Abstract

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.

Highlights

  • Landslide processes and evolution are influenced by the interactions between triggering events and local natural conditions, including hillslope topography and geological background [1,2,3,4]

  • We observed three landslides that occurred on adjacent hillslopes in the same period and were characterized by different movement processes using Unmanned Aerial Vehicles (UAVs) surveys, time-series Interferometric Synthetic Aperture Radar (InSAR) and Differential InSAR (DInSAR) analyses, and electrical resistivity tomography

  • This combination of methods provided us with the opportunity to obtain a better understanding of the landslide processes in the surface and subsurface regions of these landslides

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Summary

Introduction

Landslide processes and evolution are influenced by the interactions between triggering events and local natural conditions, including hillslope topography and geological background [1,2,3,4]. These processes can reflect the differences in landslides’ deformation patterns and the spatial redistribution characteristics of their materials [5,6,7,8,9,10], which is helpful in understanding the mechanisms of slope instability. The deformation signal of landslide is a key parameter for early landslide warning systems It reflects the deformation degree of the hillslope and determines how the local

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