Supporting data for landslide susceptibility modeling in karst terrains

This dataset contains supporting data for the study on landslide susceptibility assessment in Nayong County, Guizhou, China, a typical karst region characterized by complex interbedded lithologies. The dataset includes three main components:<b>Landslide cumulative frequency data</b> – describing the statistical distribution of landslide occurrences in the study area.<b>Factor correlation matrix</b> – quantifying the relationships among geomorphological, geological, hydrological, and anthropogenic factors considered in the susceptibility modeling.<b>Model variable importance measures</b> – derived from multiple machine learning algorithms (LM, LR, SVM, RF, XGBoost), highlighting the relative contributions of conditioning factors to landslide susceptibility.These data provide the basis for reproducibility and transparency of the modeling framework presented in the manuscript. They may also be useful for further research on landslide susceptibility, hazard mapping, and machine learning applications in geomorphological studies.