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基于逻辑回归模型和3S技术的思南县滑坡易发性评价

胡涛 樊鑫 王硕 郭子正 刘爱昌 黄发明

胡涛, 樊鑫, 王硕, 郭子正, 刘爱昌, 黄发明. 基于逻辑回归模型和3S技术的思南县滑坡易发性评价[J]. 地质科技通报, 2020, 39(2): 113-121. doi: 10.19509/j.cnki.dzkq.2020.0212
引用本文: 胡涛, 樊鑫, 王硕, 郭子正, 刘爱昌, 黄发明. 基于逻辑回归模型和3S技术的思南县滑坡易发性评价[J]. 地质科技通报, 2020, 39(2): 113-121. doi: 10.19509/j.cnki.dzkq.2020.0212
Hu Tao, Fan Xin, Wang Shuo, Guo Zizheng, Liu Aichang, Huang Faming. Landslide susceptibility evaluation of Sinan County using logistics regression model and 3S technology[J]. Bulletin of Geological Science and Technology, 2020, 39(2): 113-121. doi: 10.19509/j.cnki.dzkq.2020.0212
Citation: Hu Tao, Fan Xin, Wang Shuo, Guo Zizheng, Liu Aichang, Huang Faming. Landslide susceptibility evaluation of Sinan County using logistics regression model and 3S technology[J]. Bulletin of Geological Science and Technology, 2020, 39(2): 113-121. doi: 10.19509/j.cnki.dzkq.2020.0212

基于逻辑回归模型和3S技术的思南县滑坡易发性评价

doi: 10.19509/j.cnki.dzkq.2020.0212
基金项目: 

国家自然科学基金项目 41807285

江西省自然科学基金项目 20192BAB216034

中国博士后基金项目 2019M652287

江西省博士后基金项目 2019KY08

详细信息
    作者简介:

    胡涛(1986—),男,工程师,主要从事地质灾害风险评价工作。E-mail:hutao_2018@sina.com

    通讯作者:

    樊鑫(1984—),男,高级工程师,主要从事地质灾害预测与易发性评价工作。E-mail:fx.1984@163.com

  • 中图分类号: P642.22

Landslide susceptibility evaluation of Sinan County using logistics regression model and 3S technology

  • 摘要: 区域滑坡易发性评价对滑坡灾害防治具有重要意义,贵州省思南县由于其特殊的自然地理和地质条件,受滑坡地质灾害的影响非常严重,因此,非常有必要对思南县的滑坡易发性进行评价。在滑坡编录的基础上,采用由RS、GIS和GPS组成的3S技术,获取了思南县的数字高程模型、坡度、坡向、剖面曲率、坡长、岩土类型、地表湿度指数、距离水系的距离、植被覆盖度和地表建筑物指数10个滑坡影响因子;再在频率比和相关性分析的基础上,利用逻辑回归模型对思南县的滑坡易发性进行了评价并绘制了易发性分布图。结果表明:利用逻辑回归模型预测思南县滑坡易发性的准确率(AUC值)达到0.797,较为准确地预测出了思南县滑坡分布规律;极高和高滑坡易发区主要分布在高程低于600 m、地表坡度较大且以软质岩类为主的区域;而极低和低滑坡易发区主要分布在高程较高、地表坡度较小且以硬质岩类为主的区域。

     

  • 图 1  思南县Landsat 8遥感影像及滑坡地灾分布图

    Figure 1.  remote sensing image and landslides distribution location of Sinan County

    图 2  思南县地形地貌因子的频率比值

    Figure 2.  Frequency ratio values of geographic and geomorphic conditions of Sinan County

    图 3  思南县岩土类型频率比分布

    Figure 3.  Frequency ratio values of rock types in Sinan County

    图 4  思南县MNDWI(a)和距离水系的距离(b)的频率比值

    Figure 4.  Frequency ratio values of MNDWI (a) and distance to river (b) in Sinan County

    图 5  思南县NDBI(a)和NDVI(b)频率比值

    Figure 5.  Frequency ratio values of NDBI (a) and NDVI (b) maps in Sinan County

    图 6  逻辑回归模型计算得到的思南县滑坡易发性分布图

    Figure 6.  Landslide susceptibility mapping result calculated using the logistic model

    图 7  逻辑回归模型计算思南县滑坡易发性的ROC预测率曲线

    Figure 7.  ROC curve of landslide susceptibility indexes calculation using the logistic model

    表  1  滑坡易发性评价的影响因子分级体系

    Table  1.   Classification system of basic influencing factors of landslides in Sinan County

    因子类别 影响因子 因子分级
    地形地貌 高程/m < 476;476~ < 568;568~ < 648;648~ < 729;729~ < 815;815~ < 911;911~1 021;>1 021
    坡度/(°) < 6.11;6.11~ < 10.88;10.88~ < 15.40;15.40~ < 19.91;19.91~ < 24.95;24.95~ < 31.06;31.06~39.29;>39.29
    坡向 平坡;正北;东北;正东;东南;正南;西南;正西;西北
    剖面曲率 < 2.2;2.2~ < 4.2;4.2~ < 6.4;6.4~ < 8.7;8.7~ < 11.5;11.5~ < 14.9;14.9~19.9;>19.9
    坡长/m < 1.3;1.3~ < 2.7;2.7~ < 4.0;4.0~ < 5.5;5.5~ < 7.2;7.2~ < 9.4;9.4~ < 12.1;>12.1
    工程地质 岩土类型 软质岩类;硬质岩类;软硬相间岩类;松散岩类
    水文环境 MNDWI < 39;39~ < 61;61~ < 83;83~ < 106;106~ < 132;132~ < 163;163~215;>215
    距离水系的距离/m < 300;300~ < 600;600~900;>900 m
    地表覆盖因子 NDVI < 38;38~ < 93;93~ < 128;128~ < 154;154~ < 176;176~ < 199;199~224;>224
    NDBI < 44;44~ < 73;73~ < 100;100~ < 126;126~ < 154;154~ < 183;183~218;>218
    下载: 导出CSV

    表  2  逻辑回归方程中的相关变量

    Table  2.   Relative variables of the logistic regression model

    变量 影响因子 系数值 S.E. Wals df Sig.
    X1, j 高程 1.508 0.026 3 344.073 1 0.000
    X2, j 坡度 1.500 0.032 2 164.334 1 0.000
    X3, j 坡向 -0.109 0.138 22.627 1 0.041
    X4, j 剖面曲率 1.717 0.093 340.572 1 0.000
    X5, j 坡长 0.655 0.037 317.869 1 0.000
    X6, j 岩土类型 0.998 0.015 4 298.464 1 0.000
    X7, j MNDWI 0.784 0.093 71.343 1 0.000
    X8, j 距离水系的距离 2.714 0.081 1 124.072 1 0.000
    X9, j NDBI 0.225 0.088 49.622 1 0.000
    X10, j NDVI 0.622 0.038 34.364 1 0.000
    C 常量 -11.450 0.241 2 263.122 1 0.000
    注:S.E.标准误差;Wals.检验因子;df.自由度;Sig.显著性检验
    下载: 导出CSV
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