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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/138353
Ver los metadatos del registro completo
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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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1844613259005526016 |
score |
13.070432 |