Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-903-2026
https://doi.org/10.5194/essd-18-903-2026
Data description paper
 | 
04 Feb 2026
Data description paper |  | 04 Feb 2026

A lake salinity dataset produced via microwave and optical imageries

Mingming Deng, Ronghua Ma, Lixin Wang, Minqi Hu, Kun Xue, and Junfeng Xiong

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Cited articles

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Bayati, M. and Danesh-Yazdi, M.: Mapping the spatiotemporal variability of salinity in the hypersaline Lake Urmia using Sentinel-2 and Landsat-8 imagery, J. Hydrol., 595, 126032, https://doi.org/10.1016/j.jhydrol.2021.126032, 2021. 
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Cao, Z., Wang, M., Ma, R., Zhang, Y., Duan, H., Jiang, L., Xue, K., Xiong, J., and Hu, M.: A decade-long chlorophyll-a data record in lakes across China from VIIRS observations, Remote Sensing of Environment, 301, 113953, https://doi.org/10.1016/j.rse.2023.113953, 2024. 
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Short summary
Lake salinity is an important parameter to characterize physical and biogeochemical processes. We proposed a microwave-optical integrated framework for high-precision salinity estimation, producing a 10 m resolution Inner Mongolia Xinjiang Lake zone lake salinity dataset (2016–2024). Salinity increased significantly in Lake Daihai and Lake Dalinor. The dataset can contribute to research on salinization prevention and salinity budget research.
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