Satellite images reveal reduced lake chlorophyll concentration and eutrophication in China

Chlorophyll-a (Chl-a) concentration in lake water is an indicator of its trophic state and water quality. Although many anthropogenic drivers have increased lake trophic state, leading to severe negative consequences, many environmental policies and management were done towards improving water quality. Here, we analyzed the Chl-a concentration maps derived from Landsat images during 1990–2020 and assessed the changes of trophic states over > 1138 large lakes (surface water areas larger than 1 km 2 ), which together account for 60.1 % of total lake areas in China. The average Chl-a concentration over all the lakes declined more rapidly after 2010. Lake trophic states dropped in 180 light-eutrophic lakes (10 < Chl-a < 26, μg L -1 ), but rose in 14.29 % oligotrophic lakes (Chl-a < 1.6, μg L -1 ). We observed pronounced decreases in averaged Chl-a levels since 2010, accompanied by increased identified mesotrophic and oligotrophic states; however, this shift exhibited considerable variability across different provinces. The climate change (i.e., increased temperature, decreased precipitation) often lead to increases in Chl-a concentration, but the implementation of national environmental policies lead to decreases in lake Chl-a levels since 2010, particular in those provinces with large economy.

Authors

Publication Details

Journal
ISPRS Journal of Photogrammetry and Remote Sensing
Published
2025-12-27
DOI
https://doi.org/10.1016/j.isprsjprs.2025.12.020
Primary Topic
Aquatic Ecosystems and Phytoplankton Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Satellite images reveal reduced lake chlorophyll concentration and eutrophication in China

Lele Zhang, Sijia LI, Haoyun Zhou, Yingxin Shang et al.
ISPRS Journal of Photogrammetry and Remote Sensing
Aquatic Ecosystems and Phytoplankton Dynamics
article

Satellite images reveal reduced lake chlorophyll concentration and eutrophication in China

Lele Zhang, Sijia LI, Haoyun Zhou, Yingxin Shang, Chong Fang, Xiangming Xiao, Yong Li, Hui Tao, Zhidan Wen, Qiang Wang, Ge Liu, Kaishan Song
article en

Abstract

Chlorophyll-a (Chl-a) concentration in lake water is an indicator of its trophic state and water quality. Although many anthropogenic drivers have increased lake trophic state, leading to severe negative consequences, many environmental policies and management were done towards improving water quality. Here, we analyzed the Chl-a concentration maps derived from Landsat images during 1990–2020 and assessed the changes of trophic states over > 1138 large lakes (surface water areas larger than 1 km 2 ), which together account for 60.1 % of total lake areas in China. The average Chl-a concentration over all the lakes declined more rapidly after 2010. Lake trophic states dropped in 180 light-eutrophic lakes (10 < Chl-a < 26, μg L -1 ), but rose in 14.29 % oligotrophic lakes (Chl-a < 1.6, μg L -1 ). We observed pronounced decreases in averaged Chl-a levels since 2010, accompanied by increased identified mesotrophic and oligotrophic states; however, this shift exhibited considerable variability across different provinces. The climate change (i.e., increased temperature, decreased precipitation) often lead to increases in Chl-a concentration, but the implementation of national environmental policies lead to decreases in lake Chl-a levels since 2010, particular in those provinces with large economy.

ISPRS Journal of Photogrammetry and Remote SensingVol. 232
Clean water and sanitation
Openalex Percentile: Top 38%
Aquatic Ecosystems and Phytoplankton Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.