Evaluation of Geological Hazards Susceptibility along the Hefei-Fuzhou High- Speed Railway Based on Machine Learning Algorithms

Geological hazards pose significant risks during the construction and operation of railways, demanding effective prevention and control measures to ensure operational safety. The Hefei-Fuzhou High-Speed Railway, a critical transportation artery, traverses complex geological terrain and diverse landforms, leading to prominent geological hazards risk along its route. This study focuses on the Huangshan-Fuzhou section of this railway, evaluating landslide susceptibility within the railway corridor using the Random Forest (RF) algorithm. Furthermore, we analyze spatial variations in the primary influencing factors by comparing two distinct sub-regions. The main findings are as follows: (1) A landslide susceptibility model developed using a historical landslide inventory and the RF algorithm demonstrated strong predictive performance, achieving an Area Under the Curve (AUC) value of 0.86. (2) Application of this model produced a landslide susceptibility zonation map, which revealed that approximately 30% of the study area is classified as high (16.92%) and very high (13.22%) susceptibility zones. (3) Analysis of feature importance identified Slope (0.28), Relief (0.18), and Topographic Wetness Index (TWI, 0.11) as the most influential factors governing landslide susceptibility across the entire study area. (4) Comparative analysis of factor importance between the northern and southern sub-regions revealed distinct patterns: the primary factors in the north were Slope (0.115), TWI (0.051), and Relief (0.050), whereas in the south, they were Slope (0.149), Rainfall (0.043), and Curvature (0.041). These results highlight the dominant influence of topography on landslide susceptibility at a regional scale, while underscoring the enhanced role of precipitation as a key contributing factor to landslide in the southern region. This research provides a scientific basis for targeted geological hazards prevention along the Hefei-Fuzhou High-Speed Railway and offers a valuable methodological approach for regional infrastructure planning and geological risk management in similar environments.