Articles | Volume 14, issue 1
https://doi.org/10.5194/essd-14-79-2022
https://doi.org/10.5194/essd-14-79-2022
Data description paper
 | 
13 Jan 2022
Data description paper |  | 13 Jan 2022

A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018

Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, Zhidan Wen, Pierre-Andre Jacinthe, Xiaofeng Xu, Jia Du, Yingxin Shang, Sijia Li, Zongming Wang, Lili Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, and Hongtao Duan

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Cited articles

Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., Moghaddam, S. H. A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., and Brisco, B.: Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review, IEEE J. Sel. Top. Appl., 13, 5326–5350, https://doi.org/10.1109/jstars.2020.3021052, 2020. 
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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.
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