Preliminary Risk Assessment of Geological Disasters in Qinglong Gorge Scenic Area of Taihang Mountain with GIS Based on Analytic Hierarchy Process and Logistic Regression Model

Ruixia Ma, Yan Lyu (), Tianbao Chen and Qian Zhang
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Ruixia Ma: School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710000, China
Yan Lyu: School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710000, China
Tianbao Chen: Chongqing Shutong Geotechnical Engineering Co., Ltd., Chongqing 401147, China
Qian Zhang: School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710000, China

Sustainability, 2023, vol. 15, issue 22, 1-19

Abstract: Qinglong Gorge Scenic Area (QGSA) boasts stunning natural landscapes, characterized by towering peaks and extensive cliffs. Nevertheless, the intricate geological backdrop and distinctive topographical conditions of this area give rise to various geological disasters, posing a substantial safety concern for tourists and presenting ongoing operational and safety management challenges for the scenic area. In light of these challenges, this study placed its focus on the geological disasters within QGSA and sought to assess risks across various scales. The assessment was accomplished through a combination of methods, including field surveys conducted in 2022, remote sensing interpretation, and comprehensive data collection and organization. For the geological disaster risk assessment of the scenic area, this research selected seven key indicators, encompassing terrain factors, geological elements, structural characteristics, and other relevant factors. The assessment utilized a logistic regression model, which yielded satisfactory results with an AUC value of 0.8338. Furthermore, a model was constructed incorporating seven indicators, encompassing factors such as population vulnerability, material susceptibility, and the vulnerability of tourism resources. To assess vulnerability to geological disasters, the Analytic Hierarchy Process (AHP) was employed, resulting in a CR of 0, thus ensuring the reliability of the findings. The outcomes of the risk assessment indicate that the low-risk area covers a substantial expanse of 5.45 km 2 , representing 53.66% of the total area. The moderate-risk area extends over 3.59 km 2 , constituting 35.43%, while the high-risk area encompasses 0.72 km 2 , accounting for 7.14%. Additionally, the very high-risk area encompasses 0.38 km 2 , making up 3.77% of the total area. Consequently, building upon the findings of the risk assessment, this paper introduces a risk classification and control prevention system. This system provides invaluable insights for disaster prevention and control in mountainous and canyon-type scenic areas.

Keywords: geological disaster; risk assessment; logistic model; analytic hierarchy process; Qinglong Gorge Scenic Area; Taihang Mountain; China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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