EGU23-2080, updated on 09 Jan 2024
https://doi.org/10.5194/egusphere-egu23-2080
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

A multi‐source remote sensing technical framework for wide-area landslide detection

Zhenhong Li, Chenglong Zhang, Bo Chen, Jiantao Du, Mingtao Ding, Wu Zhu, Chuang Song, Chen Yu, Jiewei Zhan, and Jianbing Peng
Zhenhong Li et al.
  • College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China (zhenhong.li@chd.edu.cn)

Landslides pose a destructive geohazard to people and infrastructure that results in hundreds of deaths and billions of dollars in damages every year. China is one of the countries worst affected by landslides in the world, and great efforts have been made to detect potential landslides over wide regions. However, a recent government work report shows that 80% of the newly formed landslides occurred outside the areas labelled as potential landslides, and 80% of them occurred in remote rural areas with limited capability of disaster prevention and mitigation. In this presentation, a multi‐source remote sensing technical framework is demonstrated to detect potential landslides over wide regions.

How to cite: Li, Z., Zhang, C., Chen, B., Du, J., Ding, M., Zhu, W., Song, C., Yu, C., Zhan, J., and Peng, J.: A multi‐source remote sensing technical framework for wide-area landslide detection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2080, https://doi.org/10.5194/egusphere-egu23-2080, 2023.