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基于滑坡分类和改进卷积神经网络的滑坡敏感性区划

尹超 李仲波 刘新良 李颖 王绍平 郭兵

尹超,李仲波,刘新良,等. 基于滑坡分类和改进卷积神经网络的滑坡敏感性区划[J]. 中国地质灾害与防治学报,2023,34(0): 1-14 doi: 10.16031/j.cnki.issn.1003-8035.202301003
引用本文: 尹超,李仲波,刘新良,等. 基于滑坡分类和改进卷积神经网络的滑坡敏感性区划[J]. 中国地质灾害与防治学报,2023,34(0): 1-14 doi: 10.16031/j.cnki.issn.1003-8035.202301003
YIN Chao,LI Zhongbo,LIU Xinliang,et al. Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-14 doi: 10.16031/j.cnki.issn.1003-8035.202301003
Citation: YIN Chao,LI Zhongbo,LIU Xinliang,et al. Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-14 doi: 10.16031/j.cnki.issn.1003-8035.202301003

基于滑坡分类和改进卷积神经网络的滑坡敏感性区划

doi: 10.16031/j.cnki.issn.1003-8035.202301003
基金项目: 国家自然科学基金项目(51808327);山东省自然科学基金项目(ZR2019PEE016、ZR2021MD011)。
详细信息
    作者简介:

    尹超:尹 超(1987-),男,山东日照人,博士,副教授,主要从事自然灾害风险评价方面的研究,E-mail:yinchao1987611@163.com

    通讯作者:

    李 颖(1977-),女,黑龙江依安人,副教授,主要从事道路与桥梁工程方面的研究,E-mail:liying@sdut.edu.cn

  • 中图分类号: P694

Landslide susceptibility assessment and zonation based on landslide classification and improved Convolutional Neural Networks

  • 摘要: 滑坡敏感性区划是根据研究区域的滑坡调查数据和地质环境条件,分析致灾因子的组合特征对滑坡发生的影响并将研究区域划分为不同等级的敏感区,为土地利用规划和滑坡防治政策制定提供理论依据。对山东省淄博市博山区开展了工程岩组和地质灾害调查,结合多种数据源和地质调查资料建立了博山区滑坡数据库;采用Pearson相关系数法筛选了滑坡致灾因子,基于信息量法分别对全部滑坡、自然滑坡和工程滑坡的致灾因子进行分级;建立了包含2轮卷积和池化的7层改进卷积神经网络,分别对全部滑坡、自然滑坡和工程滑坡进行了评价模型的训练和验证,采用AUC法验证了模型的准确性;基于ArcGIS12.0计算了博山区所有栅格的滑坡敏感性概率,绘制了博山区滑坡敏感性区划图。研究结果表明:滑坡致灾因子包括高程、坡度、坡向、剖面曲率、平面曲率、距河流距离、地表流沙输送量、地形湿度指数、距道路距离、土地利用类型、距断层距离、工程岩组和归一化植被覆盖指数;博山区滑坡敏感性概率最小为0.136、最大为0.841;极高敏感区、高敏感区、中敏感区、低敏感区和极低敏感区分别占博山区总面积的8.08%(56.4 km2)、17.62%(123.0 km2)、25.33%(176.8 km2)、32.87%(229.4 km2)和16.10%(112.4 km2),极高敏感区主要分布在博山区西北部、南部、东北部及其他地区,其中,自然滑坡主要分布于西北部极高敏感区,工程滑坡主要分布于东北部极高敏感区。
  • 图  1  博山区滑坡分布图

    Figure  1.  Landslide distribution map of Boshan district

    图  2  博山区典型滑坡

    Figure  2.  Typical landslides site photo in Boshan district

    图  3  高程分级图

    Figure  3.  Elevation classification map

    图  4  坡度分级图

    Figure  4.  Slope gradient classification map

    图  5  坡向分级图

    Figure  5.  Slope Aspect classification map

    图  6  剖面曲率分级图

    Figure  6.  Profile curvature classification map

    图  7  平面曲率分级图

    Figure  7.  Plane curvature classification map

    图  8  距河流距离分级图

    Figure  8.  Distance from rivers classification map

    图  9  STI分级图

    Figure  9.  STI classification map

    图  10  TWI分级图

    Figure  10.  TWI classification map

    图  11  距道路距离分级图

    Figure  11.  Distance from roads classification map

    图  12  距断层距离分级图

    Figure  12.  Distance from faults classification map

    图  13  NDVI分级图

    Figure  13.  NDVI classification map

    图  14  土地利用分级图

    Figure  14.  Land use classification map

    图  15  工程岩组分级图

    Figure  15.  Engineering Agrotype classification map

    图  16  二维方阵结构形式

    Figure  16.  Two dimensional matrix structure form a) Based on All Landslides b) Based on Natural Landslides c) Based on Engineering Landslides

