Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir

Autores
Bonansea, Matias; Rodriguez, Claudia; Pinotti, Lucio Pedro
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 ¼ 0.88). Using observed versus predicted Chl-a values the model was validated (R2 ¼ 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.
Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina
Fil: Rodriguez, Claudia. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina
Fil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina
Materia
CHLOROPHYLL-A
LANDSAT
REMOTE SENSING
SENSORS
WATER QUALITY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/138353

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spelling Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoirBonansea, MatiasRodriguez, ClaudiaPinotti, Lucio PedroCHLOROPHYLL-ALANDSATREMOTE SENSINGSENSORSWATER QUALITYhttps://purl.org/becyt/ford/2.7https://purl.org/becyt/ford/2Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 ¼ 0.88). Using observed versus predicted Chl-a values the model was validated (R2 ¼ 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; ArgentinaFil: Rodriguez, Claudia. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; ArgentinaFil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; ArgentinaIWA Publishing2018-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/138353Bonansea, Matias; Rodriguez, Claudia; Pinotti, Lucio Pedro; Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir; IWA Publishing; Hydrology Research; 49; 5; 10-2018; 1608-16171998-95632224-7955CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://iwaponline.com/hr/article/49/5/1608/38863/Assessing-the-potential-of-integrating-Landsatinfo:eu-repo/semantics/altIdentifier/doi/10.2166/nh.2017.116info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:39:46Zoai:ri.conicet.gov.ar:11336/138353instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:39:46.515CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
title Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
spellingShingle Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
Bonansea, Matias
CHLOROPHYLL-A
LANDSAT
REMOTE SENSING
SENSORS
WATER QUALITY
title_short Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
title_full Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
title_fullStr Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
title_full_unstemmed Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
title_sort Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir
dc.creator.none.fl_str_mv Bonansea, Matias
Rodriguez, Claudia
Pinotti, Lucio Pedro
author Bonansea, Matias
author_facet Bonansea, Matias
Rodriguez, Claudia
Pinotti, Lucio Pedro
author_role author
author2 Rodriguez, Claudia
Pinotti, Lucio Pedro
author2_role author
author
dc.subject.none.fl_str_mv CHLOROPHYLL-A
LANDSAT
REMOTE SENSING
SENSORS
WATER QUALITY
topic CHLOROPHYLL-A
LANDSAT
REMOTE SENSING
SENSORS
WATER QUALITY
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.7
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 ¼ 0.88). Using observed versus predicted Chl-a values the model was validated (R2 ¼ 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.
Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina
Fil: Rodriguez, Claudia. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina
Fil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina
description Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 ¼ 0.88). Using observed versus predicted Chl-a values the model was validated (R2 ¼ 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
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 http://hdl.handle.net/11336/138353
Bonansea, Matias; Rodriguez, Claudia; Pinotti, Lucio Pedro; Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir; IWA Publishing; Hydrology Research; 49; 5; 10-2018; 1608-1617
1998-9563
2224-7955
CONICET Digital
CONICET
url http://hdl.handle.net/11336/138353
identifier_str_mv Bonansea, Matias; Rodriguez, Claudia; Pinotti, Lucio Pedro; Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir; IWA Publishing; Hydrology Research; 49; 5; 10-2018; 1608-1617
1998-9563
2224-7955
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://iwaponline.com/hr/article/49/5/1608/38863/Assessing-the-potential-of-integrating-Landsat
info:eu-repo/semantics/altIdentifier/doi/10.2166/nh.2017.116
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv IWA Publishing
publisher.none.fl_str_mv IWA Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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