Abstract
Geological disaster risk assessment can quantitatively assess the risk of disasters to hazard-bearing bodies. Visualizing the risk of geological disasters can provide scientific references for regional engineering construction, urban planning, and disaster prevention and mitigation. There are some problems in the current binary classification landslide risk assessment model, such as a single sample type, slow multiclass classification speed, large differences in the number of positive and negative samples, and large errors in classification results. This paper introduces multilevel landslide hazard scale samples, selects multiple types of samples according to the divided multilevel landslide hazard scale grade, and proposes a landslide hazard assessment model based on a multiclass support vector machine (SVM). Due to the objective limitations of the single weighting method, the combined weights are used to determine the vulnerability of the landslide hazard-bearing body, and the analytic hierarchy process (AHP) and entropy method are combined to construct a landslide vulnerability assessment model that considers subjective and objective weights. This paper takes landslide disasters in Xianyang City, Shaanxi Province, as the research object. Based on the landslide hazard assessment model and the landslide vulnerability assessment model, a landslide risk assessment experiment is carried out. It generates the landslide risk assessment zoning map and summarizes the risk characteristics of landslides in various towns. The experimental results verify the feasibility and effectiveness of the proposed model and provide important decision support for decision makers in Xianyang City.
Highlights
In recent years, disasters have occurred frequently worldwide, destroying human property and socioeconomic activities [1,2,3]
We show the classification standard of the geological disaster scale and classification standard of geological disasters, and introduces the multiclass support vector machine (SVM) landslide hazard assessment model and landslide vulnerability assessment model, which consider the subjective and objective weights to carry out landslide risk assessment
The results showed that the vulnerability of the northern part of Xianyang City was generally low, while the vulnerability of the southern part was relatively high, especially the area around the Xianyang urban area
Summary
Disasters have occurred frequently worldwide, destroying human property and socioeconomic activities [1,2,3]. (1) Nine evaluation factors are selected from the four aspects of terrain features, meteorological features, human influence, and historical geological disasters to construct the landslide hazard evaluation index system: elevation, slope, aspect, normalized difference vegetation index (NDVI), distance from rivers, accumulated rainfall, distance from roads, lithology, and landforms. (3) Taking the landslide in Xianyang city of Shaanxi Province as the research object and taking the towns as the evaluation unit, the landslide risk assessment is carried out based on the landslide hazard assessment model and the landslide vulnerability assessment model. Geo-Inf. 2021, 10, x FOR PtEoEtRalRoEVf InEiWne evaluation factors in four categories were selected as natural attribute d5aotfa for landslide hazard assessment They were terrain characteristic factors (elevation slope, aspect, NDVI, distance from rivers), meteorological characteristic factors (accumulated rainfall), human influence factors (distance from roads), and historical geological disasters t(hloitlhooglyo,glya,nladnfodrfmorsm).sT).hTehdeetdaeiltsaialsrearsehoshwonwinn iFnigFuigreusre2sa2nadn3d. 33. .LLaannddsslildideeRRiisskkAAsssseessssmmeenntt MMeetthhoodd TThhisissseeccttioionnsshhoowwsstthheeccllaasssification standarrddoofftthheeggeeoollooggiiccaallddisisaassteterrscscaaleleaannddclcalsa-ssisfiifcicaatitoionnsstatannddaarrddooff ggeeoollooggiiccal disasters, and iinnttrroodduucceesstthheemmuultlitciclalasssSSVVMMlalannddslsildide e
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