Articles | Volume 14, issue 1
https://doi.org/10.5194/essd-14-79-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-79-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
13 Jan 2022
Data description paper |
| 13 Jan 2022
| 13 Jan 2022
A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018
Hui Tao
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
School of Resources and Environment, University of the Chinese Academy of Sciences, Beijing, 100049, China
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
School of Environment and Planning, College of Urban Research and Planning, Liaocheng University, Liaocheng, 252000, China
Ge Liu
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Qiang Wang
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Zhidan Wen
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Pierre-Andre Jacinthe
Department of Earth Sciences, Indiana University–Purdue University Indianapolis, Indianapolis, IN 46202, USA
Xiaofeng Xu
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Jia Du
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Yingxin Shang
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Sijia Li
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Zongming Wang
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Lili Lyu
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Junbin Hou
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Xiang Wang
Center of Remote Sensing and Geographic Information, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
Dong Liu
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
Kun Shi
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
Baohua Zhang
School of Environment and Planning, College of Urban Research and Planning, Liaocheng University, Liaocheng, 252000, China
Hongtao Duan
CORRESPONDING AUTHOR
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
Data sets
Water clarity annual dynamics dataset across China (1990-2018) Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, and Zhidan Wen https://doi.org/10.11888/Hydro.tpdc.271571
Short summary
During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean 3.32 ± 0.38 m), while those in the northeastern region had the lowest Secchi disk depth (SDD) (mean 0.60 ± 0.09 m). Among the 10 814 lakes with > 10 years of SDD results, 55.4 % and 3.5 % experienced significantly increasing and decreasing trends of SDD, respectively. With the exception of Inner Mongolia–Xinjiang, more than half of lakes in all the other regions exhibited a significant trend of increasing SDD.
During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean...
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