深度随机森林和随机森林算法的滑坡易发性评价对比

贾俊, 毛伊敏, 孟晓捷, 高波, 高满新, 武文英. 2023. 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. 西北地质, 56(3): 239-249. doi: 10.12401/j.nwg.2023084
引用本文: 贾俊, 毛伊敏, 孟晓捷, 高波, 高满新, 武文英. 2023. 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. 西北地质, 56(3): 239-249. doi: 10.12401/j.nwg.2023084
JIA Jun, MAO Yimin, MENG Xiaojie, GAO Bo, GAO Manxin, WU Wenying. 2023. Comparison of Landslide Susceptibility Evaluation by Deep Random Forest and Random Forest Model: A Case Study of Lueyang County, Hanzhong City. Northwestern Geology, 56(3): 239-249. doi: 10.12401/j.nwg.2023084
Citation: JIA Jun, MAO Yimin, MENG Xiaojie, GAO Bo, GAO Manxin, WU Wenying. 2023. Comparison of Landslide Susceptibility Evaluation by Deep Random Forest and Random Forest Model: A Case Study of Lueyang County, Hanzhong City. Northwestern Geology, 56(3): 239-249. doi: 10.12401/j.nwg.2023084

深度随机森林和随机森林算法的滑坡易发性评价对比

  • 基金项目: 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。
详细信息
    作者简介: 贾俊(1985−),男,高级工程师,主要从事地质灾害调查工作。E−mail:geoj@qq.com
    通讯作者: 孟晓捷(1986−),男,高级工程师,主要从事地质灾害调查工作。E−mail: 270405820@qq.com
  • 中图分类号: P694

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

More Information
  • 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。

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  • 图 1  研究区位置图

    Figure 1. 

    图 2  研究区灾害示意图

    Figure 2. 

    图 3  深度随机森林模型流程结构(据Zhou, 2017

    Figure 3. 

    图 4  滑坡与单评价因子分类图

    Figure 4. 

    图 5  略阳县随机森林滑坡易发性评价图

    Figure 5. 

    图 6  略阳县深度随机森林滑坡易发性评价图

    Figure 6. 

    图 7  深度随机森林与随机森林易发性评价ROC曲线对比图

    Figure 7. 

    表 1  各评价因子信息量表

    Table 1.  Weighted information values of individual evaluation factors

    因子分级Si(km2Ni(个)Ii
    坡度 <10° 10.535625 8 −0.085244
    10°~20° 13.3961 21 0.639636
    20°~30° 35.77955 46 0.441342
    30°~40° 54.226925 38 −0.165514
    40°~50° 38.6219 12 −0.978836
    >50° 13.119575 12 0.100879
    相对高差 16~175 m 24.930925 53 0.944260
    175~238 m 55.38815 46 0.004353
    238~300 m 49.224425 29 −0.339017
    300~379 m 26.43665 8 −1.005232
    379~605 m 9.6986 1 −2.081904
    坡向 0~45° 23.746850 21 0.067150
    45°~90° 21.137625 23 0.274517
    90°~135° 17.924900 10 −0.393528
    135°~180° 18.869250 14 −0.108399
    180°~225° 20.641625 26 0.420864
    225°~275° 22.018400 18 −0.011429
    275°~315° 20.152475 13 −0.248300
    315°~360° 21.185550 12 −0.378335
    曲率 <−0.5(凹形坡) 11.1099 12 0.267147
    −0.5~0.5
    (直线形坡)
    143.597 119 0.002190
    >0.5(凸形坡) 10.969775 6 −0.413307
    工程地质岩组 坚硬岩组 65.882425 40 −0.308915
    半坚硬岩组 29.980725 13 −0.645528
    软硬相间岩组 58.766425 46 −0.054852
    松散岩组 11.050425 39 1.451170
    距断裂距离 <100 m 31.79 26 −0.010915
    100~200 m 25.87 26 0.195167
    200~500 m 49.79 53 0.252595
    500~1000 m 34.60 23 −0.218224
    >1000 m 23.64 9 −0.775554
    距河流水系
    距离
    <200 m 69.69 86 0.400425
    200~400 m 52.38 31 −0.334384
    400~600 m 27.98 17 −0.308056
    600~800 m 11.37 1 −2.240549
    >800 m 4.28 2 −0.569794
    距公路、铁路
    距离
    <100 m 18.99 58 1.306584
    100~500 m 46.12 41 0.072488
    500~1000 m 38.06 14 −0.809915
    1000~1500 m 26.29 11 −0.681226
    >1500 m 36.23 13 −0.834794
    NDVI −0.41~0.07 1.88 0
    0.07~0.32 7.64 26 1.415100
    0.32~0.52 26.25 56 0.947905
    0.52~0.68 91.74 50 −0.416840
    0.68~0.84 38.18 5 −1.842838
    下载: 导出CSV

    表 2  易发性等级划分与滑坡实际发生比率对比表

    Table 2.  Comparison of susceptibility classification and actual landslide occurrence rate

    评价
    方法
    易发性
    等级
    a
    易发分区面积占比(%)
    b
    分区滑坡数量
    c
    滑坡百分比(%)
    c/a
    滑坡发生比率
    随机森林16.3410.730.04
    69.217454.010.78
    11.244029.202.60
    极高3.212216.065.00
    深度
    随机森林
    29.6175.110.17
    42.114129.930.71
    22.976245.261.97
    极高5.312719.713.71
    下载: 导出CSV
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出版历程
收稿日期:  2023-03-15
修回日期:  2023-04-23
刊出日期:  2023-06-20

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