Classification Optimization of Geological Hazard Susceptibility Evaluation Factors Based on AIFFC Algorithm
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摘要: 本文针对地质灾害易发性评价因子分级数不确定的问题,引入自适应膨胀因子模糊覆盖分级方法(AIFFC)对易发性评价因子分级进行优化。以湖南省湘乡市为研究区,提取了坡度、坡向、高程、年平均降雨量、归一化植被指数(NDVI)、道路、断层、岩性和土地利用9类评价因子,运用AIFFC及自然断点法对连续型因子进行分级,并分别代入加权信息量模型和随机森林模型,获取研究区易发性区划图。采用单因子分级结果精度对比、灾积比分析和易发性分区结果ROC曲线对比对AIFFC分级法的优越性进行检验,结果表明:各因子采用AIFFC算法分级的AUC值均高于自然断点法;基于AIFFC的随机森林模型及加权信息量模型的高易发区灾积比分别提升了56.3%、74.6%,低易发区灾积比分别降低了48%、58.1%,AUC值分别提升了7.6%、2.7%。采用AIFFC分级方法优化了地质灾害易发性评价因子分级,显著提高了地质灾害易发性评价的合理性。Abstract: This paper addresses the issue of uncertainty in the grading of geological hazard susceptibility evaluation factors and introduces the adaptive expansion factor fuzzy coverage grading method (AIFFC) to optimize the grading of geological hazard susceptibility evaluation factors. Taking Xiangxiang city, Hunan province as the research area, nine evaluation factors, including slope, slope direction, elevation and average annual rainfall, normalized difference vegetation index (NDVI) for land use, roads, faults, lithology, were extracted. The AIFFC method and the natural breakpoint method were used to grade continuous factors. These graded factors were then incorporated into a weighted information model and random forest model to obtain a susceptibility zoning map for the study area. The superiority of the AIFFC classification method was tested through the comparison of single-factor grading results, disaster product ratio analysis,and ROC curve comparison of susceptibility zoning results. Based on AIFFC, the hazard accumulation ratio of the random forest model and the weighted information entropy model in the high susceptibility areas increased by 56.3% and 74.6%, respectively, while in the low susceptibility areas, it decreased by 48% and 58.1%, respectively. The AUC values increased by 7.6% and 2.7%, respectively. The AIFFC classification method is used to optimize the evaluation factor classification of geological disaster susceptibility, which significantly improves the rationality of the evaluation of geological disaster susceptibility.
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表 1 各评价因子AIFFC分级参数
Table 1. AIFFC classification parameters for each evaluation factor
评价因子 研究区范围 灾害点分布范围 di λ 分级数(l) 分级区间({ρl}) 坡度/(°) [0,71.26] [2,70] 1.0~2.0 8 7 {1, 12, 125, 35, 14, 49, 34} 坡向/(°) [0,360] [0,360] 1.0~1.67 20 12 {10, 11, 19, 23, 38, 52, 25, 30, 25, 15, 9, 13} 高程/m [31.90,800.44] [113.12,456.70] 1.0~2.0 40.33 8 {112, 92, 34, 22, 5, 3, 1, 1} 年平均降雨量/mm [1202.70,1600.43] [1221.03,1554.89] 1.0~1.9 22.81 10 {1, 2, 14, 19, 59, 70, 60, 36, 8, 1} NDVI [0,0.61] [0.015,0.417] 1.0~1.5 0.04 6 {7, 27, 48, 89, 85, 14} 距道路距离/m [0,大于3483.20] [326.11,3483.20] 1.0~1.79 230.84 10 {102, 55, 33, 37, 16, 10, 10, 5, 1, 1} 距断层距离/m [0,大于4634.35] [423.71,4634.35] 1.0~1.5 236.17 11 {75, 57, 43, 38, 10, 16, 10, 6, 5, 5, 5} 表 2 AIFFC分级结果
