Articles | Volume 20, issue 5
https://doi.org/10.5194/tc-20-2977-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-2977-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 May 2026
Research article |
| 22 May 2026
| 22 May 2026
Estimation of snow depth from AMSR-2 based on an AutoML method over the Qinghai-Tibet Plateau
Xuan Li
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
Fan Xu
Tencent Dadi Tongtu (Beijing) Technology Co., Ltd., Beijing 100086, China
Chen Zhang
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China
Liyun Dai
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China
Yanli Zhang
CORRESPONDING AUTHOR
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
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Short summary
The microwaves used in current products to measure snow depth don't pick up on the small changes in snow depth on the Qinghai-Tibet Plateau. To deal with these issues, our study suggests a new way of doing things. This uses Auto Machine Learning, data from satellite and other geographical information. Our results show that the method we used is good for checking how snow cover changes in mountain areas.
The microwaves used in current products to measure snow depth don't pick up on the small changes...
