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

DU Guoliang; YANG Zhihua; YUAN Ying; REN Sanshao; REN Tao

doi:10.16030/j.cnki.issn.1000-3665.202104009

2021 Vol. 48, No. 5

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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

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

1.
School of urban geology and Engineering, Hebei GEO University, Shijiazhuang, Hebei　050031, China
2.
Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang , Hebei　050031, China
3.
Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing　100081, China
4.
Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang , Hebei　050061, China

Received Date: 03 April 2021

Revised Date: 18 May 2021

Publish Date: 15 September 2021

Abstract

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.
- Qinghai-Tibetan Plateau /
- Sichuan-Tibet traffic corridor /
- landslide /
- logistic regression-information value /
- landslide susceptibility

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References

[1]	彭建兵, 马润勇, 卢全中, 等. 青藏高原隆升的地质灾害效应[J]. 地球科学进展,2004,19(3):457 − 466. [PENG Jianbing, MA Runyong, LU Quanzhong, et al. Geological hazards effects of uplift of Qinghai-Tibet plateau[J]. Advance in Earth Sciences,2004,19(3):457 − 466. (in Chinese with English abstract) doi: 10.3321/j.issn:1001-8166.2004.03.018 CrossRef Google Scholar
[2]	彭建兵, 崔鹏, 庄建琦. 川藏铁路对工程地质提出的挑战[J]. 岩石力学与工程学报,2020,39(12):2377 − 2389. [PENG Jianbing, CUI Peng, ZHUANG Jianqi. Challenges to engineering geology of Sichuan-Tibet Railway[J]. Chinese Journal of Rock Mechanics and Engineering,2020,39(12):2377 − 2389. (in Chinese with English abstract) Google Scholar
[3]	张永双, 郭长宝, 姚鑫, 等. 青藏高原东缘活动断裂地质灾害效应研究[J]. 地球学报,2016,37(3):277 − 286. [ZHANG Yongshuang, GUO Changbao, YAO Xin, et al. Research on the geohazard effect of active fault on the eastern margin of the Tibetan Plateau[J]. Acta Geoscientica Sinica,2016,37(3):277 − 286. (in Chinese with English abstract) doi: 10.3975/cagsb.2016.03.03 CrossRef Google Scholar
[4]	李郎平, 兰恒星, 郭长宝, 等. 基于改进频率比法的川藏铁路沿线及邻区地质灾害易发性分区评价[J]. 现代地质,2017,31(5):911 − 929. [LI Langping, LAN Hengxing, GUO Changbao, et al. Geohazard susceptibility assessment along the Sichuan-Tibet Railway and its adjacent area using an improved frequency ratio method[J]. Geoscience,2017,31(5):911 − 929. (in Chinese with English abstract) doi: 10.3969/j.issn.1000-8527.2017.05.004 CrossRef Google Scholar
[5]	郭长宝, 吴瑞安, 蒋良文, 等. 川藏铁路雅安—林芝段典型地质灾害与工程地质问题[J]. 现代地质,2021,35(1):1 − 17. [GUO Changbao, WU Rui'an, JIANG Liangwen, et al. Typical geohazards and engineering geological problems along the Ya'an-Linzhi section of the Sichuan-Tibet Railway, China[J]. Geoscience,2021,35(1):1 − 17. (in Chinese with English abstract) Google Scholar
[6]	吴树仁, 石菊松, 张春山, 等. 地质灾害风险评估技术指南初论[J]. 地质通报,2009,28(8):995 − 1005. [WU Shuren, SHI Jusong, ZHANG Chunshan, et al. Preliminary discussion on technical guideline for geohazard risk assessment[J]. Geological Bulletin of China,2009,28(8):995 − 1005. (in Chinese with English abstract) doi: 10.3969/j.issn.1671-2552.2009.08.001 CrossRef Google Scholar
[7]	许冲, 戴福初, 姚鑫, 等. GIS支持下基于层次分析法的汶川地震区滑坡易发性评价[J]. 岩石力学与工程学报,2009,28(增刊2):3978 − 3985. [XU Chong, DAI Fuchu, YAO Xin, et al. GIS-based landslide susceptibility assessment using analytical hierarchy process in Wenchuan earthquake region[J]. Chinese Journal of Rock Mechanics and Engineering,2009,28(Sup2):3978 − 3985. (in Chinese with English abstract) Google Scholar
