Comparative analyses of susceptibility assessment for landslide disasters based on information value, weighted information value and logistic regression coupled model in Luoping County, Yunnan Province
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摘要:
以罗平县崩滑地质灾害为研究对象，选取工程岩组、坡度、坡向、高程、起伏度、曲率、地貌类型、距河流距离、距断裂距离9个评价因子，基于共线性诊断和相关性分析对其进行独立性检验。然后采用信息量法计算各评价因子分类分级的信息量值，采用层次分析法和逻辑回归法对各评价因子进行权重的定量计算，从而构建信息量、加权信息量和信息量-逻辑回归耦合易发性评价模型并进行对比分析。基于GIS的自然断点法将评价结果划分为非、低、中和高4个等级，并采用ROC曲线对其精度进行检验。结果表明：3种评价模型的AUC值分别为0.757、0.723和0.852，信息量-逻辑回归耦合模型的精度最高，模型结果分区与崩滑地质灾害点的分布较吻合，其非、低、中和高的面积（分级比）分别为771.1 km2（25.55%）、836.6 km2（27.73%）、864.36 km2（28.64%）和545.94 km2（18.08%）。
Abstract:This study focuses on landslide susceptibility assessments in Luoping County, where 9 evaluation factors, including engineering rock group, slope, slope aspect, elevation, undulation, curvature, landform type, distance from rivers, and distance from fault, were selected as the research variables. After conducting collinearity diagnosis and correlation analysis, the information value method was applied to calculate the information value for each classification level of the evaluation factors. Quantitative weights for each evaluation factor were determined using the AHP and logistic regression methods, leading to the construction and comparison of three susceptibility evaluation models: information value, and weighted information value, and information-logistic regression coupled model. The results were categorized into four grades -- none, low, medium, and high – using the GIS-based natural breakpoint method, and their accuracy was validated using ROC curves. The results show that the AUC values of the three evaluation models were 0.757, 0.723 and 0.852 respectively, with the information-logistic regression coupled model demonstrating the highest accuracy. Moreover, the model results were in good agreement with the distribution of landslide geological disaster points. The respective areas (classification ratios) for the none, low, medium, and high categories were 771.1 km2 (25.55%), 836.6 km2 (27.73%), 864.36 km2 (28.64%), and 545.94 km2 (18.08%).
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表 1 评价因子VIF计算结果表
Table 1. Calculation results of VIF for evaluation factors
评价因子 TOL VIF 工程岩组 0.818 1.222 坡度 0.656 1.524 坡向 0.954 1.048 高程 0.904 1.107 地貌类型 0.713 1.402 起伏度 0.669 1.495 曲率 0.970 1.031 距断裂距离 0.945 1.058 距河流距离 0.717 1.396 
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表 2 评价因子之间的相关系数矩阵
Table 2. Correlation coefficient matrix of evaluation factors
评价因子 工程岩组 坡度 坡向 高程 地貌类型 起伏度 曲率 距断裂距离 距河流距离 工程岩组 1 坡度 0.07 1 坡向 −0.09 0.07 1 高程 0.03 −0.08 0.08 1 地貌类型 0.02 0.11 0.03 0.01 1 起伏度 0.11 0.03 0.04 0.00 0.01 1 曲率 0.07 −0.07 0.08 0.03 0.06 0.04 1 距断裂距离 0.09 −0.03 −0.04 0.06 0.09 −0.05 0.08 1 距河流距离 0.01 0.04 0.01 0.01 0.02 0.06 0.06 0.07 1
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表 3 评价因子分类分级信息量值
Table 3. Information value of classification levels for evaluation factors
评价因子 因子分级 崩滑数量 栅格数量 信息量值 加权信息量值 工程岩组 软硬相间碳酸盐岩夹碎屑岩岩组 2 205041 0.1347 0.0396 块状结构坚硬玄武岩岩组 50 1817099 1.1717 0.3433 坚硬层状碳酸盐岩岩组 97 15380267 −0.3014 −0.0883 第四系冲洪积松散岩组 5 661729 −0.1206 −0.0353 坡度
