research data_heavy haul railway

The research data is derived from landslide investigations along the Shuohuang Railway, including historical records of 1,185 landslide points provided by the Natural Resources and Planning Bureau, as well as environmental and geological parameters extracted through remote sensing and GIS analysis. The initial dataset comprises 14 influencing factors, such as elevation, slope, road and river densities, lithology, fault density, NDVI, rainfall, SPI, and TWI. Pearson correlation analysis was applied to select 10 key factors, improving model performance and reducing data dimensionality. The dataset was divided into training, validation, and testing sets (70%, 10%, 20%), and the 3-Sigma rule was used to remove outliers, ensuring the reliability of model inputs. The landslide susceptibility zoning maps generated by the model outputs were spatially analyzed using GIS, providing a scientific basis for disaster risk management in complex geological regions.