A Landslide Susceptibility Evaluation of Highway Disasters Based on the Frequency Ratio Coupling Model

Huadan Fan, Yuefeng Lu, Yulong Hu, Jun Fang, Chengzhe Lv, Changqing Xu, Xinyi Feng and Yanru Liu
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Huadan Fan: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China
Yuefeng Lu: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China
Yulong Hu: China Transport Telecommunications & Information Center, Beijing 100011, China
Jun Fang: Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China
Chengzhe Lv: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China
Changqing Xu: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China
Xinyi Feng: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China
Yanru Liu: School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255049, China

Sustainability, 2022, vol. 14, issue 13, 1-17

Abstract: A landslide disaster, especially a highway landslide, may greatly impact the transport capacity of nearby roads. Keeping highways open, in particular, is crucial for supporting the functioning of the economy, society and people. Therefore, evaluating the highway landslide susceptibility is particularly important. In this paper, the city of Laibin, in the Guangxi Zhuang Autonomous Region of China, was taken as the study zone. According to data on 641 highway landslide disaster points measured in the field and a basic evaluation of the study area, nine evaluation factors—the elevation, slope, aspect, height difference, plan curve, profile curve, precipitation, Topographic Wetness Index (TWI) and vegetation coverage—were selected. We coupled a Frequency Ratio (FR) model, Analytic Hierarchy Process (AHP), Logistic Regression (LR), Back Propagation Neural Network (BPNN) and Support Vector Machine (SVM) to evaluate the susceptibility to highway landslides, with a Receiver Operating Characteristic (ROC) curve used to analyze the precision of these models. The ROC curve showed that the accuracy of the five models was greater than 0.700 and thus had a certain reliability. Among them, the FR-LR model had the highest accuracy, at 0.804. The study protocol presented here can therefore provide a reference for evaluation studies on landslide susceptibility in other areas.

Keywords: highway landslide disaster; frequency ratio; coupling model; ROC curve (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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