@article{fdi:010095032,
  title = {{A}dvanced phycocyanin detection in a south {A}merican lake using landsat imagery and remote sensing [{C}orrection, 1 p.]},
  author = {{R}odriguez-{L}ópez, {L}. and {U}sta, {D}. {F}. {B}. and {D}uran-{L}lacer, {I}. and {A}lvarez, {L}. {B}. and {B}ourrel, {L}uc and {F}rappart, {F}. and {U}rrutia, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n this study, multispectral images were used to detect toxic blooms in {V}illarrica {L}ake in {C}hile, using a time series of water quality data from 1989 to 2024, based on the extraction of spectral information from {L}andsat 8 and 9 satellite imagery. {T}o explore the predictive capacity of these variables, we constructed 255 multiple linear regression models using different combinations of spectral bands and indices as independent variables, with phycocyanin concentration as the dependent variable. {T}he most effective model, selected through a stepwise regression procedure, incorporated seven statistically significant predictors (p < 0.05) and took the following form: {FCA} = {N}/{G} + {NDVI} + {B} + {GNDVI} + {EVI} + {SABI} + {CCI}. {T}his model achieved a strong fit to the validation data, with an {R}-2 of 0.85 and an {RMSE} of 0.10 mu g/{L}, indicating high explanatory power and relatively low error in phycocyanin estimation. {W}hen applied to the complete weekly time series of satellite observations, the model successfully captured both seasonal dynamics and interannual variability in phycocyanin concentrations ({R}-2 = 0.92; {RMSE} = 0.05 mu g/{L}). {T}hese results demonstrate the robustness and practical utility for long-term monitoring of harmful algal blooms in {L}ake {V}illarrica.},
  keywords = {remote sensing ; phycocyanin ; algal blooms ; lake ; {C}hile ; {CHILI}},
  booktitle = {},
  journal = {{F}rontiers in {R}emote {S}ensing},
  volume = {6},
  numero = {},
  pages = {1633522 [16 ] [+ {C}orrection, 6, 1714525, 1 p., 2026]},
  year = {2025},
  DOI = {10.3389/frsen.2025.1633522},
  URL = {https://www.documentation.ird.fr/hor/fdi:010095032},
}