/（°）0～6 7 3162705 −1.3501 −0.2012 6～12 33 3790902 0.0193 0.0029 12～18 50 3707425 0.4571 0.0681 18～24 31 3008341 0.1880 0.0280 24～30 17 2054943 −0.0316 −0.0047 30～36 5 1186737 −0.7064 −0.1053 36～60 11 1091533 0.1657 0.0247 60～90 0 33429 0 0 坡向 北 16 2219489 −0.1692 −0.0129 东北 15 1920437 −0.0891 −0.0068 东 22 2493207 0.0329 0.0025 东南 31 2704414 0.2946 0.0224 南 20 2304895 0.0161 0.0012 西南 13 1974899 −0.2601 −0.0198 西 17 2138397 −0.0714 −0.0054 西北 20 2280277 0.0269 0.0020 高程/m 715～860 8 350496 0.9848 0.1468 860～1200 8 1149066 −0.2025 −0.0233 1200～1350 14 1312775 0.2239 0.4811 1350～1500 26 3226787 −0.0097 −0.1776 1500～1650 26 3079467 0.3627 −0.0402 1650～1800 29 2366839 −0.1401 1.8675 1800～1950 30 4047954 −0.5067 −0.8614 1950～2420 13 2530843 −0.5067 −3.6224 地貌类型 岩溶低中山地貌 22 2824754 −0.0904 −0.0037 构造侵蚀剥蚀地貌 18 1200919 0.5643 0.0231 岩溶中山地貌 40 3833292 0.2021 0.0083 岩溶盆地地貌 0 1948623 0 0 峰林谷地地貌 0 91609 0 0 峰丛洼地地貌 16 3752094 −0.6927 −0.0284 断块上升岩溶地貌 1 177099 −0.4119 −0.0169 断坳盆地 1 116724 0.0049 0.0002 石丘（垅岗） 2 390319 −0.5091 −0.0209 侵蚀谷地地貌 52 2561268 0.8677 0.0356 构造侵蚀岩溶地貌 2 1167462 −1.6047 −0.0658 起伏度/m 0～4 13 4183395 −1.0071 −0.0594 4～8 40 4306129 0.0879 0.0052 8～15 74 5697380 0.4232 0.0249 15～23 17 2685735 −0.2956 −0.0174 23～30 2 750479 −1.1607 −0.0684 30～38 7 294073 1.0289 0.0607 38～50 0 128414 0 0 50～220 1 57698 0.7117 0.0419 曲率 <0 70 7431512 0.0997 0.0041 0 20 3330755 −0.3505 −0.0144 >0 64 7301960 0.0277 0.0011 距断裂距离/m 0～600 70 6123046 0.2934 0.0194 600～1200 26 4659019 −0.4237 −0.0279 1200～1800 20 2742459 −0.1561 −0.0103 1800～2400 8 1599989 −0.5336 −0.0352 2400～3000 5 1028561 −0.5617 −0.0371 >3000 25 1911080 0.4281 0.0282 距河流距离/m 0～600 57 3404716 0.6748 0.0445 600～1200 32 2816455 0.2872 0.0189 1200～1800 21 2280631 0.0771 0.0051 1800～2400 14 1898512 −0.1451 −0.0096 2400～3000 6 1564553 −0.7989 −0.0528 >3000 24 6099326 −0.7731 −0.0511
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表 4 评价因子分类分级判断矩阵及其权重
Table 4. Judgment matrix and weight of classification levels for evaluation factors
评价因子 1 2 3 4 5 6 7 8 9 权重 CI/CR 工程岩组 1 2 4 2 6 8 4 4 6 0.31 0.003
0.002坡度 1/2 1 2 1 3 4 2 2 3 0.155 坡向 1/4 1/2 1 1/2 2 2 1 1 2 0.083 高程 1/2 1 2 1 3 4 2 2 3 0.155 起伏度 1/6 1/3 1/2 1/3 1 1 1/2 1/2 1 0.046 曲率 1/8 1/4 1/2 1/4 1 1 1/2 1/2 1 0.041 距断裂距离 1/4 1/2 1 1/2 2 2 1 1 2 0.082 距河流距离 1/4 1/2 1 1/2 2 2 1 1 2 0.082 地貌类型 1/6 1/3 1/2 1/3 1 1 1/2 1/2 1 0.046
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表 5 逻辑回归分析结果
Table 5. Results of logistic regression analysis
评价因子 B S.E Wals df sig 工程岩组 0.698 0.261 7.142 1 0.002 坡度 1.331 0.513 6.721 1 0.000 坡向 0.761 0.862 0.780 1 0.007 高程 0.309 0.246 1.570 1 0.002 地貌类型 0.171 0.421 0.165 1 0.006 起伏度 0.641 0.304 4.455 1 0.005 曲率 1.523 0.907 2.820 1 0.003 距断裂距离 0.528 0.365 2.090 1 0.004 距河流距离 0.458 0.264 3.001 1 0.000 常量 −0.165 0.142 1.336 1 0.005 注：B为回归系数，S.E为标准误，wals为卡方值，df为自由度，sig为显著性。
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表 6 崩滑易发性等级分布预测结果
Table 6. Prediction results of landslide susceptibility grade distribution
易发性等级 信息量模型 加权信息量模型 信息量-逻辑回归耦合模型 分级比/% 崩滑比/% 分级面积/km2 分级比/% 崩滑比/% 分级面积/km2 分级比/% 崩滑比/% 分级面积/km2 非易发区 17.56 5.84 529.96 16.17 7.14 489.03 25.55 6.49 771.1 低易发区 28.27 14.29 853.18 31.80 15.58 959.02 27.73 20.13 836.6 中易发区 32.46 31.17 979.64 33.82 35.06 1020.68 28.64 25.32 864.36 高易发区 21.71 48.70 655.22 18.20 42.21 549.27 18.08 48.05 545.94
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