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

被引：39

作者：

Flores-Anderson, Africa, I ^{[1
,2
]}

Griffin, Robert ^{[1
,2
]}

Dix, Margaret ^{[3
]}

Romero-Oliva, Claudia S. ^{[3
]}

Ochaeta, Gerson ^{[4
]}

Skinner-Alvarado, Juan ^{[5
]}

Ramirez Moran, Maria Violeta ^{[5
]}

Hernandez, Betzy ^{[1
,2
]}

Cherrington, Emil ^{[1
,2
]}

Page, Benjamin ^{[6
]}

Barreno, Flor ^{[5
]}

机构：

[1] Univ Alabama, Earth Syst Sci Ctr, Huntsville, AL 35899 USA

[2] NASA SERVIR Sci Coordinat Off, Huntsville, AL 35899 USA

[3] Univ Valle Guatemala, Ctr Estudios Atitlan, Solola, Guatemala

[4] Autoridad Manejo Lago Peten Itza, Flores, Guatemala

[5] Author Sustainable Management Lake Atitlan Basin, Solola, Guatemala

[6] Univ Minnesota, Water Resources Ctr, Minneapolis, MN USA

来源：

FRONTIERS IN ENVIRONMENTAL SCIENCE | 2020年 / 8卷

关键词：

hyperspectral remote sensing; water quality; chlorophyll a concentration; Lake Atitlan; Guatemala; CYANOBACTERIAL BLOOMS; CHLOROPHYLL; ALGORITHMS; PHYTOPLANKTON; VALIDATION; RESERVOIR;

D O I：

10.3389/fenvs.2020.00007

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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 Atitlan 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 Atitlan. This study also highlights the need to test and update this algorithm with operational multispectral sensors such as Landsat and Sentinel-2.

引用

页数：13

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