Event-based mapping and spatial pattern analysis of landslides in parts of central Vietnam

Abstract Systematic landslide inventories following major triggering events are crucial for understanding spatial and temporal patterns and for enabling the development of advanced predictive models. This study examines landslide distributions triggered by Typhoons Ketsana, Molave, and Tropical Storm Podul in the highlands of central Vietnam using high-resolution satellite imagery. A total of 8744, 915, and 11,575 landslides were mapped for these events, respectively. Ripley’s K and cross K-functions were applied to assess clustering, dispersion, or randomness at various distances between inventories. Results reveal pronounced clustering for landslides from Typhoons Ketsana and Molave, while landslides triggered by Podul exhibited clustering up to 22.5 km, transitioning to strong repulsion at larger distances. Cross-event analysis revealed clustering between Ketsana and Molave landslides within an 8.1 km radius, whereas Ketsana and Podul landslides exhibited consistent repulsion across all distances, indicating spatial independence. Spatial independence tests, including the Spatial Kolmogorov–Smirnov test for seven covariates—elevation, topographic slope, topographic aspect, Topographic Position Index, drainage density, annual average rainfall, distance from mapped geologic faults, and the Chi-square test for lithology, revealed statistically significant non-random associations, indicating spatial dependencies between landslide occurrences and covariates. These findings provide critical insights into landslide dynamics under varying storm conditions, thereby contributing to enhanced hazard modeling and risk management.