Abstract
The deep-seated landslide in the Lantai area, Taiwan, has a long history of landslide activity and often damages the sole access road to the Tai-Ping Mountain National Forest Recreation Area. This study adopted the high-resolution digital terrain model (DTMH) derived from UAV mounted LiDAR point cloud data for mapping geological structures and verified through field investigation. A slope model was proposed with mapped geological structures and shear zone, and numerical analysis was conducted using finite difference analysis. The failure mechanism was found to be significantly affected by the shear zone bounded by geological structures, which would not have been uncovered without the high-resolution DTM (DTMH). The resulting landslide behavior consisted well with mapped scarp, borehole data, and conformed with the event records. These results provided vital information supporting hazard mitigation strategy.
Highlights
Among different types of landslide hazards, the deep-seated landslide often involves large amount of landslide volume and causes severe hazard and damages to infrastructures [1,2]
When investigating the deepseated landslide hazard, many researchers found that the local geological settings including characteristics of rock formation and geological structures affect the failure mechanism of a deep-seated landslide significantly [6,7,8]
The location of the sliding surface intersected with the shear zone bounded by the mapped geological structures, and the crest of the sliding surface was close to the shear zone
Summary
Among different types of landslide hazards, the deep-seated landslide often involves large amount of landslide volume and causes severe hazard and damages to infrastructures [1,2]. To properly draft up the mitigation strategy for such deep-seated landslide hazard, it is essential to investigate the related geological setting and structures. This investigation of geological settings is often conducted by ground-based investigation, which is time consuming and expensive, and the results often rely on accessibility of the site and available out-crops of the geological formations and structures. The light detection and ranging (LiDAR) data, especially, provide terrain details in support of identification of geomorphological. Sci. 2021, 11, 10052 years, and remote sensing data have been used by many researchers to analyze topographic characteristics of the deep-seated landslides [9,10]. The resolution of the DTMH derived from the LiDAR point cloud data was 0.2 m
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