Assessment of landslide susceptibility in southeast Xizang Region based on multiple models
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摘要:
藏东南地区地质环境复杂、灾害频发，滑坡给区内工程建设和人财安全造成较大威胁。为选出藏东南地区区域滑坡预测精度较高的模型，文章通过实地调研修正滑坡点数据，结合地形地貌因子、地质因子、地表覆盖因子和诱发因子并通过主成分分析法进行因子筛选，采用频率比模型、BP神经网络模型以及两种模型耦合来进行藏东南地区区域滑坡预测，最后用ROC曲线来检验模型精度。结果表明：经过因子筛选后的频率比模型对藏东南地区预测精度最高（AUC=0.889），通过主成分分析剔除因子的模型精度高于未剔除因子模型精度且藏东南地区滑坡主要沿水系分布，多分布在雅鲁藏布江、达曲、藏曲、怒江、澜沧江、伟曲、詹曲和扎曲两侧。利用所得模型对研究区灾害进行预测，得出滑坡点均处于高易发区及易发区内，研究得出的模型可为藏东南地区工程建设提供技术参考。
Abstract:The geological environment in southeast Xizang is complicated and disasters occur frequently. Landslides pose a great threat to engineering construction and human and financial safety in the region. In order to select models with higher precision for regional landslide prediction in southeast Xizang, this paper used modified landslide point data through field investigation, combined with topographic and geomorphic factors, geological factors, land cover factors and induced factors, and screened the factors through principal component analysis. Frequency ratio models, BP neural network models, and a combination of the two models were used for regional landslides prediction in southeast Xizang. Finally, ROC curves were used to evaluate the model accuracy. The results showed that the frequency ratio model after factor selection had the highest prediction accuracy for southeast Xizang (AUC=0.889). Models with factors removed through principal component analysis had higher accuracy than those without removal, and landslides in southeast Xizang were mainly distributed along river systems, including the Yarlung Zangbo River, Daqu River, Zangqu River, Nujiang River, Lancang River, Weiqu River, Janqu River and Zhaqu River. The models were used to predict the disaster in the study area, revealing that landslide points were located in high susceptibility and susceptibility zones. The models developed in this study can provide technical reference for engineering construction in southeast Xizang.
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Key words:
- geological hazards /
- landslide /
- frequency ratio /
- BP neural networks /
- southeast Xizang
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表 1 数据来源
Table 1. Summary table of data sources
一级因子 二级因子 数据来源 类型 精度 地形因子 坡度 国家地理空间数据云（ www.gscloud.cn ）
国家地质资料数据中心（www.ngac.org.cn ）栅格 30 m 坡向 栅格 30 m 高程 栅格 30 m 地形起伏度 栅格 30 m 地质因子 地层岩性 GLi M 全球岩性数据集 栅格 30 m 地表覆盖因子 距河流距离 1∶100万全国基础地理信息数据 矢量 1∶50 000 距道路距离 矢量 1∶50 000 土地利用率 中国科学院资源环境科学与技术中心 矢量 1∶50 000 诱发因子 降雨量 栅格 30 m 
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表 2 因子相关性分析
Table 2. Factor correlation analysis
坡度 坡向 高程 地形起伏度 距河流距离 距道路距离 土地利用 降雨量 地层岩性 坡度 1 坡向 0.062 1 高程 −0.072 −0.016 1 地形起伏度 0.679** 0.077* −0.167** 1 距河流距离 −0.07 0 0.413** −0.073 1 距道路距离 0.053 0.047 −0.049 0.198** 0.162** 1 土地利用 0.007 0.026 0.073 0.053 0.057 0.186** 1 降雨量 0.149** 0.155** −0.547** 0.259** −0.228** 0.195** 0.008 1 地层岩性 0.110** 0.067 −0.353** 0.157** −0.144** 0.098* 0.051 0.295** 1 注：**在0.01级别（双尾），相关性显著；*在0.05级别（单尾），相关性显著。
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表 3 主成分分析矩阵
Table 3. Principal component analysis matrix
成分 1 2 3 高程 −0.855 降雨量 0.748 距河流距离 −0.601 地层岩性 0.585 坡度 0.923 地形起伏度 0.890 距道路距离 0.768 土地利用 0.621 坡向
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表 4 重大滑坡事件易发性预测
Table 4. Prediction of susceptibility for major landslide events
灾害名称 地理位置 预测易发性 贡龙滑坡 昌都市察雅县 易发区 易贡电站滑坡 林芝市波密县 易发区 达木乡滑坡 林芝市墨脱县 高易发区 通易公路滑坡 林芝市波密县 高易发去 塔林村 林芝市察隅县 易发区
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