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    基于GIS与WOE-BP模型的滑坡易发性评价

    郭子正 殷坤龙 付圣 黄发明 桂蕾 夏辉

    郭子正, 殷坤龙, 付圣, 黄发明, 桂蕾, 夏辉, 2019. 基于GIS与WOE-BP模型的滑坡易发性评价. 地球科学, 44(12): 4299-4312. doi: 10.3799/dqkx.2018.555
    引用本文: 郭子正, 殷坤龙, 付圣, 黄发明, 桂蕾, 夏辉, 2019. 基于GIS与WOE-BP模型的滑坡易发性评价. 地球科学, 44(12): 4299-4312. doi: 10.3799/dqkx.2018.555
    Guo Zizheng, Yin Kunlong, Fu Sheng, Huang Faming, Gui Lei, Xia Hui, 2019. Evaluation of Landslide Susceptibility Based on GIS and WOE-BP Model. Earth Science, 44(12): 4299-4312. doi: 10.3799/dqkx.2018.555
    Citation: Guo Zizheng, Yin Kunlong, Fu Sheng, Huang Faming, Gui Lei, Xia Hui, 2019. Evaluation of Landslide Susceptibility Based on GIS and WOE-BP Model. Earth Science, 44(12): 4299-4312. doi: 10.3799/dqkx.2018.555

    基于GIS与WOE-BP模型的滑坡易发性评价

    doi: 10.3799/dqkx.2018.555
    基金项目: 

    国家重点研发计划项目 2018YEC0809400

    国家自然科学基金项目 41572292

    国家自然科学基金项目 41907253

    详细信息
      作者简介:

      郭子正(1994-), 男, 博士研究生, 主要从事滑坡灾害预测预报和风险分析方面的研究

      通讯作者:

      殷坤龙(1963-), 男, 教授

    • 中图分类号: P642

    Evaluation of Landslide Susceptibility Based on GIS and WOE-BP Model

    • 摘要: 区域滑坡易发性研究对地质灾害风险管理具有重要意义.以往研究中,将多元统计模型与机器学习方法相结合用于滑坡易发性评价的研究较少.以三峡库区万州区为例,首先选取9种指标因子(坡度、坡向、剖面曲率、地表纹理、地层岩性、斜坡结构、地质构造、水系分布及土地利用类型)作为滑坡易发性评价指标.基于证据权模型(weights of evidence,WOE)计算得到的对比度和滑坡面积比与分级面积比的相对大小,对各指标因子进行状态分级;再利用粒子群法优化的BP神经网络模型(PSO-BP)得到各指标因子权重.综合两种模型确定的状态分级权重和指标因子权重(WOE-BP)计算滑坡易发性指数(landslide susceptibility index,LSI),基于GIS平台得到全区滑坡易发性分区图.结果表明:水系、地层岩性和地质构造是影响万州区滑坡发育的主要指标因子;WOE-BP模型的预测精度为80.8%,优于WOE模型的73.1%和BP神经网络模型的71.6%,可为定量计算指标因子权重和优化滑坡易发性评价提供有效途径.

       

    • 图  1  人工神经网络模型示意图

      Fig.  1.  Sketch of artificial neural network model

      图  2  WOE-BP模型计算流程

      Fig.  2.  Flow chart of WOE-BP model

      图  3  研究区地理位置及概况

      Fig.  3.  Location and general situation of study area

      图  4  万州区历史滑坡数及降雨时间分布特征

      Fig.  4.  The time distribution characteristic of history landslide number and rainfall in Wanzhou District

      图  5  地形地貌类因子状态分级统计图

      Fig.  5.  Statistical results of state classification of topography index

      图  6  不同级别水系状态分级

      Fig.  6.  Statistical results of state classification of different levels water system

      图  7  水系综合状态分级

      Fig.  7.  Statistical results of state classification of water system

      图  8  不同级别地质构造状态分级

      Fig.  8.  Statistical results of state classification of different geological structures

      图  9  基础地质类因子状态分级统计图

      Fig.  9.  Statistical results of state classification of basic geology index

      图  10  土地利用类型状态分级统计图

      Fig.  10.  Statistical results of state classification of land use

      图  11  万州区滑坡易发性分区图

      Fig.  11.  The landslide susceptibility mapping of Wanzhou District

      图  12  ROC曲线对比图

      Fig.  12.  The comparison of ROC curve

      表  1  万州区特大型滑坡信息

      Table  1.   The information of super-large landslides in Wanzhou District

      滑坡名称 位置 面积(104 m2 体积(104 m3 类型
      塘角1号滑坡 陈家坝街道 115 2 900 特大型堆积体滑坡
      和平广场滑坡 高笋塘街道 105 1 950 特大型堆积体滑坡
      枇杷坪滑坡 钟鼓楼街道 105 5 050 特大型堆积体滑坡
      下载: 导出CSV

      表  2  水系影响带分级

      Table  2.   Classification of river system influenced region

      水系 影响距离(m)
      级别 1级带 2级带 3级带 4级带
      1 [0, 800] (800, 1200] (1 200, 2 000] > 2000
      2 > 1000 (400, 800] (800, 1000] [0, 400]
      3 > 450 (300, 450] (200, 300] [0, 200]
      对比度C 1.611 0.331 0.620 -0.514
      下载: 导出CSV

