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

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

JOURNAL=Frontiers in Environmental Science

VOLUME=8

YEAR=2020

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2020.00007

DOI=10.3389/fenvs.2020.00007

ISSN=2296-665X

ABSTRACT=<p>In this study we evaluated the applicability of a space-borne hyperspectral sensor, Hyperion, to resolve for chlorophyll a (Chl <italic>a</italic>) concentration in Lake Atitlan, a tropical mountain lake in Guatemala. <italic>In situ</italic> water quality samples of Chl <italic>a</italic> 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 <italic>a</italic>. The final algorithm uses a blue (467 nm) to green (559 nm) band ratio to successfully model Chl <italic>a</italic> 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 <italic>a</italic> 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.</p>