SPATIAL DISTRIBUTION AND SUSCEPTIBILITY EVALUATION OF LANDSLIDE DISASTERS IN LOESS PLATEAU BASED ON INFORMATION-CNN COUPLING MODEL: A Case Study of Jiyuan City in Henan Province
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摘要:
通过野外调查和资料收集, 选择地形地貌、基础地质、气象水文、人类活动、岩土体性质以及植被覆盖共计18个影响因子, 基于信息量模型和卷积神经网络模型构建耦合模型对河南省济源市开展滑坡易发性评价研究, 利用GIS空间分析量化了滑坡空间分布特征. 结果表明, 研究区滑坡灾害整体呈聚集分布, 具有多个核密度高值中心; 滑坡极低、低、中、高和极高易发性区面积占比分别为45.04%、34.58%、8.67%、9.12%和2.57%. 极高和高易发区主要特征为断层发育、地质环境脆弱以及水力侵蚀. 中易发区滑坡密度最高, 为0.804个/km2. ROC曲线和AUC值表明评价结果准确性较好, 耦合模型预测能力具有可靠性. 滑坡影响因子敏感度分析前五位分别为距道路距离、距断层距离、坡向、地形粗糙度以及侵蚀程度和类型. 本研究可为黄土高原城镇滑坡地质灾害的预测和防治工作提供科学依据.
Abstract:Through field survey and data collection, 18 influencing factors involving landform, geology, hydrometeorology, human activities, rock-soil mass properties and vegetation coverage are selected to evaluate the landslide vulnerability in Jiyuan City of Henan Province on the basis of information-convolutional neural network (CNN) coupling model, with GIS spatial analysis to quantify the spatial distribution characteristics of landslide. The results show that the landslide disasters are distributed aggregately in the area, with multiple high value centers of kernel density. The areas with very low, low, medium, high and very high landslide susceptibility account for 45.04%, 34.58%, 8.67%, 9.12% and 2.57%, respectively. The very high and high susceptible areas are characterized by developed faults, fragile geological environment and hydraulic erosion. The highest landslide density is 0.804 per km2, occurring in medium susceptible area. The ROC curve and AUC value indicate that the evaluation results have good accuracy, and the prediction ability of the coupling model is reliable. The top 5 influencing factors of landslide susceptibility analysis are distance from roads, distance from faults, slope aspect, terrain roughness, as well as erosion degree and type. This study may provide scientific basis for the prediction and prevention of landslide geological disasters in cities and towns on the Loess Plateau.
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表 1 滑坡易发性影响因子数据源信息
Table 1. Impact factor data sources of landslide susceptibility
类型 影响因子 数据来源 数据类型 分辨率/m 地形地貌 高程 基于SAGA 7.0软件和ASTER 30 m-DEM计算和提取 连续型 30 坡度 连续型 30 坡向 连续型 30 曲率 连续型 30 地形粗糙度 连续型 30 地形起伏度 连续型 30 地表切割度 连续型 30 地形位置指数（TPI） 连续型 30 基础地质 距断层距离 中国国家地质资料数据中心 连续型 500 风化层厚度 美国NASA DACC 连续型 1000 侵蚀类型 中华人民共和国行业标准SL190—96《土壤侵蚀分类分级标准》 离散型 1000 气象水文 距河流距离 中国1∶ 400万主要基础数据集 连续型 500 地形湿度指数（TWI） 基于SAGA 7.0软件和ASTER 30 m-DEM计算和提取 连续型 30 降水量 中国气象数据网 连续型 1000 岩土体性质 黏粒含量 Predictive Soil Mapping with R 连续型 1000 人类活动 距道路距离 中国1∶ 400万主要基础数据集 连续型 500 人口密度 美国NASA SEDAC 连续型 1000 植被覆盖 归一化植被指数（NDVI） Landsat-8遥感影像 连续型 1000 
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表 2 信息量－积卷神经网络模型滑坡易发性分区结果
Table 2. Landslide susceptibility zonation based on information-CNN coupling model
易发性分区 区域面积/
km2面积占比/
%滑坡数量/
个滑坡数量占比/
%滑坡密度/
（个/km2）极低易发区 969.29 45.04 139 34.41 0.143 低易发区 744.166 34.58 62 15.34 0.083 中易发区 186.654 8.67 150 37.13 0.804 高易发区 196.386 9.12 25 6.93 0.127 极高易发区 55.426 2.57 28 6.18 0.505
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表 3 滑坡易发性影响因子共线性分析
Table 3. Collinearity analysis of landslide susceptibility influencing factors
影响因子 方差膨胀系数（TOL） 容忍度（VIF） 影响因子 方差膨胀系数（TOL） 容忍度（VIF） 高程 0.112 8.896 侵蚀类型 0.249 4.015 坡度 0.126 8.176 风化层厚度 0.284 3.523 坡向 0.463 2.160. NDVI 0.265 3.778 曲率 0.404 2.474 距断层距离 0.150 6.665 地表粗糙度 0.837 5.785 距河流距离 0.186 5.379 地表起伏度 0.479 2.653 距道路距离 0.830 1.885 地形切割度 0.229 4.234 降水量 0.158 6.342 TPI 0.172 5.829 人口密度 0.214 4.681 TWI 0.331 3.025 黏粒含量 0.460 2.174
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