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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Cited
16 citations as recorded by crossref.
- Integrating optical and InSAR data for machine learning-based rock glacier activity classification: Model evaluation across mountain regions X. Wang et al.
- 基于深度学习和遥感大数据的亚洲高山区2020年有时间戳标记的冰川编目 长. 柯 et al.
- Underestimated number and significance of rock glaciers on the Tibetan Plateau M. Feng et al.
- Occurrence and Characteristics of Rock Glaciers in Western Tien Shan A. Merekeyev et al.
- Rock Glacier Detection Using Satellite Embeddings and Machine Learning on Google Earth Engine V. Khajuria et al.
- A review of evolving remote sensing and automated techniques in rock glacier mapping S. Tamang et al.
- Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments A. Wen et al.
- Topographic primacy in rock glacier distribution revealed by GAMs and their water storage: Insights from a new polygonised inventory of the southeastern Tibetan Plateau P. Fu et al.
- A comprehensive rock glacier inventory for the Peruvian Andes (PRoGI): dataset, characterization and topoclimatic attributes K. Medina et al.
- A new time-stamped glacier inventory of High Mountain Asia based on deep learning and remote sensing big data in 2020 C. Ke et al.
- Time-Series models for ground subsidence and heave over permafrost in InSAR Processing: A comprehensive assessment and new improvement C. Fan et al.
- Detection and reconstruction of rock glacier kinematics over 24 years (2000–2024) from Landsat imagery D. Cusicanqui et al.
- Rock Glacier Inventories (RoGIs) in 12 areas worldwide using a multi-operator consensus-based procedure L. Rouyet et al.
- Underestimated small thermokarst lakes of the Qinghai-Tibet Plateau and their carbon emission potential X. Peng et al.
- RGIK guidelines for compiling consistent rock glacier inventories F. Brardinoni et al.
- Temporal scale dictates the dominant driver of lake dynamics on the Tibetan Plateau T. Li et al.
16 citations as recorded by crossref.
- Integrating optical and InSAR data for machine learning-based rock glacier activity classification: Model evaluation across mountain regions X. Wang et al.
- 基于深度学习和遥感大数据的亚洲高山区2020年有时间戳标记的冰川编目 长. 柯 et al.
- Underestimated number and significance of rock glaciers on the Tibetan Plateau M. Feng et al.
- Occurrence and Characteristics of Rock Glaciers in Western Tien Shan A. Merekeyev et al.
- Rock Glacier Detection Using Satellite Embeddings and Machine Learning on Google Earth Engine V. Khajuria et al.
- A review of evolving remote sensing and automated techniques in rock glacier mapping S. Tamang et al.
- Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments A. Wen et al.
- Topographic primacy in rock glacier distribution revealed by GAMs and their water storage: Insights from a new polygonised inventory of the southeastern Tibetan Plateau P. Fu et al.
- A comprehensive rock glacier inventory for the Peruvian Andes (PRoGI): dataset, characterization and topoclimatic attributes K. Medina et al.
- A new time-stamped glacier inventory of High Mountain Asia based on deep learning and remote sensing big data in 2020 C. Ke et al.
- Time-Series models for ground subsidence and heave over permafrost in InSAR Processing: A comprehensive assessment and new improvement C. Fan et al.
- Detection and reconstruction of rock glacier kinematics over 24 years (2000–2024) from Landsat imagery D. Cusicanqui et al.
- Rock Glacier Inventories (RoGIs) in 12 areas worldwide using a multi-operator consensus-based procedure L. Rouyet et al.
- Underestimated small thermokarst lakes of the Qinghai-Tibet Plateau and their carbon emission potential X. Peng et al.
- RGIK guidelines for compiling consistent rock glacier inventories F. Brardinoni et al.
- Temporal scale dictates the dominant driver of lake dynamics on the Tibetan Plateau T. Li et al.
Saved (final revised paper)
Latest update: 06 May 2026
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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