Landslide susceptibility assessment in Shimian County based on time-series InSAR deformation

ObjectiveLandslides are geological disasters that cause significant damage to both natural and social environment. Effective landslide susceptibility assessment is crucial for disaster prevention and mitigation. Existing landslide databases are often used as the primary data source for susceptibility assessments. However, due to delays in updates, these databases suffer from issues such as poor timeliness and incompleteness. Moreover, traditional landslide susceptibility assessment methods primarily rely on static data (e.g., topography, geology, and hydrology) and lack dynamic data (e.g., surface deformation), making it difficult to fully characterize the deforming landslides and reducing assessment reliability. MethodsThis study combined optical remote sensing technology and interferometric synthetic aperture radar (InSAR) to identify landslides in the study area and obtain surface deformation as a dynamic evaluation factor. In combination with static evaluation factors, two methods (joint training and weighted superposition) were employed, alongside the maximum entropy (MaxEnt) model and the iterative self-organizing (ISO) clustering algorithm to assess and categorize landslide susceptibility in Shimian County. ResultsThe findings are as follows: (1) By integrating optical remote sensing and InSAR technologies, 139 landslides are identified in the study area. High-risk landslide zones in Shimian County are predominantly located along riverbanks and roadsides. The distribution of landslide disaster points aligns well with the zoned areas. (2) Incorporating the InSAR deformation factor enhances the susceptibility accuracy by 6.1% (AUC=0.921) and substantially reduces the occurrence of false positives and false negatives, thereby improving overall model accuracy. ConclusionThis study demonstrates the advantages of incorporating InSAR deformation data into landslide susceptibility models, offering valuable support for landslide disaster prevention in Shimian County.