Production and Analysis of a Landslide Susceptibility Map Covering Entire China
China, with its complex geology and diverse climate, is highly prone to landslides, endangering public safety and infrastructure. To address disaster prevention needs, this study comprehensively assesses national landslide susceptibility. We divided China into 37 geomorphic districts, diverging from traditional methods. By using a 2018–2022 surface deformation dataset, we introduced a rarely—considered dynamic aspect for more accurate mapping of landslide—prone areas. Nine key environmental factors were carefully considered, including terrain, geology, meteorology, hydrology, seismic activities, and engineering activities. Based on these innovative methods and data, we created a 40 m—resolution landslide susceptibility map (LSM) for the whole country. Our assessment showed high accuracy, with an AUC of 0.927, precision of 0.859, recall of 0.815, F1—score of 0.828 and Matthews correlation coefficient of 0.773. Seven high—risk regions, like the Tianshan Mountains and the southern Tibetan valleys, were analyzed. The study revealed regional differences in landslide occurrences and key influencing factors. The LSM and findings enrich landslide susceptibility theory and offer a valuable resource for engineering, disaster management, and mitigation in China, helping reduce potential landslide losses.
Authors
- Shunyao Wang
- Guo Zhang (ORCID: https://orcid.org/0000-0002-3987-5336)
- Weiqi Lian (ORCID: https://orcid.org/0000-0001-6253-6511)
- Hang Xu (ORCID: https://orcid.org/0000-0003-2862-4838)
- Zixing Xu (ORCID: https://orcid.org/0000-0002-1109-1345)
- Zan Ding (ORCID: https://orcid.org/0000-0003-0311-3353)
- Yuan Yuan (ORCID: https://orcid.org/0000-0002-4041-8765)
- Yutao Liu (ORCID: https://orcid.org/0000-0002-7890-1357)
- Run Wang (ORCID: https://orcid.org/0000-0001-5570-6391)
- Zhenwei Chen (ORCID: https://orcid.org/0000-0002-1865-602X)
Institutions
- PLA Information Engineering University (CN)
- Wuhan University (CN)
- China Metallurgical Geology Bureau (CN)
- Nanyang Normal University (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
- Hong Kong Metropolitan University (HK)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-05-01
- DOI
- https://doi.org/10.3390/rs17091615
- Citations
- 5
- Primary Topic
- Landslides and related hazards
- Type
- article
- Field-Weighted Citation Impact
- 12.11
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China