Xi'an Center, China Geological SurveyHost
Advanced Search
Previous Article Next Article
2021 Vol. 54, No. 2
Article Contents
Article navigation > Northwestern Geology > 2021 > 54(2): 259-272
Next Article Previous Article

WANG Gaofeng, GUO Ning, DENG Bing, TIAN Yuntao, YE Zhennan, CHEN Zongliang, LÜ Fenglan, GAO Youlong. 2021. Analysis of Landslide Susceptibility and Accuracy in Different Combination Models. Northwestern Geology, 54(2): 259-272. doi: 10.19751/j.cnki.61-1149/p.2021.02.023
Citation: WANG Gaofeng, GUO Ning, DENG Bing, TIAN Yuntao, YE Zhennan, CHEN Zongliang, LÜ Fenglan, GAO Youlong. 2021. Analysis of Landslide Susceptibility and Accuracy in Different Combination Models. Northwestern Geology, 54(2): 259-272. doi: 10.19751/j.cnki.61-1149/p.2021.02.023
shu

Analysis of Landslide Susceptibility and Accuracy in Different Combination Models

  • 1. Hydrogeological Environmental Center of ChinaGeological Survey, China Geology Survey, Baoding 071051, Hebei, China;

  • 2. Natural Resources Three Gorges Reservoir Area Geological Disaster Monitoring and Early Warning Field Science Observation Base, Chongqing 404100, China;

  • 3. China University of Geosciences, Wuhan 430074, Hubei, China

More Information
Received Date:  10 June 2020
Revised Date:  31 August 2020
    Abstract
  • This paper carried out the studies in Bailong river basin,where landslide incidences frequently occurred, to explore the applicability and the rationality of the landslide susceptibility evaluation model.Six indicators of slope, top ographic relief, distance from fault, stratum lithology, watershed gully density and vegetation normalization index were selected assusceptibility evaluation indication. The authors took 2 093 landslide disaster points in the study area as sample data and determined the factor classification status by using the information value, deterministic coefficient value and the mutation law of evidence weight value curve, combined with the frequency ratio curve of the landslide area and the graded area as the criticality of the grading division value. Based on the state grade of each index and correlation analysis, three combination models with logistic regression, of information value method, deterministic coefficient method and evidence weight method were used to evaluate the susceptibility of regional landslide hazard.The three combination models were compared and discussed from the aspects of the results, the applicability and the accuracy.Results show that in the evaluation of regional landslide susceptibility, all the three models are ideal. The prediction accuracy of the combination model of information value method with logistic regressionis better than the other two combination models, with a prediction accuracy of94.6%. The results provide reference for geological disaster prevention and land use in this area.
    • FullText(HTML)
  • 加载中
    • References
  • 张俊, 殷坤龙, 王佳佳, 等.三峡库区万州区滑坡灾害易发性评价研究[J].岩石力学与工程报, 2016,35(2):284-296.

    Google Scholar

    ZHANG Jun,YIN Kunlong, WANG JiaJia, et al. Evaluation of landslide susceptibity forWanzhou district of Three Gorges reservoir[J]. Chinese Journal of Rock Mechanics and Engineering, 2016, 35(2):284-296.

    Google Scholar

    许冲, 戴福初, 姚鑫, 等.基于GIS与确定性系数分析方法的汶川地震滑坡易发性评价[J]. 工程地质学报, 2010,18(1):15-26.

    Google Scholar

    XU Chong, DAI Fuchu, YAO Xin, et al. Gis platform and certainty factor analysis method based Wenchuan earthquake-induced landslide susceptibility evaluation[J]. Journal of Engineering Geology, 2010,18(1):15-26.

    Google Scholar

    唐亚明, 张茂省, 李林, 等.滑坡易发性危险性风险评价例析[J]. 水文地质工程地质, 2011,38(2):125-129.

    Google Scholar

    TANG Yaming,ZHANG Maosheng, LI Lin, et al. Discrimination to the landslide susceptibility,hazard and risk assessment[J]. Hydrogeology & Engineering Geology, 2011,38(2):125-129.

    Google Scholar

    张茂省,薛强,贾俊, 等.山区城镇地质灾害调查与风险评价方法及实践[J]. 西北地质, 2019,52(2):125-135.

    Google Scholar

    ZHANG Maosheng, XUE Qiang, JIA Jun, et al. Methods and practices for the investigation and risk assessment of Ge0-hazards in Mountainous towns[J]. Northwestern Geology, 2019,52(2):125-135.

    Google Scholar

    张帆宇, 刘高, 谌文武, 等.基于多变量统计分析的大型滑坡敏感性评价:以汶川地震影响的陇南地区为例[J]. 中南大学学报(自然科学版), 2012. 43(9):3595-3600.

    Google Scholar

    ZHANG Fanyu, LIU Gao, CHEN Wenwu, et al. Large landslide susceptibility assessment by multivariate statistical analysis in the Longnan area affected by the Wenchuan earthquake[J]. Journal of Central South University(Science and Technology), 2012. 43(9):3595-3600.