    图  17  ROC曲线及AUC值

    Figure  17.  ROC curves and AUC values of susceptibility results

    图  18  博山区滑坡敏感性区划图

    Figure  18.  Landslide susceptibility zoning map of Boshan district

    表  1  数据源和地质调查资料

    Table  1.   Data sources and geological survey data

    数据源和地质调查资料可提取的信息数据提供者或下载地址
    Landsat TM影像土地利用类型、NDVI地理空间数据云(http://www.gscloud.cn/
    博山区数字高程模型(DEM)高程、坡度、坡向、剖面曲率、平面曲率、
    距河流距离、SPI、STI、TWI
    山东省断层数据图距断层距离地质专业知识服务系统(http://geol.ckcest.cn/
    博山区道路数据距道路距离https://www.openstreetmap.org/#map=5/34.574/113.247
    山东省工程岩组图工程岩组中国科学院地理科学与资源研究所资源环境科学与数据中心(http://www.resdc.cn/
    博山区降水数据、博山区地质灾害普查数据、
    博山区地质灾害防治方案
    年平均降水量、滑坡数据淄博市自然资源和规划局、淄博市交通运输局、博山区气象局
    博山区工程岩组和地质灾害调查数据工程岩组、滑坡数据山东理工大学
    下载: 导出CSV

    表  2  Pearson相关系数计算结果

    Table  2.   Calculation results of Pearson correlation coefficient

    影响
    因子
    高程坡度坡向剖面
    曲率
    平面
    曲率
    年平均
    降水量
    距河流
    距离
    SPISTITWI距道路
    距离
    土地
    利用
    距断层
    距离
    工程
    岩组
    NDVI
    高程1.000
    坡度0.3701.000
    坡向−0.052−0.0191.000
    剖面曲率−0.0370.1190.0191.000
    平面曲率0.2460.099−0.092−0.3581.000
    年平均降水量0.2690.163−0.2740.537−0.3251.000
    距河流距离0.190−0.1120.1620.0690.044−0.6381.000
    SPI−0.0340.0020.0910.257−0.2610.0620.0401.000
    STI0.1630.3690.0470.366−0.3600.173−0.0530.8261.000
    TWI0.060−0.2340.0600.229−0.333−0.2270.2060.4780.2221.000
    距道路距离0.2870.0740.052−0.0270.060−0.0820.3120.0010.0400.0871.000
    土地利用0.3560.368−0.0220.2040.0530.2610.1120.0830.210−0.1640.1711.000
    距断层距离0.0850.0980.1130.050−0.0550.173−0.0210.0370.1490.0120.2870.0411.000
    工程岩组−0.164−0.1040.0060.005−0.0930.372−0.093−0.101−0.1050.006−0.243−0.085−0.0091.000
    NDVI0.1910.110−0.1910.0200.0270.2190.104−0.0180.012−0.1760.1750.139−0.128−0.0681.000
    下载: 导出CSV

    表  3  样本集概况

    Table  3.   Overview of the sample dataset

    样本类别自然滑坡栅格数工程滑坡栅格数无明显滑坡迹象的
    普通边坡栅格数
    全部滑坡6198411460
    自然滑坡6190619
    工程滑坡0841841
    下载: 导出CSV

    表  4  改进CNN的结构参数

    Table  4.   Structure parameters of the improved CNN model

    层号层名层尺寸过滤器尺寸步长零补方式
    1Input13×1300NONE
    2Conv-113×133×3×41SAME
    3Pool-113×13×42×22VALID
    4Conv-26×6×43×3×81SAME
    5Pool-26×6×82×22VALID
    6F-layer72NONENONENONE
    7SoftMax2NONENONENONE
    下载: 导出CSV
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  • 收稿日期:  2022-12-03
  • 录用日期:  2023-07-10
  • 网络出版日期:  2023-07-16

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