Evaluation of geological hazard susceptibility of collapse and landslide in Yuanyang County using slope units and random forest modeling
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摘要:
针对基于栅格单元与定性定量方法模型在地质灾害易发性评价中存在模型预测精度低且使用较为频繁的不足与弊端，采用斜坡单元与机器学习方法之一的随机森林模型相结合开展元阳县崩滑地质灾害易发性评价。在ArcGIS中，利用曲率分水岭法划分出7851个斜坡单元。经过大量统计研究与地质环境条件分析，选取工程地质岩组、地貌类型、高程、坡度、坡向、曲率、起伏度、河流距离、断层距离等9个因子作为评价指标，并通过SPSS软件，将9个评价指标与灾点发育特征的关系进行数据分析，得出各评价指标权重。在SPSS中，采用随机森林模型，建立易发性评价模型，将元阳县崩滑地质灾害易发性划分为低、中、高、极高4类，所占面积分别为410.06 km2、470.21 km2、550.02 km2和776.87 km2，分别占元阳县面积的18.58%、21.30%、24.92%和35.20%。经与详查结果对比，评价结果与实际高度吻合。利用ROC曲线得出区划结果精度AUC值为92.7%，区划结果相当好。研究显示，元阳县中部和西南两个部分地质灾害集中，易发性极高。
Abstract:The model based on grid unit and qualitative and quantitative method has the disadvantages of low prediction accuracy and frequent use in the evaluation of geological hazard susceptibility, was utilized to evaluate the potential for collapse and landslide in Yuanyang County. Using ArcGIS, 7851 slope units were divided via the curvature watershed method. Through a large number of statistical study and analysis of geological environment condition, nine evaluation factors were selected, including engineering geological petrofabric, landform type, elevation, gradient, slope direction, curvature, ups and downs, rivers, distance and fault distance. These factors were analyzed and their weights determined using SPSS software, in conjunction with data on the development characteristics of disaster points. The random forest model was then applied to establish a vulnerability evaluation model, which categorized landslide geological disaster in Yuanyang County into four types: low, medium, high and extremely high, occupying an area of 410.06 km2, 470.21 km2, 550.02 km2 and 776.87 km2 respectively. These areas correspond to 18.58%, 21.30%, 24.92% and 35.20% of Yuanyang County’s total area. The evaluation results were compared with the detailed investigation results and were found to be highly consistent. The accuracy of ROC curve was calculated at 92.7%, indicating a high level of accuracy. The central and southwest parts of Yuanyang County were found to be highly susceptible to geological disasters.
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表 1 随机森林模型参数
Table 1. Summary table of Random forest model parameters
参数名 参数值 训练用时/s 0.156 数据切分 0.7 数据洗牌 是 交叉验证 否 节点分裂评价准则 gini 决策树数量 100 有放回采样 TRUE 袋外数据测试 FALSE 划分时考虑的最大特征比例 auto 内部节点分裂的最小样本数 2 叶子节点的最小样本数 1 叶子节点中样本的最小权重 0 树的最大深度 10 叶子节点的最大数量 50 节点划分不纯度的阈值 0 
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表 2 数据集精确率
Table 2. Summary table of dataset accuracy
准确率 召回率 精确率 F1 训练集 0.920 0.920 0.926 0.920 测试集 0.705 0.705 0.705 0.704 注：F1为精确率和召回率的调和平均。
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表 3 易发性分级数据统计
Table 3. Sueceptibility classification data statistics
易发性等级 灾点数 比重/% 区间面积/km2 比重/% 低 19 7.34 410.06 18.58 中 21 8.11 470.21 21.30 高 77 29.73 550.02 24.92 极高 142 54.83 776.87 35.20
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表 4 评价结果对比表
Table 4. Comparison table of evaluation results
结果来源 易发性等级 灾点数 比重/% 区间面积/km2 比重/% 本文评价结果 低 19 7.34 410.06 18.58 中 21 8.11 470.21 21.30 高 77 29.73 550.02 24.92 极高 142 54.83 776.87 35.20 详查评价结果 低 0 0.00 369.70 16.75 中 19 7.34 511.18 23.16 高 80 30.89 591.30 26.79 极高 157 60.62 734.98 33.30
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LIU Lei, YIN Kunlong, ZHANG Jun. Estimation method of the quaternary deposits thickness and its application in Wanzhou central district, Three Gorges Reservoir region[J]. Geological Science and Technology Information, 2016, 35（1）: 177-183. （in Chinese with English abstract）
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