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Article

Monitoring the Vertical Variations in Chlorophyll-a Concentration in Lake Chaohu Using the Geostationary Ocean Color Imager

1
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2
Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
3
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
4
University of Chinese Academy of Sciences, Beijing 100049, China
5
Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Huaiyin Normal University, Huaian 223001, China
6
NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD 20740, USA
7
CIRA, Colorado State University, Fort Collins, CO 80523, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(14), 2611; https://doi.org/10.3390/rs16142611
Submission received: 20 May 2024 / Revised: 12 July 2024 / Accepted: 15 July 2024 / Published: 17 July 2024

Abstract

Due to the external environment and the buoyancy of cyanobacteria, the inhomogeneous vertical distribution of phytoplankton in eutrophic lakes affects remote sensing reflectance (Rrs) and the inversion of surface chlorophyll-a concentration (Chla). In this study, vertical profiles of Chla(z) (where z is the water depth) and field Rrs (Rrs_F) were collected and utilized to retrieve the vertical profiles of Chla in Lake Chaohu in China. Chla(z) was categorized into vertically uniform (Type 1: N = 166) and vertically non-uniform (Type 2: N = 58) types. Based on the validation of the atmospheric correction performance of the Geostationary Ocean Color Imager (GOCI), a Chla(z) inversion model was developed for Lake Chaohu from 2011 to 2020 using GOCI Rrs data (Rrs_G). (1) Five functions of non-uniform Chla(z) were compared, and the best result was found for Chla(z) = a·exp(b·z) + c (R2 = 0.98, RMSE = 38.15 μg/L). (2) A decision tree of Chla(z) was established with the alternative floating algae index (AFAIRrs), the fluorescence line height (FLH), and wind speed (WIN), where the overall accuracy was 89% and the kappa coefficient was 0.79. The Chla(z) inversion model for Type 1 was established using the empirical relationship between Chla (z = surface) and AFAIRrs (R2 = 0.58, RMSE = 10.17 μg/L). For Type 2, multivariate regression models were established to estimate the structural parameters of Chla(z) combined with Rrs_G and environmental parameters (R2 = 0.75, RMSE = 72.80 μg/L). (3) There are obvious spatial variations in Chla(z), especially from the water surface to a depth of 0.1 m; the largest diurnal variations were observed at 12:16 and 13:16 local time. The Chla(z) inversion method can determine Chla in different layers of each pixel, which is important for the scientific assessment of phytoplankton biomass and lake carbon and can provide vertical information for the short-term prediction of algal blooms (and the generation of corresponding warnings) in lake management.
Keywords: chlorophyll-a concentration; geostationary satellite; GOCI; vertical distribution; diurnal variations chlorophyll-a concentration; geostationary satellite; GOCI; vertical distribution; diurnal variations

Share and Cite

MDPI and ACS Style

Li, H.; Wei, X.; Huang, Z.; Liu, H.; Ma, R.; Wang, M.; Hu, M.; Jiang, L.; Xue, K. Monitoring the Vertical Variations in Chlorophyll-a Concentration in Lake Chaohu Using the Geostationary Ocean Color Imager. Remote Sens. 2024, 16, 2611. https://doi.org/10.3390/rs16142611

AMA Style

Li H, Wei X, Huang Z, Liu H, Ma R, Wang M, Hu M, Jiang L, Xue K. Monitoring the Vertical Variations in Chlorophyll-a Concentration in Lake Chaohu Using the Geostationary Ocean Color Imager. Remote Sensing. 2024; 16(14):2611. https://doi.org/10.3390/rs16142611

Chicago/Turabian Style

Li, Hanhan, Xiaoqi Wei, Zehui Huang, Haoze Liu, Ronghua Ma, Menghua Wang, Minqi Hu, Lide Jiang, and Kun Xue. 2024. "Monitoring the Vertical Variations in Chlorophyll-a Concentration in Lake Chaohu Using the Geostationary Ocean Color Imager" Remote Sensing 16, no. 14: 2611. https://doi.org/10.3390/rs16142611

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