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IOE模型在延安市宝塔区碾庄沟流域滑坡易发性分区中的应用

IOE模型在延安市宝塔区碾庄沟流域滑坡易发性分区中的应用

ISSN:1672-643X
2021年第32卷第1期
岩土工程
张庭瑜,孙增慧,程杰,刘金宝,石磊,孔辉,杨亮彦,罗丹 ZHANG Tingyu,SUN Zenghui,CHENG Jie,LIU Jinbao,SHI Lei,KONG Hui,YANG Liangyan,LUO Dan
1.陕西地建土地工程技术研究院有限责任公司;2.陕西省土地工程建设集团有限责任公司;3.自然资源部退化及未利用土地整治工程重点实验室;4.陕西省土地整治工程技术研究中心

将延安市宝塔区碾庄沟流域作为研究区,在野外调查以及遥感解译的基础上,得到了73个滑坡点数据,其中70%的滑坡点被当作训练样本,剩余的30%的滑坡点被当作测试样本.选取坡度、坡向、高程、归一化植被指数(NDVI)、岩土体类型、土地利用类型、平面曲率和剖面曲率作为滑坡易发性分区建模的解释变量.利用熵指数模型(IOE)计算研...

The Nianzhuanggou watershed of Yan’an City was regarded as the study area.Based on the field survey and remote sensing image,the data of 73 landslide points were obtained.70%of the points were used as training dataset,and the remaining were used for validation purpose.Slope,aspect,elevation,normalized difference vegetation index(NDVI),lithology,land use,plan curvature and profile curvature were selected as explanatory variables for landslide susceptibility modeling.The landslide susceptibility index(LSI)of the study area was calculated using the index of entropy model(IOE),and a landslide susceptibility map(LSM)was generated.Finally,the results were evaluated using the accuracy and area under the receiver operating characteristic curve(AUC).The results show that the accuracy of the training dataset and the validation dataset are both greater than 0.8,and the AUC value of validation dataset is 0.9641,indicating that the LSM is highly reliable,and the IOE model has strong generalization ability.The results can also provide some reference for the local prevention and control of landslides.

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ISSN:1672-643X
2021年第32卷第1期
岩土工程

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