Remote Sensing (Nov 2021)

Landslide Characteristics and Evolution: What We Can Learn from Three Adjacent Landslides

  • Dongdong Yang,
  • Haijun Qiu,
  • Yaru Zhu,
  • Zijing Liu,
  • Yanqian Pei,
  • Shuyue Ma,
  • Chi Du,
  • Hesheng Sun,
  • Ya Liu,
  • Mingming Cao

DOI
https://doi.org/10.3390/rs13224579
Journal volume & issue
Vol. 13, no. 22
p. 4579

Abstract

Read online

Landslide processes are a consequence of the interactions between their triggers and the surrounding environment. Understanding the differences in landslide movement processes and characteristics can provide new insights for landslide prevention and mitigation. Three adjacent landslides characterized by different movement processes were triggered from August to September in 2018 in Hualong County, China. A combination of surface and subsurface characteristics illustrated that Xiongwa (XW) landslides 1 and 2 have deformed several times and exhibit significant heterogeneity, whereas the Xiashitang (XST) landslide is a typical retrogressive landslide, and its material has moved downslope along a shear surface. Time-series Interferometric Synthetic Aperture Radar (InSAR) and Differential InSAR (DInSAR) techniques were used to detect the displacement processes of these three landslides. The pre-failure displacement signals of a slow-moving landslide (the XST landslide) can be clearly revealed by using time-series InSAR. However, these sudden landslides, which are a typical catastrophic natural hazard across the globe, are easily ignored by time-series InSAR. We confirmed that effective antecedent precipitation played an important role in the three landslides’ occurrence. The deformation of an existing landslide itself can also trigger new adjacent landslides in this study. These findings indicate that landslide early warnings are still a challenge since landslide processes and mechanisms are complicated. We need to learn to live with natural disasters, and more relevant detection and field investigations should be conducted for landslide risk mitigation.

Keywords