[8]	牛瑞卿, 彭令, 叶润青, 等. 基于粗糙集的支持向量机滑坡易发性评价[J]. 吉林大学学报(地球科学版),2012,42(2):430 − 439. [NIU Ruiqing, PENG Ling, YE Runqing, et al. Landslide susceptibility assessment based on rough sets and support vector machine[J]. Journal of Jilin University (Earth Science Edition),2012,42(2):430 − 439. (in Chinese with English abstract) Google Scholar
[9]	孙长明, 马润勇, 尚合欣, 等. 基于滑坡分类的西宁市滑坡易发性评价[J]. 水文地质工程地质,2020,47(3):173 − 181. [SUN Changming, MA Runyong, SHANG Hexin, et al. Landslide susceptibility assessment in Xining based on landslide classification[J]. Hydrogeology & Engineering Geology,2020,47(3):173 − 181. (in Chinese with English abstract) Google Scholar
[10]	OZDEMIR A, ALTURAL T. A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey[J]. Journal of Asian Earth Sciences,2013,64:180 − 197. doi: 10.1016/j.jseaes.2012.12.014 CrossRef Google Scholar
[11]	方然可, 刘艳辉, 苏永超, 等. 基于逻辑回归的四川青川县区域滑坡灾害预警模型[J]. 水文地质工程地质,2021,48(1):181 − 187. [FANG Ranke, LIU Yanhui, SU Yongchao, et al. A early warning model of regional landslide in Qingchuan County, Sichuan Province based on logistic regression[J]. Hydrogeology & Engineering Geology,2021,48(1):181 − 187. (in Chinese with English abstract) Google Scholar
[12]	UMAR Z, PRADHAN B, AHMAD A, et al. Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia[J]. CATENA,2014,118:124 − 135. doi: 10.1016/j.catena.2014.02.005 CrossRef Google Scholar
[13]	YAO X, THAM L G, DAI F C. Landslide susceptibility mapping based on Support Vector Machine: a case study on natural slopes of Hong Kong, China[J]. Geomorphology,2008,101(4):572 − 582. doi: 10.1016/j.geomorph.2008.02.011 CrossRef Google Scholar
[14]	杜国梁, 张永双, 吕文明, 等. 基于加权信息量模型的藏东南地区滑坡易发性评价[J]. 灾害学,2016,31(2):226 − 234. [DU Guoliang, ZHANG Yongshuang, LV Wenming, et al. Landslide susceptibility assessment based on weighted information value model in southeast Tibet[J]. Journal of Catastrophology,2016,31(2):226 − 234. (in Chinese with English abstract) doi: 10.3969/j.issn.1000-811X.2016.02.042 CrossRef Google Scholar
[15]	DU G L, ZHANG Y S, IQBAL J, et al. Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed, Gansu Province, China[J]. Journal of Mountain Science,2017,14(2):249 − 268. doi: 10.1007/s11629-016-4126-9 CrossRef Google Scholar
[16]	殷坤龙, 晏同珍. 汉江河谷旬阳段区域滑坡规律及斜坡不稳定性预测[J]. 地球科学,1987,12(6):631 − 638. [YIN Kunlong, YAN Tongzhen. Distribution regularity of landslides and prediction of slope instability nearby Xunyang, Han river valley[J]. Earth Science,1987,12(6):631 − 638. (in Chinese with English abstract) Google Scholar
[17]	DU G L, ZHANG Y S, YANG Z H, et al. Landslide susceptibility mapping in the region of eastern Himalayan syntaxis, Tibetan Plateau, China: a comparison between analytical hierarchy process information value and logistic regression-information value methods[J]. Bulletin of Engineering Geology and the Environment,2019,78(6):4201 − 4215. doi: 10.1007/s10064-018-1393-4 CrossRef Google Scholar
[18]	张玘恺, 凌斯祥, 李晓宁, 等. 九寨沟县滑坡灾害易发性快速评估模型对比研究[J]. 岩石力学与工程学报,2020,39(8):1595 − 1610. [ZHANG Qikai, LING Sixiang, LI Xiaoning, et al. Comparison of landslide susceptibility mapping rapid assessment models in Jiuzhaigou County, Sichuan Province, China[J]. Chinese Journal of Rock Mechanics and Engineering,2020,39(8):1595 − 1610. (in Chinese with English abstract) Google Scholar