Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile

This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, South-Central Chile, by analyzing time series of Landsat-8 OLI satellite images. The bio-optical parameters, i.e., chlorophyll-a (Chl-a, in mg·m−3) and turbidity (in...

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Detalles Bibliográficos
Autores: Yépez, Santiago, Velásquez, Germán, Torres, Daniel, Saavedra-Passache, Rodrigo, Pincheira, Martin, Cid, Hayleen, Rodríguez-López, Lien, Contreras, Frédéric, Frappart, Frédéric, Cristóbal, Jordi, Pons, Xavier, Flores, Neftali, Bourrel, Luc
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.12327/2820
Acceso en línea:http://hdl.handle.net/20.500.12327/2820
https://doi.org/10.3390/rs16020427
Access Level:acceso abierto
Palabra clave:628
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spelling Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in ChileYépez, SantiagoVelásquez, GermánTorres, DanielSaavedra-Passache, RodrigoPincheira, MartinCid, HayleenRodríguez-López, LienContreras, FrédéricFrappart, FrédéricCristóbal, JordiPons, XavierFlores, NeftaliBourrel, Luc628This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, South-Central Chile, by analyzing time series of Landsat-8 OLI satellite images. The bio-optical parameters, i.e., chlorophyll-a (Chl-a, in mg·m−3) and turbidity (in NTU) were measured in situ during a satellite overpass to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction method were then compared with spectral signatures acquired in situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process, reaching R2 values of 0.88 and 0.79 for Chl-a and turbidity, respectively. This underlies the importance of using inversion models, when processing water surfaces, to mitigate errors due to aerosols and the sun-glint effect. Subsequently, reflectance data derived from the ACOLITE model were used to establish correlations between various spectral indices and the in situ data. The empirical retrieval models (based on band combinations) yielding superior performance, with higher R2 values, were subjected to a rigorous statistical validation and optimization by applying a bootstrapping approach. From this process the green chlorophyll index (GCI) was selected as the optimal choice for constructing the Chl-a retrieval model, reaching an R2 of 0.88, while the red + NIR spectral index achieved the highest R2 value (0.79) for turbidity analysis, although in the last case, it was necessary to incorporate data from several seasons for an adequate model training. Our analysis covered a broad spectrum of dates, seasons, and years, which allowed us to search deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014–2022) characterized by a decline in Chl-a concentration in the lake, possibly attributable to governmental measures in the region for the protection and conservation of the lake. Additionally, the OLI imagery showed a spatial pattern varying from higher Chl-a values in the northern zone compared to the southern zone, probably due to the heat island effect of the northern urban areas. The results of this study suggest a positive effect of recent local regulations and serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.This research was funded by the Chilean government through ANID’s Fondecyt Regular Project no. 1221091.info:eu-repo/semantics/publishedVersionMDPIProducció VegetalÚs Eficient de l'Aigua en Agricultura2024info:eu-repo/semantics/article25http://hdl.handle.net/20.500.12327/2820https://doi.org/10.3390/rs16020427reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésRemote SensingAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:20.500.12327/28202026-05-29T05:05:01Z
dc.title.none.fl_str_mv Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
title Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
spellingShingle Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
Yépez, Santiago
628
title_short Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
title_full Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
title_fullStr Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
title_full_unstemmed Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
title_sort Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
dc.creator.none.fl_str_mv Yépez, Santiago
Velásquez, Germán
Torres, Daniel
Saavedra-Passache, Rodrigo
Pincheira, Martin
Cid, Hayleen
Rodríguez-López, Lien
Contreras, Frédéric
Frappart, Frédéric
Cristóbal, Jordi
Pons, Xavier
Flores, Neftali
Bourrel, Luc
author Yépez, Santiago
author_facet Yépez, Santiago
Velásquez, Germán
Torres, Daniel
Saavedra-Passache, Rodrigo
Pincheira, Martin
Cid, Hayleen
Rodríguez-López, Lien
Contreras, Frédéric
Frappart, Frédéric
Cristóbal, Jordi
Pons, Xavier
Flores, Neftali
Bourrel, Luc
author_role author
author2 Velásquez, Germán
Torres, Daniel
Saavedra-Passache, Rodrigo
Pincheira, Martin
Cid, Hayleen
Rodríguez-López, Lien
Contreras, Frédéric
Frappart, Frédéric
Cristóbal, Jordi
Pons, Xavier
Flores, Neftali
Bourrel, Luc
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Producció Vegetal
Ús Eficient de l'Aigua en Agricultura
dc.subject.none.fl_str_mv 628
topic 628
description This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, South-Central Chile, by analyzing time series of Landsat-8 OLI satellite images. The bio-optical parameters, i.e., chlorophyll-a (Chl-a, in mg·m−3) and turbidity (in NTU) were measured in situ during a satellite overpass to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction method were then compared with spectral signatures acquired in situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process, reaching R2 values of 0.88 and 0.79 for Chl-a and turbidity, respectively. This underlies the importance of using inversion models, when processing water surfaces, to mitigate errors due to aerosols and the sun-glint effect. Subsequently, reflectance data derived from the ACOLITE model were used to establish correlations between various spectral indices and the in situ data. The empirical retrieval models (based on band combinations) yielding superior performance, with higher R2 values, were subjected to a rigorous statistical validation and optimization by applying a bootstrapping approach. From this process the green chlorophyll index (GCI) was selected as the optimal choice for constructing the Chl-a retrieval model, reaching an R2 of 0.88, while the red + NIR spectral index achieved the highest R2 value (0.79) for turbidity analysis, although in the last case, it was necessary to incorporate data from several seasons for an adequate model training. Our analysis covered a broad spectrum of dates, seasons, and years, which allowed us to search deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014–2022) characterized by a decline in Chl-a concentration in the lake, possibly attributable to governmental measures in the region for the protection and conservation of the lake. Additionally, the OLI imagery showed a spatial pattern varying from higher Chl-a values in the northern zone compared to the southern zone, probably due to the heat island effect of the northern urban areas. The results of this study suggest a positive effect of recent local regulations and serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12327/2820
https://doi.org/10.3390/rs16020427
url http://hdl.handle.net/20.500.12327/2820
https://doi.org/10.3390/rs16020427
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Remote Sensing
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 25
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812455

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