The Cryosphere
The Cryosphere
TC
Articles | Volume 20, issue 5
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.
https://doi.org/10.5194/tc-20-2977-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 5
Research article
 | 
22 May 2026
Research article |  | 22 May 2026

Estimation of snow depth from AMSR-2 based on an AutoML method over the Qinghai-Tibet Plateau

Xuan Li, Fan Xu, Chen Zhang, Tao Che, Liyun Dai, and Yanli Zhang

Viewed

Total article views: 9,745 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
8,069 1,416 260 9,745 429 467
  • HTML: 8,069
  • PDF: 1,416
  • XML: 260
  • Total: 9,745
  • BibTeX: 429
  • EndNote: 467
Views and downloads (calculated since 15 Jul 2025)
Cumulative views and downloads (calculated since 15 Jul 2025)

Viewed (geographical distribution)

Total article views: 9,745 (including HTML, PDF, and XML) Thereof 9,686 with geography defined and 59 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 07 Nov 2026
Download
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint