Evaluation Of Landslide Susceptibility Based On GIS Tecnology In ShanYang County

The occurrence of landslide disasters has a great impact on human life,and a reasonable and effective assessment of the susceptibility assessment of landslide disasters in a region can provide a reference for disaster prevention and mitigation.Shanyang County is located in the mountainous area of southern Shaanxi Province,with complex terrain,fragile geological conditions,abundant rainfall,and intense human engineering activities,resulting in frequent lanslide disasters.Based on this,this paper studies the landslide susceptibility evaluation in Shanyang County,by collecting data,analyzing the background of the research area,and conducting experimental modeling,ArcGIS technology,R language,Matlab language and SPSS software are used to evaluate the susceptibility of Shanyang County.The main research contents and results are as follows:(1)Analyze the background data and geological maps of the study area,select 12 evaluation factors of elevation,slope,aspect,curvature,precipitation,vegetation index,river,road,fault,stratigraphic lithology,topography and land use type,and use ArcGIS software Make an evaluation factor layer.By calculating the classification area,classification ratio,number of disaster points,disaster ratio and disaster point density under different status classifications of each evaluation factor,correlation analysis and multi-collinearity check are carried out on the selected index factors,and the curvature factor and land use type are eliminated.factor,and establish a susceptibility evaluation index system for the remaining 10 types of evaluation factors.(2)The Frequency Ratio Model(FRM),logistic Regression Model(LRM),BP Neural Network Model(BPNNM)and Random Forest Model(RFM)were selected to evaluate the susceptibility of landslides in Shanyang County.The susceptibility index of each model obtained by modeling was imported into ArcGIS and divided into five susceptibility levels:non-susceptible area,low-susceptibility area,medium-susceptibility area,high-susceptibility area and extremely high-susceptibility area according to the natural discontinuity method.Zoning map of susceptibility grades under different models in Shanyang County.According to the results of each model partition,the areas of high-high-prone areas predicted by frequency ratio,logistic regression,BP neural network,and random forest model account for 22.61%,30.60%,29.38%,and 30.96%of the total area of Shanyang County,respectively;Landslide disaster points account for 57.36%,72.36%,74.38%,and 93.93%of the total disaster points.The density of disaster points in the extremely high-prone areas are:3.36/km2,3.71/km2,3.17/km2,6.28/km2.The results show that the zoning results are consistent with the actual location distribution of landslide disaster points,and the evaluation results are consistent with the actual situation.(3)The ROC curve accuracy of four models are verified,and results showed that the the training set accuracy and validation set prediction rate of the frequency ratio model were 78.9%and 82.6%,the training set accuracy rate and the verification set prediction rate of the logistic regression model were 81.3%and 85.3%,the training set accuracy and validation set prediction rate of the BP neural network model were 89.4%and 90.5%,and the training set accuracy rate and the verification set prediction rate of the random forest model were 98.2%and 97.6%.The four models can make better predictions,and the random forest model has better performance than the other three models,which is more suitable for landslide susceptibility evaluation in the study area.