三峡库区万州区滑坡灾害易发性评价研究

doi:10.13722/j.cnki.jrme.2015.0318

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摘要滑坡灾害易发性研究在滑坡灾害风险管理与城市规划等方面具有非常重要的现实意义。以往的研究中，鲜有对指标因子状态划分作有关深入分析和讨论的。鉴于此，以滑坡灾害频发的三峡库区万州区为研究对象：首先，选取影响滑坡发生的7个致灾因子(地层岩性、地质构造、水系分布、坡度、坡向、坡体结构及土地利用)作为滑坡易发性的评价指标，依据各指标条件下滑坡累计发生频率曲线斜率的变化，并结合滑坡面积比和分级面积比曲线对指标因子的状态进行分级；其次，根据全区655个历史滑坡数据，分别运用信息量模型和逻辑回归模型建立各自的滑坡易发性评价体系；再则，采用快速聚类法(K-means cluster)对以上2种方法所得到的易发性结果进行分级，并基于GIS平台，得到全区滑坡易发性区划图；最后，从模型结果、精度、适用条件等方面对2个模型进行讨论和比较，研究结果表明：信息量模型和逻辑回归模型的预测精度分别为73.0%和54.9%，前者预测能力要优于后者。

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关键词 ：边坡工程, 滑坡, 易发性评价, 信息量模型, 逻辑回归模型, 快速聚类模型

Abstract：Evaluation of landslide susceptibility for Wanzhou district of Evaluation of susceptibility of landslide hazard plays an important role in landslide hazard risk management and urban planning. In previous studies，few scholars had done any in-depth analysis and discussion on the state division of index factors. Wanzhou district of the Three Gorges Reservoir region where landslide disasters take place frequently is the focus of this study. Seven influence factors including stratum lithology，geological structure，water distribution，gradient，direction and structure of slopes，and land utilization were chosen to be the evaluation indexes. The state of each index was graded based on the variation of gradients of the cumulative frequency curve of landslide，the landslide area ratio curve and the grading area ratio curve. The information value model and the logistic regression model were used to build the susceptibility evaluation systems based on the data of 655 landslides in the history of the district. The susceptibility results of the two methods above were graded by adopting the K-means cluster analysis. A zoned map of landslide susceptibility for the whole district was obtained based on GIS platform. The two models were compared with respect to the modeling results，the accuracy，the application condition etc. The results showed that the prediction accuracies of the information value model and the logistic regression model reached 73.0% and 54.9% respectively，indicating that the information value model had better performance than the logistic regression model.

Key words： slope engineering landslide susceptibility evaluation the information value model the logistic regression model the K-means cluster model

引用本文:

张俊1，殷坤龙1，王佳佳1，刘磊1，黄发明2. 三峡库区万州区滑坡灾害易发性评价研究[J]. 岩石力学与工程学报, 2016, 35(2): 284-296.
ZHANG Jun1，YIN Kunlong1，WANG Jiajia1，LIU Lei1，HUANG Faming2. Evaluation of landslide susceptibility for Wanzhou district of Three Gorges Reservoir. , 2016, 35(2): 284-296.

链接本文:

http://www.rockmech.org/CN/10.13722/j.cnki.jrme.2015.0318 或 http://www.rockmech.org/CN/Y2016/V35/I2/284

