The impact of slope unit scale and landslide sampling methods on regional landslide susceptibility assessment

Recent advancements in the automatic extraction of slope units have been significant. However，research on the effective organization of landslide hazard data based on slope units remains limited，particularly regarding the impact of slope unit scales and landslide sampling methods on regional landslide susceptibility assessments. This study focuses on the Yuqu River Basin in southeastern Tibet，where six slope unit scales，ranging from fine to coarse，were defined by adjusting slope unit size parameters. Additionally，three landslide sampling methods-centroid-based，intersecting centroid-based，and area ratio threshold-based—were developed using landslide vector points and polygons. These approaches enabled the construction of 33 distinct datasets for evaluating landslide susceptibility. The results indicate that fine-scale slope units struggle to achieve high predictive accuracy，while overly coarse units reduce the rationality of susceptibility zoning，particularly through the overestimation of high-susceptibility areas. A moderate slope unit size can enhance the model's predictive accuracy，leading to more reasonable partitioning results. This finding also validates the effectiveness of the principle of maximizing internal homogeneity and external heterogeneity of topography in landslide susceptibility assessments，providing robust support for the appropriate selection of slope unit sizes. Moreover，under complex environmental conditions，assigning the slope unit containing the landslide centroid as the sample proves to be a robust and rational method，enhancing both the predictive accuracy and zoning performance of the model. The variations in susceptibility assessment outcomes across different data organization strategies are primarily due to the effectiveness of the correlation between landslides and environmental factors，especially the distinctiveness between landslide and non-landslide scenarios. This study provides a valuable reference for landslide susceptibility modeling based on slope units in the alpine canyon regions of southeastern Tibet and significantly contributes to improving the quality of landslide risk assessments in complex environments.