ISSN 1000-3665 CN 11-2202/P
    杜国梁, 杨志华, 袁颖, 任三绍, 任涛. 基于逻辑回归–信息量的川藏交通廊道滑坡易发性评价[J]. 水文地质工程地质, 2021, 48(5): 102-111. DOI: 10.16030/j.cnki.issn.1000-3665.202104009
    引用本文: 杜国梁, 杨志华, 袁颖, 任三绍, 任涛. 基于逻辑回归–信息量的川藏交通廊道滑坡易发性评价[J]. 水文地质工程地质, 2021, 48(5): 102-111. DOI: 10.16030/j.cnki.issn.1000-3665.202104009
    DU Guoliang, YANG Zhihua, YUAN Ying, REN Sanshao, REN Tao. Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression- information value method[J]. Hydrogeology & Engineering Geology, 2021, 48(5): 102-111. DOI: 10.16030/j.cnki.issn.1000-3665.202104009
    Citation: DU Guoliang, YANG Zhihua, YUAN Ying, REN Sanshao, REN Tao. Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression- information value method[J]. Hydrogeology & Engineering Geology, 2021, 48(5): 102-111. DOI: 10.16030/j.cnki.issn.1000-3665.202104009

    基于逻辑回归–信息量的川藏交通廊道滑坡易发性评价

    Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression- information value method

    • 摘要: 川藏交通廊道位于青藏高原中东部,是世界上隆升和地貌演化最快的区域之一。在内外动力耦合作用下,区内滑坡灾害极其发育,严重制约着公路、铁路和水电工程的规划建设。在区域地质资料收集和整理的基础上,选取岩性、坡度、坡向、坡形、地形起伏度、地形粗糙度、断裂密度和河流距离8个因素为评价因子,结合传统信息量和逻辑回归模型的优势,采用逻辑回归–信息量模型对研究区滑坡进行易发性评价。通过对评价因子的多重共线性和显著性检验,得到评价因子不存在多重共线性且均对滑坡发生具有显著影响。采用ROC曲线对评价结果进行检验,其AUC值为0.81,表明评价模型能很好地预测滑坡的发生。易发性评价结果表明:研究区高易发区主要集中龙门山断裂带、金沙江断裂带、澜沧江断裂带、怒江断裂带、边坝–洛隆断裂带等大型活动断裂带控制区,以及区内坡度陡峭、地形起伏度大的大型河流深切河谷的两岸;中易发区在区内分布广泛,主要分布在岸坡较陡、地形起伏度中等的大型河流支流的两岸。研究结果有利于加深对川藏交通廊道滑坡发育分布的认识,也可为研究区的工程规划建设和防灾减灾提供科学依据。

       

      Abstract: Located in east-central Qinghai-Tibet Plateau, the Sichuan-Tibet traffic corridor is one of fastest uplifting and geomorphic evolution regions on the earth. Under the coupling of internal and external dynamics, the landslide in this region is extremely developed, which seriously restricts the planning and construction of highways, railways and hydropower projects. Based on the data collection and analysis of regional geological data, this paper selects lithology, slope gradient, aspect, slope shape, topographic relief, terrain roughness, fault density and distance to rivers as contributing factors. Combined the advantages of traditional information value method and logistic regression, this paper uses the logistic regression-information value method to evaluate the landslide susceptibility of the study area. Through the multi-collinearity test and significance test of the contributing factors, it is found that the selected contributing factors have no multi-collinearity and have a significant impact on the occurrence of landslides. ROC curve is used to test the results of landslide susceptibility, and the AUC value is 0.81, which shows that the model can well predict the occurrence of landslides. The results show that the high risk areas in the study area mainly occur in the regions of the Longmenshan fault zone, Jinshajiang fault zone, Lancangjiang fault zone, Nujiang fault zone and Bianba-Luolong fault zone, as well as on the sides of deep valleys of large rivers with steep slope and large topographic relief. The middle risk areas widely exist on both sides of the tributaries of large rivers. The results are helpful in understanding the development and distribution of landslides in the Sichuan-Tibet traffic corridor, and also provide a scientific basis for the project planning and construction, disaster prevention and mitigation in the study area.

       

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