Table 2. AIFFC classification results
评价因子 分级数 分级结果 坡度/(°) 8 0~2;2~22;22~35;35~48;48~55;55~65;65~70;大于70 坡向/(°) 12 0~30;30~68;68~90;90~125;125~162;162~190;190~225;225~260;260~280;280~310;310~338;338~360 高程/m 9 31.9~113.12;113.12~165.57;165.57~221.23;221.23~278.54;278.54~333.59;333.59~367.50;367.50~408.51;408.51~456.70;大于456.70 年平均降雨量/mm 11 1 202.70~1 221.03;1 221.03~1 283.85;1 283.85~1 336.92;1 336.92~1 368.54;1 368.54~1 410.03;
1 410.03~1 446.28;1 446.28~1 484.91;1 484.91~1 516.62;1 516.62~1 536.87;1 536.87~1 554.89;
大于1 554.89NDVI 7 0~0.015;0.015~0.180;0.180~0.246;0.246~0.316;0.316~0.377;0.377~0.417;大于0.417 距道路距离/m 11 0~326.11;326.11~664.23;664.23~989.03;989.03~1368.63;1 368.63~1 688.75;1 688.75~2 075.72;
2 075.72~2 497.47;2 497.47~2 831.94;2 831.94~3 065.30;3 065.30~3 483.20;大于3 483.20距断层距离/m 12 0~423.71;423.71~850.88;850.88~1 272.26;1 272.27~1 694.48;1 694.49~2 150.42;2 150.43~2 485.00;2 485.01~3 005.74;3 005.75~3 523.15;3 523.16~4 107.21;4 107.22~4 248.58;4 248.59~4 634.35;大于4 634.35 表 3 自然断点法分级结果
Table 3. Natural break point method grading results
评价因子 分级数 分级结果 坡度/(°) 8 0~3.91;3.91~9.50;9.50~15.37;15.37~20.95;20.95~26.26;26.26~31.85;31.85~38.56;38.56~71.26 坡向/(°) 12 0~24.48;24.48~ 57.04;57.04~88.18;88.18~ 117.91;117.91~147.64;147.64~ 177.37;177.37~ 208.52;208.52~239.66;239.66~269.39;269.39~ 299.12;299.12~ 328.85;328.85~ 360.00 高程/m 9 31.90~79.93;79.93~121.96;121.96~166.99;166.99~218.03;218.03~275.07;275.07~341.11;341.11~425.17;425.17~542.26;542.26~800.44 年平均降雨量/mm 11 1 202.70~1 289.62;1 289.62~1 333.91;1 333.91~1 363.46;1 363.46~1 386.40;1 386.40~1 405.55;1 405.55~1 425.18;1 425.18~1 444.75;1 444.75~1 463.71;1 463.71~1 488.88;1 488.88~1 523.98;1 523.98~1 600.42 NDVI 7 0~0.051;0.051~0.152;0.152~0.208;0.208~0.259;0.259~0.303;0.303~0.347;0.347~0.611 距道路距离/m 11 0~71.14;71.14~167.93;167.93~287.96;287.96~398.67;398.67~534.77;534.77~757.79;757.79~1 088.95;1 088.95~1 532.08;1 532.08~2 160.22;2 160.22~3 483.20;大于3 483.20 距断层距离/m) 12 0~93.41;93.41~195.93;195.93~317.53;317.53~464.40;464.40~667.68;667.68~850.88;850.88~1 059.58;1 059.58~1 363.72;1 363.72~1 914.46;1 914.46~2 795.16;2 795.16~4 634.35;大于4 634.35 表 4 易发性评价结果灾积比统计表
Table 4. Statistical table of disaster accumulation ratio - product ratio for susceptibility evaluation results
评价
模型易发性
分区面积
占比灾积比 评价
模型易发性
分区面积
占比灾积比 NBC-MIV 高易发 13.62% 0.611 AIFFC-MIV 高易发 11.73% 0.955 中易发 25.42% 0.178 中易发 19.61% 0.147 低易发 60.96% 0.050 低易发 68.76% 0.026 NBC-RF 高易发 15.03% 0.755 AIFFC-RF 高易发 9.68% 1.318 中易发 28.53% 0.096 中易发 25.86% 0.083 低易发 56.44% 0.031 低易发 64.45% 0.013 -
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