Mapping and Characterizing Rock Glaciers in the Arid West Kunlun
of China
Yan Hu1,2, Lin Liu1,2, Lingcao
Huang3, Lin Zhao4,5, Tonghua
Wu4, Xiaowen Wang6,7 and Jiaxin
Cai6
1Institute of Environment, Energy and Sustainability,
The Chinese University of Hong Kong, Hong Kong SAR, China.
2Earth and Environmental Sciences Programme, Faculty
of Science, The Chinese University of Hong Kong, Hong Kong SAR, China.
3Earth Science and Observation Center, Cooperative
Institute for Research in Environmental Sciences, University of Colorado
Boulder, Boulder, CO, USA.
4Cryosphere Research Station on the Qinghai-Tibet
Plateau, State Key Laboratory of Cryospheric Science, Northwest
Institute of Eco-Environment and Resources, Chinese Academy of Sciences,
Lanzhou, China.
5School of Geographical Sciences, Nanjing University
of Information Science and Technology, Nanjing, China.
6Faculty of Geosciences and Environmental Engineering,
Southwest Jiaotong University, Chengdu, China.
7State-Province Joint Engineering Laboratory of
Spatial Information Technology of High-Speed Rail Safety, Chengdu,
China.
Corresponding author: Yan Hu
(huyan@link.cuhk.edu.hk)
Key Points:
- A combined use of deep learning and InSAR automates mapping rock
glaciers at the regional scale
- We compile the first rock glacier inventory in West Kunlun with
kinematic and geomorphic information documented
- Geomorphologic characteristics of rock glaciers provide insights on
the glacial and periglacial processes and interactions in West Kunlun
Abstract
Rock glaciers manifest the creep of mountain permafrost occurring in the
past or at present. Their presence and dynamics are indicators of
permafrost distribution and changes in response to climate forcing.
Knowledge of rock glaciers is completely lacking in the West Kunlun, one
of the driest mountain ranges in Asia, where widespread permafrost is
rapidly warming. In this study, we first mapped and quantified the
kinematics of active rock glaciers based on satellite Interferometric
Synthetic Aperture Radar (InSAR) and Google Earth images. Then we
trained DeepLabv3+, a deep learning network for semantic image
segmentation, to automate the mapping task. The well-trained model was
applied for a region-wide, extensive delineation of rock glaciers from
Sentinel-2 images to map the landforms that were previously missed due
to the limitations of the InSAR-based identification. Finally, we mapped
413 rock glaciers across the West Kunlun: 290 of them were active rock
glaciers mapped manually based on InSAR and 123 of them were newly
identified and outlined by deep learning. The rock glaciers are
categorized by their spatial connection to the upslope geomorphic units.
All the rock glaciers are located at altitudes between 3,389 m and 5,541
m with an average size of 0.26 km2 and a mean slope
angle of 17°. The mean and maximum surface downslope velocities of the
active ones are 24 cm yr-1 and 127 cm
yr-1, respectively. Characteristics of the rock
glaciers of different categories hold implications on the interactions
between glacial and periglacial processes in the West Kunlun.