2026-04-14T02:37:38Zhttps://recercat.cat/oai/requestoai:recercat.cat:20.500.12327/28202025-10-22T11:33:42Zcom_2072_4428com_2072_4427col_2072_487898
RECERCAT
author
Yépez, Santiago
author
Velásquez, Germán
author
Torres, Daniel
author
Saavedra-Passache, Rodrigo
author
Pincheira, Martin
author
Cid, Hayleen
author
Rodríguez-López, Lien
author
Contreras, Frédéric
author
Frappart, Frédéric
author
Cristóbal, Jordi
author
Pons, Xavier
author
Flores, Neftali
author
Bourrel, Luc
other
Producció Vegetal
group
Ús Eficient de l'Aigua en Agricultura
2025-10-22T11:33:41Z
2025-10-22T11:33:41Z
2024-01-22
Yépez, Santiago, Germán Velásquez, Daniel J. Torres, Rodrigo Saavedra-Passache, Martin Pincheira, Hayleen Cid, Lien Rodríguez‐López, et al. 2024. “Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated in Situ and Remote Sensing Analysis of an Urban Lake in Chile.” Remote Sensing 16 (2): 427. https://doi.org/10.3390/rs16020427.
2072-4292
http://hdl.handle.net/20.500.12327/2820
https://doi.org/10.3390/rs16020427
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.
eng
Attribution 4.0 International
Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile
info:eu-repo/semantics/article