Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3517-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3517-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Long-term water clarity patterns of lakes across China using Landsat series imagery from 1985 to 2020
Xidong Chen
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Xiao Zhang
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Junsheng Li
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Shenglei Wang
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Yuan Gao
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Sciences, Beijing Normal University, Beijing 100875, China
Jun Mi
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
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Cited
10 citations as recorded by crossref.
- Monitoring water clarity of lakes in the Middle-Lower Yangtze Plain using Landsat observations (1984–2023) M. Chen et al. 10.1016/j.ecolind.2024.112825
- Spatiotemporal Dynamics of Remote-Sensed Forel–Ule Index for Inland Waters Across China During the COVID-19 Pandemic L. Xu et al. 10.1109/JSTARS.2023.3298108
- Regional to global assessments of ocean transparency dynamics from 1997 to 2019 J. Guo et al. 10.1016/j.pocean.2023.103165
- Using the Forel-Ule index (FUI) to track the water quality of subsidence water bodies across the life cycle of coal mining in eastern China W. Chen et al. 10.1016/j.jenvman.2025.124037
- Temporal and spatial characteristics and driving forces of lakes in the Mongolia-Xinjiang Plateau during 1989-2021 Y. Bowen et al. 10.18307/2024.0461
- Towards global long-term water transparency products from the Landsat archive D. Maciel et al. 10.1016/j.rse.2023.113889
- Regional Accuracy Assessment of 30-Meter GLC_FCS30, GlobeLand30, and CLCD Products: A Case Study in Xinjiang Area J. Liu et al. 10.3390/rs16010082
- Quantifying the 2022 extreme drought in the Yangtze River Basin using GRACE-FO A. Duan et al. 10.1016/j.jhydrol.2024.130680
- Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors W. Hu et al. 10.1016/j.ejrh.2024.102118
- Increasing Socioeconomic Exposure to Compound Dry and Hot Events Under a Warming Climate in the Yangtze River Basin J. Zhang et al. 10.3390/su162411264
10 citations as recorded by crossref.
- Monitoring water clarity of lakes in the Middle-Lower Yangtze Plain using Landsat observations (1984–2023) M. Chen et al. 10.1016/j.ecolind.2024.112825
- Spatiotemporal Dynamics of Remote-Sensed Forel–Ule Index for Inland Waters Across China During the COVID-19 Pandemic L. Xu et al. 10.1109/JSTARS.2023.3298108
- Regional to global assessments of ocean transparency dynamics from 1997 to 2019 J. Guo et al. 10.1016/j.pocean.2023.103165
- Using the Forel-Ule index (FUI) to track the water quality of subsidence water bodies across the life cycle of coal mining in eastern China W. Chen et al. 10.1016/j.jenvman.2025.124037
- Temporal and spatial characteristics and driving forces of lakes in the Mongolia-Xinjiang Plateau during 1989-2021 Y. Bowen et al. 10.18307/2024.0461
- Towards global long-term water transparency products from the Landsat archive D. Maciel et al. 10.1016/j.rse.2023.113889
- Regional Accuracy Assessment of 30-Meter GLC_FCS30, GlobeLand30, and CLCD Products: A Case Study in Xinjiang Area J. Liu et al. 10.3390/rs16010082
- Quantifying the 2022 extreme drought in the Yangtze River Basin using GRACE-FO A. Duan et al. 10.1016/j.jhydrol.2024.130680
- Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors W. Hu et al. 10.1016/j.ejrh.2024.102118
- Increasing Socioeconomic Exposure to Compound Dry and Hot Events Under a Warming Climate in the Yangtze River Basin J. Zhang et al. 10.3390/su162411264
Latest update: 21 Jan 2025
Short summary
A 30 m LAke Water Secchi Depth (LAWSD30) dataset of China was first developed for 1985–2020, and national-scale water clarity estimations of lakes in China over the past 35 years were analyzed. Lake clarity in China exhibited a significant downward trend before the 21st century, but improved after 2000. The developed LAWSD30 dataset and the evaluation results can provide effective guidance for water preservation and restoration.
A 30 m LAke Water Secchi Depth (LAWSD30) dataset of China was first developed for 1985–2020, and...