EGU23-4886, updated on 09 Jan 2024
https://doi.org/10.5194/egusphere-egu23-4886
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Detection and characterization of earthquake accelerated landslides (EALs) using InSAR observations

Chuang Song1,2, Chen Yu1, Zhenhong Li1,3, Stefano Utili2, Paolo Frattini4, Giovanni Crosta4, and Jianbing Peng1,3
Chuang Song et al.
  • 1College of Geological Engineering and Geomatics, Chang'an University, Xi’an, China (chuang.song@chd.edu.cn)
  • 2School of Engineering, Newcastle University, Newcastle upon Tyne, UK
  • 3Key Laboratory of Western China's Mineral Resources and Geological Engineering, Ministry of Education, Xi’an, China
  • 4Department of Earth and Environmental Sciences, Università degli Studi di Milano Bicocca, Milan, Italy

Earthquake-induced landslides often pose a great threat to the safety of human life and property, especially in seismic active regions. This has motivated plentiful studies with a focus on coseismic landslides that collapsed during or shortly after an earthquake. However, long-term seismic effects that activated unstable landslides but without causing failures/collapse even after a long period since the earthquake (months to years) are typically ignored due to the minor ground changes caused compared to collapsed slopes. These landslides respond to seismic stress disturbances differently from failed coseismic/post-seismic landslides and their movements are typically accelerated with increased sliding velocity after earthquakes. The acceleration phenomenon of these earthquake accelerated landslides (EALs) could be maintained for a long time and they may generate continuous damage to the ground and develop into catastrophic failures in the future.

 

As a new type of landslides associated with earthquakes, EALs have been largely neglected by the emerging research. In our study, we used satellite radar (Sentinel-1) observations from October 2014 to August 2020 to detect and investigate EALs in Central Italy. Distinguished from previous studies based on single or discrete landslides, we established a large EAL inventory and statistically quantified as a whole their spatial clustering features against a set of landslide conditioning factors. Results show that EALs did not rely on strong seismic shaking or hanging wall effects to occur and larger landslides were more likely to accelerate after earthquakes than smaller ones. We also discovered their accelerating-to-recovering sliding dynamics, and how they differed from the collapsed coseismic landslides. These investigations serve as an important supplement to the complete picture of the landslide inducing mechanism by earthquakes and contribute to a more comprehensive long-term assessment of landslide risk.

How to cite: Song, C., Yu, C., Li, Z., Utili, S., Frattini, P., Crosta, G., and Peng, J.: Detection and characterization of earthquake accelerated landslides (EALs) using InSAR observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4886, https://doi.org/10.5194/egusphere-egu23-4886, 2023.