## 4 Discussion
### Interaction of Different Factors and Their Impact on Road Collapse Disasters  
In this study, the susceptibility risk assessment of road collapse disasters takes into account multiple natural and anthropogenic factors. These factors not only individually influence the risk assessment outcomes but also interact with one another, generating complex synergistic effects. To comprehensively understand their mechanisms of influence on road collapse disasters, this section examines the roles of individual factors and their interrelationships, delving into their contributions to risk assessment and the rationality behind their inclusion. (1) Slope: Slope is a critical geological factor influencing the risk of road collapse disasters. Generally, steeper slopes are associated with poorer soil stability, thereby increasing the likelihood of landslides and collapses [24]. As shown in Figure 7, areas with steeper slopes are typically located in high-risk zones, which aligns with the study's findings and underscores the significant role of slope in collapse risk assessment. However, the influence of slope is not isolated; it interacts with other factors such as precipitation and soil moisture [40]. In areas with steeper slopes, increased precipitation, and soil moisture further destabilize the soil, elevating the risk of collapse. This figure illustrates the slope classification for the Guangxi Zhuang Autonomous Region, based on the ASTER GDEM digital elevation model (DEM) with a resolution of 30 m sourced from the Geospatial Data Cloud platform. Slope values were extracted from elevation data using geographic information system (GIS) techniques and were classified using the Natural Breaks method [7; 29]. The classification intervals are defined as: 0-5\({}^{\circ}\), 5-10\({}^{\circ}\), 10-15\({}^{\circ}\), 15-25\({}^{\circ}\), 25-35\({}^{\circ}\), 35-50\({}^{\circ}\), and 50-86\({}^{\circ}\). The natural breaks method optimizes within-group variance minimization and between-group variance maximization based on the distribution characteristics of slope data. Regions with steeper slopes (e.g., 50-86\({}^{\circ}\)) are categorized as high-risk zones due to reduced soil stability and increased vulnerability to collapse disasters, while gentler areas with slopes less than 10\({}^{\circ}\) are categorized as low-risk zones. This slope classification is a key input to the susceptibility risk assessment model  
Figure 7: Slope map of the Guangxi Zhuang Autonomous Region. based on a convolutional neural network (CNN), providing essential support for disaster prevention and regional planning. (2) Lithology: Lithology directly affects soil stability. Areas dominated by soft rocks or highly fractured rock formations are more prone to landslides and collapses [25]. As illustrated in Figure 8, regions with softer lithology or well-developed fractures are generally associated with higher collapse risk, and the model results validate the rationality of including lithology as a factor. The synergistic interaction between lithology and other environmental factors, such as precipitation and vegetation coverage, also plays a significant regulatory role [41]. In regions with high precipitation, soft rock areas are susceptible to water infiltration, which further reduces the soil's resistance to sliding and increases the risk of collapse. This figure illustrates the lithological distribution in the Guangxi Zhuang Autonomous Region, generated based on geological surveys and geospatial data, highlighting the rock types influencing soil stability and collapse risk.