Comparison of Landslide Susceptibility Evaluation by Deep Random Forest and Random Forest Model: A Case Study of Lueyang County, Hanzhong City
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摘要:
针对浅层的机器学习模型泛化能力低而导致其滑坡易发性评价模型预测精度不高的问题，笔者围绕陕西省汉中市略阳县城中心为研究区，采用深度随机森林构建区域地灾易发性评价模型来提升预测精度。依据略阳县滑坡成灾机理研究成果，选取坡度、相对高差、坡向、坡型、工程地质岩组、断裂距离、水系距离、公路铁路距离、植被覆盖等9个因子作为易发性评价指标；将研究区栅格单元按5 m × 5 m进行划分并提取评价因子值，输入深度随机森林评价模型，从而获得研究区易发性评价图。依据评价结果略阳县地质灾害可划分为极高易发区、高易发区、中易发区、低易发区4个等级，面积所占比例分别为5.31%、22.97%、42.11%、29.61%，其划分结果与研究区内地质灾害实际发育情况吻合，合理反映研究区地灾分布的总体特征。深度随机森林的地质灾害易发性预测模型在ROC曲线下面积值（AUC）为91.2%，高于随机森林预测模型的86.3%，表明该模型具有一定的合理性与可行性，可为区域滑坡易发性评价进一步提供新方法。
Abstract:To address the problem of low prediction accuracy of landslide susceptibility evaluation model due to the difficulty of knowledge reuse and generalization of shallow machine learning model, this paper takes Lueyang County, Hanzhong City, Shaanxi Province as the study area and uses deep random forest to build a regional geological disaster susceptibility evaluation model to improve the prediction accuracy. Firstly, based on the research results of landslide mechanism in Lueyang County, nine factors such as slope, relative height difference, slope direction, slope type, engineering geological rock group, fault distance, river system distance, road and railroad distance, and vegetation cover are selected as susceptibility evaluation indexes; secondly, the study area is divided into 5 m × 5 m raster cells and the values of evaluation factors are extracted and input into the depth random forest evaluation model; finally, the susceptibility evaluation map of the study area is obtained. Based on the evaluation results, geological hazards in Lueyang County can be classified into four levels: very high susceptibility, high susceptibility, medium susceptibility, and low susceptibility, with the proportion of area being 5.31%, 22.97%, 42.11%, and 29.61%. The classification results are consistent with the actual development of geological hazards and reasonably reflect the overall characteristics of geological hazard distribution in the study area. In addition, the area under the ROC curve of the geological hazard susceptibility prediction model of deep random forest is 91.2%, which is higher than 86.3% of the random forest prediction model, indicating that the model is reasonable and feasible, and can provide new ideas for the evaluation of regional landslide susceptibility.
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Keywords:
- landslide /
- Lueyang County /
- susceptibility evaluation /
- Deep Random Forest Model
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图 2 研究区灾害示意图
a. 略阳县谢家坪村阴坡里滑坡；b. 略阳县碾子湾村何硖路旁崩塌
Figure 2. Hazard photographs of researching area
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图 3 深度随机森林模型流程结构（据Zhou， 2017）
Figure 3. Process structure illustration of Deep Random Forest Model
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图 4 滑坡与单评价因子分类图
Figure 4. The landslides division and evaluation factors classification
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图 5 略阳县随机森林滑坡易发性评价图
Figure 5. Landslide susceptibility assessment map of Lueyang County base on Random Forest Model
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图 6 略阳县深度随机森林滑坡易发性评价图
Figure 6. Landslide susceptibility assessment map of Lueyang County base on Deep Random Forest Model
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图 7 深度随机森林与随机森林易发性评价ROC曲线对比图
Figure 7. DRF and RF Mode ROC Curve Comparison on Landslide susceptibility assessment
表 1 各评价因子信息量表
Table 1 Weighted information values of individual evaluation factors
因子 分级 Si（km2） Ni（个） Ii 坡度 ＜10° 10.535625 8 −0.085244 10°～20° 13.3961 21 0.639636 20°～30° 35.77955 46 0.441342 30°～40° 54.226925 38 −0.165514 40°～50° 38.6219 12 −0.978836 ＞50° 13.119575 12 0.100879 相对高差 16～175 m 24.930925 53 0.944260 175～238 m 55.38815 46 0.004353 238～300 m 49.224425 29 −0.339017 300～379 m 26.43665 8 −1.005232 379～605 m 9.6986 1 −2.081904 坡向 0～45° 23.746850 21 0.067150 45°～90° 21.137625 23 0.274517 90°～135° 17.924900 10 −0.393528 135°～180° 18.869250 14 −0.108399 180°～225° 20.641625 26 0.420864 225°～275° 22.018400 18 −0.011429 275°～315° 20.152475 13 −0.248300 315°～360° 21.185550 12 −0.378335 曲率 ＜−0.5（凹形坡） 11.1099 12 0.267147 −0.5～0.5
（直线形坡）143.597 119 0.002190 ＞0.5（凸形坡） 10.969775 6 −0.413307 工程地质岩组 坚硬岩组 65.882425 40 −0.308915 半坚硬岩组 29.980725 13 −0.645528 软硬相间岩组 58.766425 46 −0.054852 松散岩组 11.050425 39 1.451170 距断裂距离 ＜100 m 31.79 26 −0.010915 100～200 m 25.87 26 0.195167 200～500 m 49.79 53 0.252595 500～1000 m 34.60 23 −0.218224 ＞1000 m 23.64 9 −0.775554 距河流水系
距离＜200 m 69.69 86 0.400425 200～400 m 52.38 31 −0.334384 400～600 m 27.98 17 −0.308056 600～800 m 11.37 1 −2.240549 ＞800 m 4.28 2 −0.569794 距公路、铁路
距离＜100 m 18.99 58 1.306584 100～500 m 46.12 41 0.072488 500～1000 m 38.06 14 −0.809915 1000～1500 m 26.29 11 −0.681226 ＞1500 m 36.23 13 −0.834794 NDVI −0.41～0.07 1.88 0 0.07～0.32 7.64 26 1.415100 0.32～0.52 26.25 56 0.947905 0.52～0.68 91.74 50 −0.416840 0.68～0.84 38.18 5 −1.842838 
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表 2 易发性等级划分与滑坡实际发生比率对比表
Table 2 Comparison of susceptibility classification and actual landslide occurrence rate
评价
方法易发性
等级a
易发分区面积占比（%）b
分区滑坡数量c
滑坡百分比（%）c/a
滑坡发生比率随机森林 低 16.34 1 0.73 0.04 中 69.21 74 54.01 0.78 高 11.24 40 29.20 2.60 极高 3.21 22 16.06 5.00 深度
随机森林低 29.61 7 5.11 0.17 中 42.11 41 29.93 0.71 高 22.97 62 45.26 1.97 极高 5.31 27 19.71 3.71
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