A Conditional Probability-Based Model for Mountainous Geological Hazard Susceptibility Assessment

作者：Yixi Wang, Jing Chen, Shouding Li, Pengfei Zhang, Xinshuo Chen, Shiwei Ma, Hui Ouyang, Hang Bian, Tianqiao Mao, Zhaobin Zhang, Xiaozhen Li · 发表于：Applied Sciences · 年份：2025 · DOI：10.3390/app152312653 · 被引用次数：2 · 研究领域：Landslides and related hazards、earthquake and tectonic studies、Seismic Performance and Analysis

The occurrence of mountainous geological hazards, primarily including rockfalls, landslides, and debris flows, is frequently influenced by multiple environmental factors and exhibits significant spatial heterogeneity and cumulative effects. To address the need for regional-scale susceptibility assessments within complex geological settings, we propose a novel geological hazard susceptibility assessment model based on conditional probability. This study establishes a dual-module evaluation framework incorporating certainty factors (CFs) and weights (W), in which the CF quantifies the contribution of each factor class to hazard occurrence, while the weights reflect the relative importance of the conditioning factors, thereby improving the model’s capability to characterize multifactorial coupling effects. Using three representative mountainous regions in Xinjiang, China—the Ili Valley Region (IVR), the Northern Piedmont of the Tianshan Mountains (NPTM), and the Kunlun–Altun Mountain Region (KAMR)—we integrate 7938 historical hazard points and 11 conditioning factors within a GIS environment to conduct the assessment. The results reveal regional differences in the weights of conditioning factors: IVR is primarily controlled by Elevation (0.184), Urban-Critical Infrastructure Density (0.163), and Annual Precipitation (0.156); NPTM is dominated by Annual Precipitation (0.153), Urban-Critical Infrastructure Density (0.145), and Road Density (0.136); and KAMR is governed by Elevatio...