First results of PRISMA satellite data applied to water quality monitoring in Argentina

Autores
Gauto, Víctor Hugo; Ferral, Anabella; Bonansea, Matias; Farías, Alejandro Rubén; Scavuzzo, Marcelo; Cardozo, Osvaldo; Germán, Alba; Giardino, Claudia
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Water has historically been considered a renewable resource, however in the last century a sustained degradation of its quality has been observed, both in continental and oceanic systems due to anthropic impact. In this context, the management of water resources by satellite technology represents a central point in public policies since they allow anticipating and adapting to these disturbances. In this work, Sentinel 2-MSI multispectral and PRISMA hyperspectral sensors are used to carry out an analysis of different optical water types in North-East of Argentina. Convolutional procedure was used to compare sensors responses for atmospheric corrected products and RMSE (root mean square error), BIAS and MAE (mean absolute error) metrics were used to assess their performance. Differences below 1 percent were obtained in all cases, indicating an excellent match-up between both sensors. From hyperspectral PRISMA data it was possible to detect quantitative shift towards reddish wavelengths as turbidity of Parana River increases along a transect as well as an increase of the peak value in magnitude. This work opens new opportunities to monitor water quality changes related to optical constituents with deeper details in space and time in highly urbanized and perturbed regions.
Fil: Gauto, Víctor Hugo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina
Fil: Ferral, Anabella: Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Bonansea, Matias. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina
Fil: Farías, Alejandro. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Sobre Temas Ambientales y Químicos; Argentina.
Fil: Scavuzzo, Marcelo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Cardozo, Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación Para el Desarrollo Territorial y del Hábitat Humano; Argentina
Fil: Germán, Alba. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Giardino, Claudia. Instituto para la detección electromagnética de medio ambiente CNR-IREA; Italia
Peer Reviewed
Materia
PRISMA
Sentinel 2
hyperspectral
turbid waters
atmospheric correction
cromaticity
spectral signature
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2023-07-11T20:10:17Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/8253
Acceder
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network_acronym_str RIAUTN
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network_name_str Repositorio Institucional Abierto (UTN)
spelling First results of PRISMA satellite data applied to water quality monitoring in ArgentinaGauto, Víctor HugoFerral, AnabellaBonansea, MatiasFarías, Alejandro RubénScavuzzo, MarceloCardozo, OsvaldoGermán, AlbaGiardino, ClaudiaPRISMASentinel 2hyperspectralturbid watersatmospheric correctioncromaticityspectral signatureWater has historically been considered a renewable resource, however in the last century a sustained degradation of its quality has been observed, both in continental and oceanic systems due to anthropic impact. In this context, the management of water resources by satellite technology represents a central point in public policies since they allow anticipating and adapting to these disturbances. In this work, Sentinel 2-MSI multispectral and PRISMA hyperspectral sensors are used to carry out an analysis of different optical water types in North-East of Argentina. Convolutional procedure was used to compare sensors responses for atmospheric corrected products and RMSE (root mean square error), BIAS and MAE (mean absolute error) metrics were used to assess their performance. Differences below 1 percent were obtained in all cases, indicating an excellent match-up between both sensors. From hyperspectral PRISMA data it was possible to detect quantitative shift towards reddish wavelengths as turbidity of Parana River increases along a transect as well as an increase of the peak value in magnitude. This work opens new opportunities to monitor water quality changes related to optical constituents with deeper details in space and time in highly urbanized and perturbed regions.Fil: Gauto, Víctor Hugo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; ArgentinaFil: Ferral, Anabella: Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.Fil: Bonansea, Matias. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; ArgentinaFil: Farías, Alejandro. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Sobre Temas Ambientales y Químicos; Argentina.Fil: Scavuzzo, Marcelo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.Fil: Cardozo, Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación Para el Desarrollo Territorial y del Hábitat Humano; ArgentinaFil: Germán, Alba. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.Fil: Giardino, Claudia. Instituto para la detección electromagnética de medio ambiente CNR-IREA; ItaliaPeer Reviewed2023-07-11T20:10:17Z2023-07-11T20:10:17Z2022-09-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdf978-1-6654-8015-4http://hdl.handle.net/20.500.12272/8253https://doi.org/10.1109/ARGENCON55245.2022.9939810enginfo:eu-repo/semantics/openAccess2023-07-11T20:10:17ZAcceso abiertoreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:48:15Zoai:ria.utn.edu.ar:20.500.12272/8253instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:48:17.115Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv First results of PRISMA satellite data applied to water quality monitoring in Argentina
