Preprints
https://doi.org/10.5194/essd-2024-28
https://doi.org/10.5194/essd-2024-28
04 Mar 2024
 | 04 Mar 2024
Status: this preprint is currently under review for the journal ESSD.

TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning

Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan

Abstract. Rock glaciers – periglacial landforms commonly found in high mountain systems – are of significant scientific value for inferring the presence of permafrost, understanding mountain hydrology, and assessing climate impacts on high mountain environments. However, inventories remain patchy in many alpine regions, and as a result they are poorly understood for some areas of High Mountain Asia such as the Tibetan Plateau. To address this gap, we compiled a comprehensive inventory of rock glaciers across the entire Tibetan plateau, i.e., TPRoGI [v1.0], developed using an innovative deep learning method. This inventory consists of a total of 44,273 rock glaciers, covering approximately 6,000 km2, with a mean area of 0.14 km2. They are predominantly situated at elevations ranging from 4,000 to 5,500 m.a.s.l., with a mean of 4,729 m.a.s.l.. widespread in the northwestern and southeastern areas, with dense concentrations in the Western Pamir and Nyainqêntanglha, while they are sparsely distributed in the inner part. Our inventory serves as a benchmark dataset, which will be further They tend to occur on slopes with gradients between 10° and 25°, with a mean of 17.7°. Across the plateau, rock glaciers are maintained and updated in the future. This dataset constitutes a significant contribution towards understanding, future monitoring and assessment of permafrost on the Tibetan Plateau in the context of climate change.

Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan

Status: open (until 15 May 2024)

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Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan

Data sets

TPRoGI: a complete rock glacier inventory for the Tibetan Plateau using deep learning Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan https://doi.org/10.5281/zenodo.10732042

Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan

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Short summary
We propose a new dataset, TPRoGI [v1.0], encompassing rock glaciers in the entire Tibetan Plateau. We used a neural network, DeepLabv3+, and images from Planet Basemaps. The inventory identified 44,273 rock glaciers, covering 6,000 km2, mainly at elevations of 4,000 to 5,500 m.a.s.l. The dataset, with details on distribution and characteristics, aids in understanding permafrost distribution, mountain hydrology, and climate impacts in High Mountain Asia, filling a knowledge gap.
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