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<p>Anthropogenic activities constitute a significant factor in inducing landslide instability, especially for large landslides in the vicinity of major infrastructures. However, systematic monitoring and risk assessment of the entire slope of such large landslides under engineering disturbances is challenging. In this study, we propose an approach to investigate landslide dynamics from surface to subsurface based on three-dimensional (3D) deformation monitoring and successfully applied it to the Li-Kan Road landslide (LKRL), which was induced by road engineering and located on the right bank of the Lijia Gorge Reservoir in China. We used Sentinel-1 datasets to study the spatiotemporal evolution characteristics of LKRL motion and to determine the sliding depth after inverting 3D deformation fields. Results reveal the significant cumulative displacement (over 2 m) and spatial heterogeneity of LKRL motion over the past 8.5 years. The sliding depth was found to be unevenly distributed, averaging 10.6 m, with a landslide volume of 1.45 × 10<sup>7</sup> m<sup>3</sup>. As the landslide is currently in a phase of continuous motion with occasional localized collapses, the failure risk of this large LKRL deserves further close attention in the future. This study represents the systematic survey of LKRL activity using satellite data and provides insights for the mechanistic interpretation and risk management of landslides triggered by human activities.</p>

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Kinematic behavior and sliding geometry of large anthropogenic-induced landslides using three-dimensional time series InSAR: insights from the Li-Kan Road landslide

  • 期刊论文

  • 发表日期：

    2025年5月22日

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  • Jiantao Du,
  • Chuang Song,
  • Zhenhong Li,
  • Roberto Tomás,
  • Zheng Li

摘要

Anthropogenic activities constitute a significant factor in inducing landslide instability, especially for large landslides in the vicinity of major infrastructures. However, systematic monitoring and risk assessment of the entire slope of such large landslides under engineering disturbances is challenging. In this study, we propose an approach to investigate landslide dynamics from surface to subsurface based on three-dimensional (3D) deformation monitoring and successfully applied it to the Li-Kan Road landslide (LKRL), which was induced by road engineering and located on the right bank of the Lijia Gorge Reservoir in China. We used Sentinel-1 datasets to study the spatiotemporal evolution characteristics of LKRL motion and to determine the sliding depth after inverting 3D deformation fields. Results reveal the significant cumulative displacement (over 2 m) and spatial heterogeneity of LKRL motion over the past 8.5 years. The sliding depth was found to be unevenly distributed, averaging 10.6 m, with a landslide volume of 1.45 × 107 m3. As the landslide is currently in a phase of continuous motion with occasional localized collapses, the failure risk of this large LKRL deserves further close attention in the future. This study represents the systematic survey of LKRL activity using satellite data and provides insights for the mechanistic interpretation and risk management of landslides triggered by human activities.