Articles | Volume 16, issue 12
https://doi.org/10.5194/essd-16-5703-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5703-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
17 Dec 2024
Data description article |
| 17 Dec 2024
| 17 Dec 2024
TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning
Zhangyu Sun
Department of Earth and Environmental Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China
Department of Earth and Environmental Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China
Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China
Adina Racoviteanu
Université Grenoble Alpes, CNRS, IRD, IGE, Saint-Martin-d'Hères, France
Department of Earth and Environmental Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China
Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China
Stephan Harrison
Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom
Xiaowen Wang
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China
Jiaxin Cai
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China
Xin Guo
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China
Yujun He
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China
Hailun Yuan
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China
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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 4000 to 5500 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.
We propose a new dataset, TPRoGI (v1.0), encompassing rock glaciers in the entire Tibetan...
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