孟晓捷,张新社,曾庆铭,王冬.基于加权信息量法的黄土滑坡易发性评价——以1:5万天水市麦积幅为例[J].西北地质,2022,55(2):249-259 MENG Xiaojie,ZHANG Xinshe,ZENG Qingming,WANG Dong.The Susceptibility Evaluation of Loess Landslide Based on Weighted Information Value Method—Taking 1: 50 000 Map of Maiji District of Tianshui City As an Example[J].Northwestern Geology,2022,55(2):249-259
基于加权信息量法的黄土滑坡易发性评价——以1:5万天水市麦积幅为例
The Susceptibility Evaluation of Loess Landslide Based on Weighted Information Value Method—Taking 1: 50 000 Map of Maiji District of Tianshui City As an Example
投稿时间:2021-04-07  修订日期:2021-11-10
DOI:10.19751/j.cnki.61-1149/p.2022.02.022
中文关键词:  地质灾害;易发性评价;加权信息量模型;GIS;麦积区
英文关键词:geological hazard;the susceptibility evaluation;weighted Information model;GIS;Maiji area
基金项目:中国地质调查局“关中平原城市群综合地质调查”(DD20190294)。
作者单位E-mail
孟晓捷 自然资源部黄土地质灾害重点实验室, 中国地质调查局西安地质调查中心, 陕西 西安 710054  
张新社 自然资源部黄土地质灾害重点实验室, 中国地质调查局西安地质调查中心, 陕西 西安 710054 zxinshe@qq.com 
曾庆铭 自然资源部黄土地质灾害重点实验室, 中国地质调查局西安地质调查中心, 陕西 西安 710054  
王冬 自然资源部黄土地质灾害重点实验室, 中国地质调查局西安地质调查中心, 陕西 西安 710054  
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中文摘要:
      在1:5万天水市麦积区幅地质灾害野外调查工作的基础上,针对研究区黄土滑坡,选取高程、坡度、工程地质岩组、植被归一化指数、距断裂距离、距水系距离和距道路距离等作为评价因子;采用加权信息量模型按照网格划分,基于ArcGIS平台进行易发性评价。根据评价结果,可将1:5万麦积区幅划分为极高易发区、高易发区、中易发区和低易发区4个等级,分布面积分别为97.29 km2、124.71 km2、94.99 km2和121.73 km2。通过ROC曲线对该评价结果进行验证,评价精度为75.04%,表明该评价具有较好的准确性。其评价结果可为该地区进行地质灾害防治规划、重大工程规划建设提供科学依据。
英文摘要:
      Based on the field work of 1:50,000 geological hazard survey, the elevation,slope,engineering geological rock group, normalized difference vegetative index, distance to faults, distance to water system and distance to roads are selected as evaluation factors in the study area, and the weighted information value model is used to evaluate the susceptibility based on ArcGIS platform according to grid division. According to the evaluation results, the study area could be divided into four classes:very high susceptibility area, high susceptibility area, medium susceptibility area and low susceptibility area, with the distribution areas of 97.29 km2, 124.71 km2, 94.99 km2and 121.73 km2. The evaluation results are verified by ROC curve and demonstrate that evaluation accuracy come to 75.04%. The evaluation results could provide a scientific basis for geological disaster prevention and control planning, major project planning and construction.
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