Abstract
Landslides are one of the nature hazards causing a lot of casualties and property losses in the world. Over the last decades, many researchers have made contributions in landslide susceptibility maps using qualitative and quantitative methods. Parameters of DEM, geology, etc. are selected to analyze the mechanism of landslides. The quality of data is essential in the landslide studies, and more credible results can be obtained if the data is adequate and accurate from the wide range of parameters. The aim of this study is to evaluate the landslide susceptibility of Huangyuan County of Qinghai. Through field investigations, 100 landslide disaster locations in the study area were selected, and 11 influencing factors including elevation, slope, aspect, plane curvature, profile curvature, road distance, river distance, fault distance, stratum rock property, vegetation coverage index, and terrain humidity index were selected as the influencing factors of landslide disaster based on GIS. In this paper, the information method (IM) model, frequency ratio (FR) model, and artificial neural network (ANN) model are used to evaluate the susceptibility of geological hazards, and the receiver operating characteristic (ROC) curve of disaster points at different levels is used to test the evaluation accuracy of three models. The results show that factors that have great influence on landslides are associated with witness, and the terrain humidity index has the highest weight in the occurrences of landslide. The values of AUC indicate that the ANN model is the best evaluation model suitable for the study area and can be extremely useful for landslide hazard mitigation strategies. Based on the calculation of ANN model, three valley areas are determined with high landslide susceptibility, and necessary reinforcement measures should be taken.
Highlights
Landslide is a kind of natural hazard in the mountainous regions, threatening human life and property [1–4]
Any influencing factor with a Variance Inflation Factor (VIF) value of greater than 10 should be excluded from the landslide susceptibility model. e VIFs in Table 1 show that the values of the influence factors are all below 10, so no factor needed to be excluded from the landslide susceptibility model
Where Ni is the total number of geological hazards in the class i evaluation factor of the study area; N is the total number of units with geological hazards in the study area; Si is the number of units with class i evaluation factors in the study area; S is the total number of evaluation factor units in the study area; Ii is the total information value of the study area; n is the number of evaluation factors
Summary
Landslide is a kind of natural hazard in the mountainous regions, threatening human life and property [1–4]. E occurrences of landslides are extremely complicated and affected by many factors such as geologic structure, lithological association, topography, rainfall, earthquake, and human activity [8–12]. Based on these factors, various assessing methods have been proposed to analyze the landslide susceptibility, which can be divided into two categories: qualitative analysis and quantitative analysis [13–18]. In the process of qualitative analysis, the spatial distribution of unstable slopes is based on experts’ understanding of the relationship between the occurrence of Advances in Civil Engineering landslides and the assumed antecedent factors, directly determined by the existing landslides or potentially unstable areas. Is analysis method is to estimate the potentially unstable area by using the inducing factors related to landslide occurrence Quantitative analysis, an objective evaluation, is a kind of numerical estimation, such as calculating the probability of landslides. is analysis method is to estimate the potentially unstable area by using the inducing factors related to landslide occurrence
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