    Google Scholar

    陈冠, 孟兴民, 乔良, 等. "7.22"岷县漳县地震地质灾害分布、特征及与影响因子关系分析[J]. 工程地质学报, 2013,21(5):750-760.

    Google Scholar

    CHEN Guan, MENG Xingmin, QIAO Lang, et al. Distribution,characteristics,and associated influencial factors of the geohazards induced by Minxian-Zhangxian earthquake on 22 July,2013,Gansu,China[J]. Journal of Engineering Geology, 2013,21(5):750-760.

    Google Scholar

    齐识, 张雅莉, 张鹏, 等.白龙江流域滑坡危险性评价指标体系的构建[J]. 长江科学院院报, 2014,31(1):23-28.

    Google Scholar

    QI Si, ZHANG Yali, ZHANG Peng, et al. An assessment index system for landslide risk in Bailong River basin[J]. Journal of Yangtze River Scientific Research Institute, 2014,31(1):23-28.

    Google Scholar

    王高峰, 叶振南, 李刚, 等.白龙江流域舟曲县城区地质灾害危险性评价[J]. 灾害学, 2019,34(3):128-133.

    Google Scholar

    WANG Gaofeng,YE Zhennan, LI Gang, et al. Geological hazard risk assessment of Zhouqu county in Bailong river basin[J]. Journal of Catastrophology, 2019,34(3):128-133.

    Google Scholar

    沈玲玲, 刘连友, 许冲, 等.基于多模型的滑坡易发性评价-以甘肃岷县地震滑坡为例[J]. 工程地质学报, 2016,24(1):19-28.

    Google Scholar

    SHEN Lingling, LIU Lianyou, XU Chong, et al. Multi-model based landslide susceptibility evaluation-illustrated with landslides triggered by Minxian earthquake[J]. Journal of Engineering Geology, 2016,24(1):19-28.

    Google Scholar

    范强, 巨能攀, 向喜琼, 等.证据权法在区域滑坡危险性评价中的应用-以贵州省为例[J]. 工程地质学报, 2014,22(3):474-481.

    Google Scholar

    FAN Qiang, JU Nengpan, XIANG Xiqiong, et al. Landslides hazareds assessment with weights of evidence-A case study in Guizhou,China[J]. Journal of Engineering Geology, 2014,22(3):474-481.

    Google Scholar

    樊芷吟, 苟晓峰, 秦明月, 等.基于信息量模型与Logistic回归模型耦合的地质灾害易发性评价[J]. 工程地质学报, 2018,26(2):340-347.

    Google Scholar

    FNA Zhiyin, GOU Xaiofeng, QIN Mingyue, et al. Information and logistic regression models based coupling analysis for susceptibility of geological hazards[J]. Journal of Engineering Geology, 2018,26(2):340-347.

    Google Scholar

    田春山, 刘希林, 汪佳.基于CF和Logistic回归模型的广东省地质灾害易发性评价[J]. 水文地质工程地质, 2016,43(6):154-170.

    Google Scholar

    TIAN Chunshan,LIU Xilin, WANG Jia. Geohazard susceptility assessment based on CF model and Logistic regression models in Guangdong[J]. Hydrogeology & Engineering Geology, 2016,43(6):154-170.

    Google Scholar

    杨光, 徐佩华, 曹琛, 等.基于确定性系数组合模型的区域滑坡敏感性评价[J]. 工程地质学报, 2019,27(5):1153-1163.

    Google Scholar

    YANG Guang, XU Peihua, CAO Chen, et al. Assessment of reglonal landslide susceptibility based on combined model of certalnty factor method[J]. Journal of Engineering Geology, 2019,27(5):1153-1163.

    Google Scholar

    冯杭建, 周爱国, 俞剑君, 等.浙西梅雨滑坡易发性评价模型对比[J]. 地球科学, 2016, 41(3):403-415.

    Google Scholar

    FENG Hangjian,ZHOU Aiguo,YU Jianjun, et al. A comparative study on plum-rain-triggered landslide susceptibility assessment models in West Zhejiang Province[J]. Earth Science, 2016, 41(3):403-415.

    Google Scholar

    刘坚, 李树林, 陈涛.基于优化随机森林模型的滑坡易发性评价[J]. 武汉大学学报·信息科学版, 2018,43(7):1085-1091.

    Google Scholar

    LIU Jian, LI Shulin, CHEN Tao. Landslide susceptibility assessment based on optimized random forest model[J]. Geomatics and Information Science of Wuhan University, 2018,43(7):1085-1091.

    Google Scholar

    张茂省, 贾俊,王毅,等.基于人工智能(AI)的地质灾害防控体系建设[J]. 西北地质, 2019,52(2):103-116.

    Google Scholar

    ZHANG Maosheng, JIA Jun, WANG Yi, et al. Construction of geological disaster prevention and control system based on AI[J]. Northwestern Geology, 2019,52(2):103-116.