title First results of PRISMA satellite data applied to water quality monitoring in Argentina
spellingShingle First results of PRISMA satellite data applied to water quality monitoring in Argentina
Gauto, Víctor Hugo
PRISMA
Sentinel 2
hyperspectral
turbid waters
atmospheric correction
cromaticity
spectral signature
title_short First results of PRISMA satellite data applied to water quality monitoring in Argentina
title_full First results of PRISMA satellite data applied to water quality monitoring in Argentina
title_fullStr First results of PRISMA satellite data applied to water quality monitoring in Argentina
title_full_unstemmed First results of PRISMA satellite data applied to water quality monitoring in Argentina
title_sort First results of PRISMA satellite data applied to water quality monitoring in Argentina
dc.creator.none.fl_str_mv Gauto, Víctor Hugo
Ferral, Anabella
Bonansea, Matias
Farías, Alejandro Rubén
Scavuzzo, Marcelo
Cardozo, Osvaldo
Germán, Alba
Giardino, Claudia
author Gauto, Víctor Hugo
author_facet Gauto, Víctor Hugo
Ferral, Anabella
Bonansea, Matias
Farías, Alejandro Rubén
Scavuzzo, Marcelo
Cardozo, Osvaldo
Germán, Alba
Giardino, Claudia
author_role author
author2 Ferral, Anabella
Bonansea, Matias
Farías, Alejandro Rubén
Scavuzzo, Marcelo
Cardozo, Osvaldo
Germán, Alba
Giardino, Claudia
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv PRISMA
Sentinel 2
hyperspectral
turbid waters
atmospheric correction
cromaticity
spectral signature
topic PRISMA
Sentinel 2
hyperspectral
turbid waters
atmospheric correction
cromaticity
spectral signature
dc.description.none.fl_txt_mv Water has historically been considered a renewable resource, however in the last century a sustained degradation of its quality has been observed, both in continental and oceanic systems due to anthropic impact. In this context, the management of water resources by satellite technology represents a central point in public policies since they allow anticipating and adapting to these disturbances. In this work, Sentinel 2-MSI multispectral and PRISMA hyperspectral sensors are used to carry out an analysis of different optical water types in North-East of Argentina. Convolutional procedure was used to compare sensors responses for atmospheric corrected products and RMSE (root mean square error), BIAS and MAE (mean absolute error) metrics were used to assess their performance. Differences below 1 percent were obtained in all cases, indicating an excellent match-up between both sensors. From hyperspectral PRISMA data it was possible to detect quantitative shift towards reddish wavelengths as turbidity of Parana River increases along a transect as well as an increase of the peak value in magnitude. This work opens new opportunities to monitor water quality changes related to optical constituents with deeper details in space and time in highly urbanized and perturbed regions.
Fil: Gauto, Víctor Hugo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina
Fil: Ferral, Anabella: Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Bonansea, Matias. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina
Fil: Farías, Alejandro. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Sobre Temas Ambientales y Químicos; Argentina.
Fil: Scavuzzo, Marcelo. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Cardozo, Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación Para el Desarrollo Territorial y del Hábitat Humano; Argentina
Fil: Germán, Alba. Universidad Nacional de Córdoba. Instituto de Altos Estudios Espaciales Mario Gulich; Argentina.
Fil: Giardino, Claudia. Instituto para la detección electromagnética de medio ambiente CNR-IREA; Italia
Peer Reviewed
description Water has historically been considered a renewable resource, however in the last century a sustained degradation of its quality has been observed, both in continental and oceanic systems due to anthropic impact. In this context, the management of water resources by satellite technology represents a central point in public policies since they allow anticipating and adapting to these disturbances. In this work, Sentinel 2-MSI multispectral and PRISMA hyperspectral sensors are used to carry out an analysis of different optical water types in North-East of Argentina. Convolutional procedure was used to compare sensors responses for atmospheric corrected products and RMSE (root mean square error), BIAS and MAE (mean absolute error) metrics were used to assess their performance. Differences below 1 percent were obtained in all cases, indicating an excellent match-up between both sensors. From hyperspectral PRISMA data it was possible to detect quantitative shift towards reddish wavelengths as turbidity of Parana River increases along a transect as well as an increase of the peak value in magnitude. This work opens new opportunities to monitor water quality changes related to optical constituents with deeper details in space and time in highly urbanized and perturbed regions.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-09
2023-07-11T20:10:17Z
2023-07-11T20:10:17Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 978-1-6654-8015-4
http://hdl.handle.net/20.500.12272/8253
https://doi.org/10.1109/ARGENCON55245.2022.9939810
identifier_str_mv 978-1-6654-8015-4
url http://hdl.handle.net/20.500.12272/8253
https://doi.org/10.1109/ARGENCON55245.2022.9939810
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2023-07-11T20:10:17Z
Acceso abierto
eu_rights_str_mv openAccess
rights_invalid_str_mv 2023-07-11T20:10:17Z
Acceso abierto
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.24418

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