      表  3  地质构造影响带分级

      Table  3.   Classification of geological structure influenced region

      构造 影响距离(m)
      类别 1级带 2级带 3级带 4级带 5级带 6级带
      1 [0, 500] (500, 900] (900, 1100] (1 800, 2 000] (1 100, 1 800] >2 000
      2 (1 800, 2 250] (1 050, 1 800] (2 250, 3 000] (450, 1050] [0, 450] >3 000
      3 (2 800, 4 000] (1 800, 2 800] [0, 800] (1 400, 1 800] (800, 1400] >4 000
      4 (900, 2400] [4800, 6000] [0, 900] [3300, 4 800] >6 000 (2 400, 3 300]
      对比度C 0.409 -0.218 -0.179 0.388 -0.110 0.919
      下载: 导出CSV

      表  4  因子相关性计算

      Table  4.   The calculation results of correlation between factors

      指标因子 坡度 坡向 高程 剖面曲率 地表纹理 水系 地层岩性 地质构造 斜坡结构 土地利用
      坡度(°) 1.00
      坡向 0.09 1.00
      高程(m) 0.16 0.10 1.00
      剖面曲率 0.09 -0.18 -0.06 1.00
      地表纹理 0.03 0.00 0.05 -0.02 1.00
      水系(m) 0.01 -0.01 -0.03 0.01 0.00 1.00
      地层岩性 -0.18 -0.01 0.01 0.01 0.00 0.02 1.00
      地质构造(m) -0.13 -0.03 -0.05 -0.07 -0.01 -0.01 -0.09 1.00
      斜坡结构 0.04 0.08 0.45 -0.03 0.02 -0.01 0.11 -0.11 1.00
      土地利用 -0.09 0.01 0.04 -0.06 0.00 -0.01 -0.07 0.26 0.03 1.00
      下载: 导出CSV

      表  5  各指标因子二级状态证据权重

      Table  5.   Weights of evidence of states of each index factor

      指标因子 取值 证据权重
      坡度(°) 0~15 0.161
      15~25 0.05
      25~35 -0.308
      35~45 -0.286
      45~71 -0.29
      坡向(°) -1 0.289
      0~45 0.102
      45~90 0.102
      90~135 -0.087
      135~180 -0.144
      180~225 -0.148
      225~270 0.173
      270~315 0.058
      315~360 -0.203
      剖面曲率 凹型坡 -0.016
      直线坡 0.185
      凸型坡 -0.02
      地表纹理 0~0.327 1.135
      0.327~0.545 -0.758
      0.545~0.763 -1.049
      0.763~0.817 0.179
      水系缓冲距离(m) 1级带 0.494
      2级带 -0.786
      3级带 -0.497
      4级带 -1.631
      地层岩性 T3xj -0.416
      J3s -0.024
      J3p -0.841
      T2b -1.39
      T1j -2.314
      J1z -0.153
      J1z-2z -0.295
      J2x 0.733
      J2xs -0.372
      J2s 0.104
      P2 -0.102
      T1d -0.106
      地质构造缓冲距离(m) 1级带 -0.409
      2级带 -0.218
      3级带 -0.179
      4级带 0.388
      5级带 -0.11
      6级带 0.919
      斜坡结构 飘倾坡 0.363
      伏倾坡 -0.232
      层状坡 0.488
      顺斜坡 0.194
      横向坡 0.103
      逆斜坡 -0.192
      逆向坡 -0.472
      土地利用 城镇用地 0.652
      电站 1.428
      交通运输 0.179
      林牧业 -0.547
      农业 0.267
      水域 1.517
      水工用地 1.285
      其余 -0.479
      下载: 导出CSV

      表  6  指标因子权重计算结果

      Table  6.   The results of weights of index factors

      编号 指标因子 PSO-BP计算权重 ArcGIS输入权重
      1 坡度 0.878 9 1.274 5
      2 坡向 0.884 3 1.282 3
      3 剖面曲率 0.756 4 1.096 9
      4 地表纹理 1.108 4 1.607 3
      5 水系 1.432 8 2.077 7
      6 地层岩性 1.186 1 1.720 0
      7 地质构造 1.128 7 1.636 7
      8 斜坡结构 0.934 8 1.355 6
      9 土地利用 0.689 6 1.000 0
      注:ArcGIS输入权重=计算权重/最小指标因子权重.
      下载: 导出CSV

      表  7  栅格统计结果

      Table  7.   The statistical results of grids

      易发性等级 分级栅格数 分级比例(%) 滑坡栅格数 滑坡占总栅格比例 滑坡比例(%) 滑坡比率
      1 801004 32.57 9 162 0.51 12.74 0.391 2
      1 302703 23.56 10 117 0.78 14.07 0.597 2
      1 677254 30.33 23 241 1.39 32.32 1.065 5
      极高 749 196 13.55 29 399 3.92 40.88 3.017 4
      下载: 导出CSV

      表  8  WOE-BP模型预测正确率和错报率

      Table  8.   The correct rate and erroneous rate in WOE-BP model prediction

      样本类型 样本数(个) 预测正确的样本数(个) 正确率(%) 预测错误的样本数(个) 错报率(%)
      训练样本 10 000 8 409 84.1 880 8.8
      预测样本 61 919 44 231 71.4 8 282 13.4
      总样本 71 919 52 640 73.2 9 162 12.7
      下载: 导出CSV
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    • 收稿日期:  2017-09-22
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