Bernardo, Nariane Marselhe Ribeiro [UNESP]
Imai, Nilton Nobuhiro [UNESP]
Shimabukuro, Milton Hirokazu [UNESP]
author_role author
author2 Bernardo, Nariane Marselhe Ribeiro [UNESP]
Imai, Nilton Nobuhiro [UNESP]
Shimabukuro, Milton Hirokazu [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv do Carmo, Alisson Fernando Coelho [UNESP]
Bernardo, Nariane Marselhe Ribeiro [UNESP]
Imai, Nilton Nobuhiro [UNESP]
Shimabukuro, Milton Hirokazu [UNESP]
description Empirical line methods are frequently used to correct images from remote sensing. This method is performed in two steps: the first stage finds the calibration equation representing the data interval and the second step transforms the image data into the quantity established from the equation. Several works have been successfully applied empirical lines over land areas, but it is still a great challenge to correct images from waterbodies. Remote sensing of aquatic environments captures only a small amount of energy because the water absorbs much of it. The response signal of the water is smaller than the signal from other land surface targets. This work presents a new approach to calibrate empirical lines combining reference panels with a water point. For this purpose, we evaluated several combinations of targets using both linear and exponential fit. The best matching was provided with an exponential fit using a single grey reference panel combined with a water point resulting in a coefficient of determination about 0.87, a root-mean-squared error of 0.002 sr−1 and a mean absolute percentage error of 18%. This approach presented suitable results to derive reflectance data from the raw digital numbers from images.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T01:47:47Z
2020-12-12T01:47:47Z
2020-02-01
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/10.1080/2150704X.2019.1692383
Remote Sensing Letters, v. 11, n. 2, p. 186-194, 2020.
2150-7058
2150-704X
http://hdl.handle.net/11449/199730
10.1080/2150704X.2019.1692383
2-s2.0-85075729612
1184195536814806
2985771102505330
0000-0003-0516-0567
url http://dx.doi.org/10.1080/2150704X.2019.1692383
http://hdl.handle.net/11449/199730
identifier_str_mv Remote Sensing Letters, v. 11, n. 2, p. 186-194, 2020.
2150-7058
2150-704X
10.1080/2150704X.2019.1692383
2-s2.0-85075729612
1184195536814806
2985771102505330
0000-0003-0516-0567
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing Letters
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 186-194
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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