深度随机森林和随机森林算法的滑坡易发性评价对比——以汉中市略阳县为例  

Comparison of Landslide Susceptibility Evaluation by Deep Random Forest and Random Forest Model:A Case Study of Lueyang County,Hanzhong City

作　　者：贾俊[1,2] 毛伊敏[3] 孟晓捷 高波 高满新[1] 武文英 JIA Jun;MAO Yimin;MENG Xiaojie;GAO Bo;GAO Manxin;WU Wenying(Key Laboratory for Geo-hazards in Loess Area,MLR,Xi’an Center of China Geological Survey,Xi’an 710119,Shaanxi,China;State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,Chengdu 610059,Sichuan,China;School of Information Engineering,Shaoguan University,Shaoguan 512005,Guangdong,China)

机构地区：[1]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710119 [2]地质灾害防治与地质环境保护国家重点实验室,成都理工大学,四川成都610059 [3]韶关学院信息工程学院,广东韶关512005

出　　处：《西北地质》2023年第3期239-249,共11页Northwestern Geology

基　　金：中国地质调查局项目“西北典型地区地质灾害调查”(DD20221739),“黄土高原等典型地区地质灾害精细调查与风险管控”(DD20221739)联合资助。

摘　　要：针对浅层的机器学习模型泛化能力低而导致其滑坡易发性评价模型预测精度不高的问题,笔者围绕陕西省汉中市略阳县城中心为研究区,采用深度随机森林构建区域地灾易发性评价模型来提升预测精度。依据略阳县滑坡成灾机理研究成果,选取坡度、相对高差、坡向、坡型、工程地质岩组、断裂距离、水系距离、公路铁路距离、植被覆盖等9个因子作为易发性评价指标;将研究区栅格单元按5 m×5 m进行划分并提取评价因子值,输入深度随机森林评价模型,从而获得研究区易发性评价图。依据评价结果略阳县地质灾害可划分为极高易发区、高易发区、中易发区、低易发区4个等级,面积所占比例分别为5.31%、22.97%、42.11%、29.61%,其划分结果与研究区内地质灾害实际发育情况吻合,合理反映研究区地灾分布的总体特征。深度随机森林的地质灾害易发性预测模型在ROC曲线下面积值(AUC)为91.2%,高于随机森林预测模型的86.3%,表明该模型具有一定的合理性与可行性,可为区域滑坡易发性评价进一步提供新方法。To address the problem of low prediction accuracy of landslide susceptibility evaluation model due to the difficulty of knowledge reuse and generalization of shallow machine learning model,this paper takes Lueyang County,Hanzhong City,Shaanxi Province as the study area and uses deep random forest to build a regional geological disaster susceptibility evaluation model to improve the prediction accuracy.Firstly,based on the research results of landslide mechanism in Lueyang County,nine factors such as slope,relative height difference,slope direction,slope type,engineering geological rock group,fault distance,river system distance,road and railroad distance,and vegetation cover are selected as susceptibility evaluation indexes;secondly,the study area is divided into 5 m×5 m raster cells and the values of evaluation factors are extracted and input into the depth random forest evaluation model;finally,the susceptibility evaluation map of the study area is obtained.Based on the evaluation results,geological hazards in Lueyang County can be classified into four levels:very high susceptibility,high susceptibility,medium susceptibility,and low susceptibility,with the proportion of area being 5.31%,22.97%,42.11%,and 29.61%.The classification results are consistent with the actual development of geological hazards and reasonably reflect the overall characteristics of geological hazard distribution in the study area.In addition,the area under the ROC curve of the geological hazard susceptibility prediction model of deep random forest is 91.2%,which is higher than 86.3%of the random forest prediction model,indicating that the model is reasonable and feasible,and can provide new ideas for the evaluation of regional landslide susceptibility.

关 键 词：滑坡 略阳县 易发性评价 深度随机森林 

分 类 号：P694[天文地球—地质学]