Retrieval of Chlorophyll-a Concentration in Poyang Lake by Using Multi-annual and Simultaneous Satellite-Ground Remote Sensing

ZHENG Pu; XU Xin-fa; XU Xiao-hua; CHEN Xin-yu; ZHANG Ren-gao

doi:10.11988/ckyyb.20230292

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Journal of Changjiang River Scientific Research Institute ›› 2024, Vol. 41 ›› Issue (7) : 48-56. DOI: 10.11988/ckyyb.20230292

Water Environment And Water Ecology

Retrieval of Chlorophyll-a Concentration in Poyang Lake by Using Multi-annual and Simultaneous Satellite-Ground Remote Sensing

ZHENG Pu^1,2, XU Xin-fa^1,2, XU Xiao-hua^1,2, CHEN Xin-yu³, ZHANG Ren-gao⁴

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Abstract

Poyang Lake, situated in north-central Jiangxi Province, is the largest freshwater lake in China and connects to the Yangtze River. Given its size and location, the lake’s water ecological security profoundly impacts the entire Yangtze River basin. Chlorophyll-a concentration serves as a crucial indicator of water ecological eutrophication, underscoring the importance of routine remote sensing monitoring. This study focuses on Poyang Lake, using chlorophyll-a as a proxy for eutrophication. By analyzing six years of observation data (2015-2020) and LandSat images, a retrieval model for summer chlorophyll-a concentration in Poyang Lake was developed. This model employs standard modeling techniques and ensures “satellite-ground” coordination to accurately match data. Through correlation analysis between various wavelength bands and chlorophyll-a concentration, the study constructs a robust retrieval model. Verification with six independent datasets yielded a mean R² value of 0.86, RMSE of 1.01 μg/L, and MAPE of 17.6%. These results validate the efficacy of the method for chlorophyll-a retrieval in Poyang Lake and suggest its potential application as a reference for long-term monitoring of chlorophyll-a in similar inland Class II water bodies.

Key words

remote sensing / Poyang lake / chlorophyll-a / correlation analysis

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ZHENG Pu, XU Xin-fa, XU Xiao-hua, CHEN Xin-yu, ZHANG Ren-gao. Retrieval of Chlorophyll-a Concentration in Poyang Lake by Using Multi-annual and Simultaneous Satellite-Ground Remote Sensing[J]. Journal of Changjiang River Scientific Research Institute. 2024, 41(7): 48-56 https://doi.org/10.11988/ckyyb.20230292

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