水土保持通报2024，Vol.44Issue(1)：193-205,13.DOI:10.13961/j.cnki.stbctb.2024.01.020
基于统计方法耦合地理探测器的地质灾害易发性评价
Geological Hazard Susceptibility Evaluation Based on a Statistical Method Coupled with Geographic Detector
摘要
Abstract
[Objective]A high-precision geological hazard susceptibility evaluation model was determined for the three districts(counties)of Lishi,Shilou,and Liulin in Liiliang City,Shanxi Province in Luliang mountaionous area in order to provide auxiliary decision-making support for regional planning in the area.[Methods]Based on a geographic information system,a sample of 525 historical hazard points and 500 randomly selected non-hazard points in the region were used,and 19 influencing factors of geological hazard were selected.Geographic detectors(GD)were used to judge the relative importance of each factor.Correlation tests and filtering index factors were determined on the Jupyter Notebook platform.Based on the information method(IM),a method was proposed to calculate the amount of information provided by disaster points combined with the amount of information provided by non-disaster points to obtain the improved information method(IIM),and to calculate the weight with the help of the spatial heterogeneity q value of geographic detectors.Six evaluation systems(GD-IIM,GD-IM,GD-CF,IM,CF,and IIM)were established using the certainty factor(CF).The natural breakpoint classification method was used to divide the susceptibility into five,four,and three levels,and the accuracy of the partition results was verified by the seed cell area index(SCAI).The accuracy of the model results was compared with the ROC curve.[Results]After SCAI testing,the models were divided into four levels(very low,low,high,and very high)that met the rationality requirements.The success rate and prediction rate of disaster susceptibility evaluation by the GD-IIM model reached 90.5％and 85.5％,respectively.The IIM model exhibited 2％～4％greater accuracy than the traditional IM and CF statistical methods.[Conclusion]The bivariate statistical method coupled with geographic detectors produced more accurate results in constructing the vulnerability evaluation prediction model in the study area.Model construction that considered the non-disaster point information was more accurate than the IM model that considered only the disaster point information model.The improved model was suitable for local model construction.关键词
信息量模型/确定性系数法/地理探测器/SCAI/ROC曲线/易发性Key words
information method/certainty factor/geographical detectors/SCAI/ROC curve/susceptibility分类
天文与地球科学引用本文复制引用
高星星,马鹏斐,吕义清,赵金亮,何海龙..基于统计方法耦合地理探测器的地质灾害易发性评价[J].水土保持通报,2024,44(1):193-205,13.基金项目
国家自然科学青年基金"渐新世以来西地中海板块-地幔系统的四维地球动力学重建"(420020398) （420020398）
