@article{fdi:010089497,
  title = {{S}patiotemporal variations in biophysical water quality parameters: an integrated in situ and remote sensing analysis of an urban lake in {C}hile},
  author = {{Y}{\'e}pez, {S}. and {V}elásquez, {G}. and {T}orres, {D}. and {S}aavedra-{P}assache, {R}. and {P}incheira, {M}. and {C}id, {H}. and {R}odríguez-{L}ópez, {L}. and {C}ontreras, {A}. and {F}rappart, {F}. and {C}ristóbal, {J}. and {P}ons, {X}. and {F}lores, {N}. and {B}ourrel, {L}uc},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the {B}iobio region, {S}outh-{C}entral {C}hile, by analyzing time series of {L}andsat-8 {OLI} satellite images. {T}he bio-optical parameters, i.e., chlorophyll-a ({C}hl-a, in mg center dot m-3) and turbidity (in {NTU}) were measured in situ during a satellite overpass to minimize the impact of atmospheric distortions. {T}o calibrate the satellite images, various atmospheric correction methods (including {ACOLITE}, {C}2{RCC}, i{COR}, and {L}a{SRC}) were evaluated during the image preprocessing phase. {S}pectral signatures obtained from the scenes for each atmospheric correction method were then compared with spectral signatures acquired in situ on the water surface. {I}n short, the {ACOLITE} model emerged as the best fit for the calibration process, reaching {R}2 values of 0.88 and 0.79 for {C}hl-a and turbidity, respectively. {T}his underlies the importance of using inversion models, when processing water surfaces, to mitigate errors due to aerosols and the sun-glint effect. {S}ubsequently, reflectance data derived from the {ACOLITE} model were used to establish correlations between various spectral indices and the in situ data. {T}he empirical retrieval models (based on band combinations) yielding superior performance, with higher {R}2 values, were subjected to a rigorous statistical validation and optimization by applying a bootstrapping approach. {F}rom this process the green chlorophyll index ({GCI}) was selected as the optimal choice for constructing the {C}hl-a retrieval model, reaching an {R}2 of 0.88, while the red + {NIR} spectral index achieved the highest {R}2 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. {O}ur 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. {W}e identified a striking eight-year period (2014-2022) characterized by a decline in {C}hl-a concentration in the lake, possibly attributable to governmental measures in the region for the protection and conservation of the lake. {A}dditionally, the {OLI} imagery showed a spatial pattern varying from higher {C}hl-a values in the northern zone compared to the southern zone, probably due to the heat island effect of the northern urban areas. {T}he 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.},
  keywords = {eutrophication ; {L}andsat ; {C}hl-a ; turbidity ; spectral signatures ; {OLI} ; {C}hile ; {CHILI}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {16},
  numero = {2},
  pages = {427 [25 p.]},
  year = {2024},
  DOI = {10.3390/rs16020427},
  URL = {https://www.documentation.ird.fr/hor/fdi:010089497},
}