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.