    Google Scholar

    邱海军, 曹明明, 刘闻, 等.基于三种不同模型的区域滑坡灾害敏感性评价及结果检验研究[J]. 地理科学, 2014,34(1):110-115.

    Google Scholar

    QIU Haijun CAO Mingming, LIU Wen, et al. The susceptility assessment of landslide and its calibration of the models based on three different models[J]. Scientia Geographica Sinica, 2014,34(1):110-115.

    Google Scholar

    张晓东, 刘湘南, 赵志鹏, 等.信息量模型、确定性系数模型与逻辑回归模型组合评价地质灾害敏感性的对比研究[J]. 现代地质, 2018,32(3):602-610.

    Google Scholar

    ZHANG Xiaodong,LIU Xiangnan, ZHAO Zhipeng, et al. Comparative study of geological hazards susceptibity assessment:Constraints from the information Value+Logistic regressionmodel and the CF+Logistic regression model[J]. Geoscience, 2018,32(3):602-610.

    Google Scholar

    王高峰, 杨强, 田运涛, 等.泥石流易发性评价模型的构建-以白龙江流域石门乡羊汤河段为例[J]. 干旱区研究, 2019,36(3):761-770.

    Google Scholar

    WANG Gaofeng,YANG Qiang, TIAN Yuntao, et al. Establishment of assessment model for debris flow susceptibility:a case study from Shimen township to Yangtang river in the Bailong River Basin[J]. Arid Zone Research, 2019,36(3):761-770.

    Google Scholar

    吴常润,赵冬梅,刘澄静, 等.基于GIS和信息量模型的陇川县滑坡易发性评价[J]. 西北地质, 2020,53(2):308-320.

    Google Scholar

    WU Changrun, ZHAO Dongmei,LIU Dengjing, et al. Landslide susceptibility assessment of Longchuan County based on GIS and information value model[J]. Northwestern Geology, 2020,53(2):308-320.

    Google Scholar

    邱维蓉,吴帮玉,潘学树, 等.几种聚类优化的机器学习方法在灵台县滑坡易发性评价中的应用[J]. 西北地质, 2020,53(1):222-233.

    Google Scholar

    QIU Weirong, WU Bangyu,PAN Xueshu, et al. Application of several cluster-optimization-based machine learning methods in evaluation of landslide susceptibility in Lingtai county[J]. Northwestern Geology, 2020,53(1):222-233.

    Google Scholar

    孟兴民, 陈冠, 郭鹏, 等.白龙江流域滑坡泥石流灾害研究进展与展望[J].海洋地质与第四纪地质, 2013, 33(4):1-15.

    Google Scholar

    MENG Xingmin, CHEN Guan, GUO Peng, et al. Research of landslides ans debris flow in Bailong river basin:progress and prospect[J]. Marine Geology & Quaternary Geology, 2013, 33(4):1-15.

    Google Scholar

    杨为民, 黄晓, 张春山, 等.白龙江流域坪定-化马断裂带滑坡特征及其形成演化[J].吉林大学学报(地球科学版),2014,44 (2):574-583.

    Google Scholar

    YANG Weimin, HUANG Xiao, ZHANG Chunshan,et al. Deformation behavior of landslides and their formation mechanism along Pingding-Huama active fault in Bailongjiang River Region[J]. Journal of Jilin University(Earth Science Edition), 2014,44 (2):574-583.

    Google Scholar

    李淑贞, 戴霜, 王华伟, 等.白龙江地区断裂构造与滑坡分布及发生关系[J].兰州大学学报(自然科学版),2015,51 (2):145-152.

    Google Scholar

    LI Shuzhen, DAI Shuang, WANG Huawei, et al. Fault features and their implication on distribution and formation of landslides in Bailongjiang Region[J]. Journal of Langzhou University, 2015,51 (2):145-152.

    Google Scholar

    陈明, 王运生, 梁瑞锋, 等. 白龙江流域大型滑坡发育分布规律研究[J]. 工程地质学报, 2018,26(2):325-333.

    Google Scholar

    CHEN Ming, WANG Yunsheng, LIANG Ruifeng, et al. Research on development and distribution rules of largescale landslides in Bailongjiang riber basin[J]. Journal of Engineering Geology, 2018,26(2):325-333.

    Google Scholar

    Sridevi Jadi.斜坡不稳定性分类的统计模型[J].世界地质, 1997,16(1):83-88.

    Google Scholar

    Sridevi Jadi.Statistical model of slope instability classification[J]. World Geology, 1997,16(1):83-88.

    Google Scholar

    Cohen J.Weighted Kappa:nominal scale agreement with provision for scaled disagreement or partial credit[J].Psychological Bulletin,1968,70(4):213-220.

    Google Scholar

    • Relative Articles
  • Cited by
  • Supplements
    • Proportional views
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Export Citation
PDF
XML

Article Metrics

Article views(2117) PDF downloads(74) Cited by(0)

Access History

Other Articles By Authors

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    版权所有：中国地质调查局发展研究中心 copyright @2020