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Beiliu City, Guangxi Zhuang Autonomous Region, China, like other karst landscape areas, is also suffering from the threat of landslides. This research applied the circular variance method to delineate 31,465 slope units and then combined it with a geographic information system and a well-established risk assessment system to synthesize three perspectives-susceptibility, hazard, and vulnerability to realize the risk assessment of karst landslides in Beiliu City. Using perennial field surveys, aerial images-derived landslide inventories, slope unit investigations, and a literature review combined with a Fully Convolutional Neural Networks approach, we present a culminating in the derivation of landslide susceptibility assessment outcomes within the study area. Because Beiliu City is located in a karst area, this research employs the quantification of soil erosion intensity as a metric to assess landslide hazard. In this study, based on a comprehensive analysis of the basic characteristics of landslides and their associated disaster-bearing bodies, a robust landslide vulnerability assessment index system was constructed for risk assessment of karst landslides in Beiliu City. The landslide risk assessment model in karst area is constructed by combining the landslide susceptibility and the vulnerability in the danger range. Detailed field surveys verified the scientific validity and accuracy of the assessment results. This research extends beyond merely furnishing scientific data support for local governmental efforts in disaster prevention and mitigation. It impressively enhances the methodological framework for conducting landslide risk assessments within karst landscapes, thereby offering a robust foundation for both immediate and strategic responses to the inherent geological vulnerabilities of these areas. |
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