Zhangyu (Joe) Sun is a Ph.D. student of Earth and Environmental Sciences at The Chinese University of Hong Kong. Joe obtained his Bachelor and Master degrees from Wuhan University in 2018 and 2021, respectively. He also has a double-degree Master degree from the Technical University of Munich. He obtained the Hong Kong PhD Fellowship and earned his Ph.D. in 2025. During his Ph.D. study, he used optical remote sensing, InSAR, and deep learning to comprehensively study rock glacier distribution, velocities, and water storage in High Mountain Asia.
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 for the 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 6000 km2, with a mean area of 0.14 km2. They are predominantly situated at elevations ranging from 4000 to 5500 m a.s.l., with a mean of 4729 m a.s.l. They tend to occur on slopes with gradients between 10 and 25\,^∘, with a mean of 17.7\,^∘. Across the plateau, rock glaciers are 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 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.
