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<p>landslide hazards are widely distributed around the world, posing significant challenges to economic and social development and severely affecting the lives of local populations. Among the various triggering factors, rainfall is one of the most prominent causes of landslides. However, the spatiotemporal evolution characteristics of rainfall-induced landslides are difficult to capture. To enhance the understanding of landslide deformation and damage, this paper proposes a method for quantitatively assessing the deformation trends of landslides. This method is based on spaceborne InSAR observations, integrating the PCA method with the Hurst exponent method. First, satellite-based InSAR technology was used to extract the temporal displacements before and after the landslide occurrence. Building on this, Principal Component Analysis (PCA) was applied to estimate the main deformation directions during different stages of the landslide. Furthermore, the Hurst exponent was calculated to quantify the deformation trends of the landslide. The results indicate that the primary deformation direction of the Goujiabao landslide changed before and after the landslide failure. The surface deformation direction of the landslide exhibited a specific temporal pattern, with notable changes occurring shortly before the landslide hazard. Additionally, regions with higher Hurst exponent values corresponded well with areas of severe landslide damage, suggesting that these areas with higher Hurst values are more susceptible to failure. Moreover, a positive correlation was found between precipitation and landslide deformation direction, indicating that concentrated rainfall could be a key triggering factor for landslide hazards. The findings of this study provide valuable insights into surface displacements of landslides and offer an objective method to quantify the deformation trends of surface regions during the pre-slip stage. This approach serves as a valuable tool for studying the physical characteristics of landslides and assessing regional disaster risks.</p>

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Surface deformation trend of the rainfall induced landslide during the pre-slip stage

  • 期刊论文

  • 发表日期：

    2025年12月22日

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  • Haiqing Yang,
  • Jiayan Lu,
  • Anhua Ju

摘要

landslide hazards are widely distributed around the world, posing significant challenges to economic and social development and severely affecting the lives of local populations. Among the various triggering factors, rainfall is one of the most prominent causes of landslides. However, the spatiotemporal evolution characteristics of rainfall-induced landslides are difficult to capture. To enhance the understanding of landslide deformation and damage, this paper proposes a method for quantitatively assessing the deformation trends of landslides. This method is based on spaceborne InSAR observations, integrating the PCA method with the Hurst exponent method. First, satellite-based InSAR technology was used to extract the temporal displacements before and after the landslide occurrence. Building on this, Principal Component Analysis (PCA) was applied to estimate the main deformation directions during different stages of the landslide. Furthermore, the Hurst exponent was calculated to quantify the deformation trends of the landslide. The results indicate that the primary deformation direction of the Goujiabao landslide changed before and after the landslide failure. The surface deformation direction of the landslide exhibited a specific temporal pattern, with notable changes occurring shortly before the landslide hazard. Additionally, regions with higher Hurst exponent values corresponded well with areas of severe landslide damage, suggesting that these areas with higher Hurst values are more susceptible to failure. Moreover, a positive correlation was found between precipitation and landslide deformation direction, indicating that concentrated rainfall could be a key triggering factor for landslide hazards. The findings of this study provide valuable insights into surface displacements of landslides and offer an objective method to quantify the deformation trends of surface regions during the pre-slip stage. This approach serves as a valuable tool for studying the physical characteristics of landslides and assessing regional disaster risks.