Estimation of Chlorophyll-A Concentration with Remotely Sensed Data for the Nine Plateau Lakes in Yunnan Province

Dong Wang; Bo-Hui Tang; Zhitao Fu; Liang Huang; Menghua Li; Guokun Chen; Xuejun Pan

doi:10.3390/rs14194950

Remote Sensing (Oct 2022)

Estimation of Chlorophyll-A Concentration with Remotely Sensed Data for the Nine Plateau Lakes in Yunnan Province

Dong Wang,
Bo-Hui Tang,
Zhitao Fu,
Liang Huang,
Menghua Li,
Guokun Chen,
Xuejun Pan

Affiliations

Dong Wang: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Bo-Hui Tang: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Zhitao Fu: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Liang Huang: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Menghua Li: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Guokun Chen: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Xuejun Pan: Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650093, China

DOI: https://doi.org/10.3390/rs14194950
Journal volume & issue: Vol. 14, no. 19
p. 4950

Abstract

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The quantitative retrieval of the chlorophyll-a concentration is an important remote sensing method that is used to monitor the nutritional status of water bodies. The high spatial resolution of the Sentinel-2 MSI and its subdivision in the red-edge band highlight the characteristics of water chlorophyll-a, which is an important detection tool for assessing water quality parameters in plateau lakes. In this study, the Nine Plateau Lakes in the Yunnan-Kweichow Plateau of China were selected as the study area. Using Sentinel-2 MSI transit images and in situ measured chlorophyll-a concentration as the data source, the chlorophyll-a concentrations of plateau lakes (CCAPLs) were investigated, and the surface temperatures of plateau lakes (STPLs) were retrieved to verify the hypothesis that the lake surface temperature could increase the chlorophyll-a concentration. By comparing feature importance using a random forest (RF), the Sentinel-2 MSI surface reflectance and in situ data were linearly fitted using four retrieval spectral indices with high feature importance, and the accuracy of the estimated concentration of chlorophyll-a was evaluated by monitoring station data in the same period. Then, Landsat-8 TIRS Band 10 data were used to retrieve the STPL with a single-channel temperature retrieval algorithm and to verify the correlation between the STPL and the CCAPL. The results showed that the retrievals of the CCAPL and the STPL were consistent with the actual situation. The root-mean-square error (RMSE) of the fifteenth normalized difference chlorophyll-a index (NDCI15) was 0.0249. When the CCAPL was greater than 0.05 mg/L and the STPL was within 28–34 °C, there was a positive linear correlation between the CCAPL and the STPL. These results will provide support for the remote sensing monitoring of eutrophication in plateau lakes and will contribute to the scientific and effective management of plateau lakes.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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