30&thinsp;m monthly glacier surface velocity mapping in the Kangri Karpo region (2015–2024) using multi-source remote sensing data fusion

Gao, Daoxun; Wu, Kunpeng; Duan, Yunpeng; Ji, Zhaoqi; Ma, Danyu; Bolch, Tobias; Huang, Cheng; Liu, Shiyin

doi:10.5194/tc-20-3559-2026

Articles | Volume 20, issue 6

https://doi.org/10.5194/tc-20-3559-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-20-3559-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 6

Research article

|

22 Jun 2026

Research article |

| 22 Jun 2026

30 m monthly glacier surface velocity mapping in the Kangri Karpo region (2015–2024) using multi-source remote sensing data fusion

Daoxun Gao, Kunpeng Wu, Yunpeng Duan, Zhaoqi Ji, Danyu Ma, Tobias Bolch, Cheng Huang, and Shiyin Liu

Supplement

https://doi.org/10.5194/tc-20-3559-2026-supplement

Data sets

30 m Monthly Glacier Surface Velocity Dataset for the Kangri Karpo Region, 2015–2024 Daoxun Gao and Kunpeng Wu https://doi.org/10.5281/zenodo.20361514

Landsat 8-9 Operational Land Imager/Thermal Infrared Sensor Level-1, Collection 2 Earth Resources Observation and Science (EROS) Center https://doi.org/10.5066/P975CC9B

Randolph Glacier Inventory - A Dataset of Global Glacier Outlines. (NSIDC-0770, Version 7) RGI Consortium https://doi.org/10.5067/F6JMOVY5NAVZ

Short summary

We mapped monthly glacier flow speeds in the Kangri Karpo region from 2015 to 2024 by combining measurements from several satellites and a drone survey. The merged maps are more complete and detailed than maps from any single source, with fewer gaps caused by clouds or difficult terrain. The results show where glaciers move fastest, how their speed changes through the year, and which glaciers have been speeding up or slowing down over the past decade.