Hyperspectral Satellite Remote Sensing of Water Quality in Lake Atitlán, Guatemala

Africa I. Flores-Anderson, Robert Griffin, Margaret Dix, Claudia S. Romero-Oliva, Gerson Ochaeta, Juan Skinner-Alvarado, Maria Violeta Ramirez Moran, Betzy Hernandez, Emil Cherrington, Benjamin Page, Flor Barreno

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2 Scopus citations


In this study we evaluated the applicability of a space-borne hyperspectral sensor, Hyperion, to resolve for chlorophyll a (Chl a) concentration in Lake Atitlan, a tropical mountain lake in Guatemala. In situ water quality samples of Chl a concentration were collected and correlated with water surface reflectance derived from Hyperion images, to develop a semi-empirical algorithm. Existing operational algorithms were tested and the continuous bands of Hyperion were evaluated in an iterative manner. A third order polynomial regression provided a good fit to model Chl a. The final algorithm uses a blue (467 nm) to green (559 nm) band ratio to successfully model Chl a concentrations in Lake Atitlán during the dry season, with a relative error of 33%. This analysis confirmed the suitability of hyperspetral-imagers like Hyperion, to model Chl a concentrations in Lake Atitlán. This study also highlights the need to test and update this algorithm with operational multispectral sensors such as Landsat and Sentinel-2.

Original languageEnglish (US)
Article number7
JournalFrontiers in Environmental Science
StatePublished - Feb 5 2020


  • chlorophyll a concentration
  • Guatemala
  • hyperspectral remote sensing
  • Lake Atitlán
  • water quality

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    Flores-Anderson, A. I., Griffin, R., Dix, M., Romero-Oliva, C. S., Ochaeta, G., Skinner-Alvarado, J., Ramirez Moran, M. V., Hernandez, B., Cherrington, E., Page, B., & Barreno, F. (2020). Hyperspectral Satellite Remote Sensing of Water Quality in Lake Atitlán, Guatemala. Frontiers in Environmental Science, 8, [7]. https://doi.org/10.3389/fenvs.2020.00007