Open AccessHyperspectral Satellite Remote Sensing of Water Quality in Lake Atitlán, Guatemala
Author(s) -
Africa Flores-Anderson,
Robert Griffin,
Margaret Dix,
Claudia S. Romero-Oliva,
Gerson Ochaeta,
Juan Skinner-Alvarado,
Maria Violeta Ramirez Moran,
B. E. Hernández,
Emil Cherrington,
Benjamin P. Page,
Flor Barreno
Publication year - 2020
Publication title -
frontiers in environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.225
H-Index - 37
ISSN - 2296-665X
DOI - 10.3389/fenvs.2020.00007
Subject(s) - hyperspectral imaging , multispectral image , remote sensing , environmental science , satellite , water quality , atmospheric correction , satellite imagery , reflectivity , geology , ecology , physics , optics , engineering , biology , aerospace engineering
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.
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