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[15]	范林峰，胡瑞林，曾逢春，等. 加权信息量模型在滑坡易发性评价中的应用——以湖北省恩施市为例[J]. 工程地质学报，2012，20(4)：508–513.(FAN Linfeng，HU Ruilin，ZENG Fengchun，et al. Application of weighted information value model to landslide susceptibility assessment——a case study of Enshi city，Hubei province[J]. Journal of Engineering Geology，2012，20(4)：508–513.(in Chinese))
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[1]	殷坤龙，朱良峰. 滑坡灾害空间区划及GIS应用研究[J]. 地学前缘，2001，8(2)：279–284.(YIN Kunlong，ZHU Liangfeng. Landslide hazard zonation and application of GIS[J]. Earth Science Frontiers，2001，8(2)：279–284.(in Chinese)) " target="_blank">
[18]	杜军，杨青华，严嘉，等. 基于GIS与信息量模型的汶川次生地质灾害危险性评价[J]. 地球科学：中国地质大学学报，2010，35(2)：324–330.(DU Jun，YANG Qinghua，YAN Jia，et al. Hazard evaluation of secondary geological disaster based on GIS and information value method[J]. Earth Science：Journal of China University of Geosciences，2010，35(2)：324–330.(in Chinese)) " target="_blank">
[26]	丛威青，潘懋，李铁锋，等. 基于GIS的滑坡、泥石流灾害危险性区划关键问题研究[J]. 地学前缘，2006，13(1)：185–190.(CONG Weiqing，PAN Mao，LI Tiefeng，et al. Key research on landslide and debris flow hazard zonation based on GIS[J]. Earth Science Frontiers，2006，13(1)：185–190.(in Chinese)) " target="_blank">
[30]	梁彦冰，崔雪松. SPSS15.0统计分析与实践应用宝典[M]. 北京：中国铁道出版社，2010：141–148.(LIANG Yanbing，CUI Xuesong. SPSS15.0 statistical analysis and practical application[M]. Beijing：China Railway Press，2010：141–148.(in Chinese)) " target="_blank">
[32]	PRADHAN B. A comparative study on the predictive ability of the decision tree，support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS[J]. Computers and Geosciences，2013，51：350–365. " target="_blank">
[33]	TIEN B D，PRADHAN B，LOFMAN O，et al. Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province，Vietnam[J]. Natural Hazards，2013，66(2)：707–730.
[7]	REGMI A D，DEVKOTA K C，YOSHIDA K，et al. Mapping at Haraz watershed，Iran and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya[J]. Arabian Journal of Geosciences，2014，7：725–742. " target="_blank">
[9]	LEE S，BISWAJEET P. Landslide hazard mapping at Selangor，Malaysia using frequency ratio and logistic regression models[J]. Landslides，2007，4(1)：33–41.
[10]	ALTHUWAYNEE O F，PRADHAN B，PARK H，et al. A novel ensemble decision tree-based CHi-squared automatic interaction detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping[J]. Landslides，2014，11(6)：1 063–1 078. " target="_blank">
[11]	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. " target="_blank">
[2]	中华人民共和国国土资源部. 全国地质灾害通报(2014年)[EB/OL]. http：//www.cgs.gov.cn/UploadFiles/2015_01/21/20150121111239365.pdf，2015–01–21.(Ministry of Land and Resource of the People?s Republic of China. Geological hazards bulletin of China(2014)[EB/OL]. http：//www.cgs.gov.cn/UploadFiles/2015_01/21/20150121111239365.pdf，2015–01–21.(in Chinese)) " target="_blank">
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[8]	AYALEW L，YAMAGISHI H. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains，Central Japan[J]. Geomorphology，2005，65(1/2)：15–31. " target="_blank">
[12]	戴福初，姚鑫，谭国焕. 滑坡灾害空间预测支持向量机模型及其应用[J]. 地学前缘，2007，14(6)：153–159.(DAI Fuchu，YAO Xin，TAN Leslie George. Landslide susceptibility mapping using support vector machines[J]. Earth Science Frontiers，2007，14(6)：153–159.(in Chinese)) " target="_blank">
[13]	PENG L，NIU R，HUANG B，et al. Landslide susceptibility mapping based on rough set theory and support vector machines：A case of the Three Gorges area，China[J]. Geomorphology，2014，204(2)：287–301. " target="_blank">
[14]	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))
[16]	高克昌，崔鹏，赵纯勇，等. 基于地理信息系统和信息量模型的滑坡危险性评价——以重庆万州为例[J]. 岩石力学与工程学报，2006，25(5)：991–996.(GAO Kechang，CUI Peng，ZHAO Chunyong，et al. Landslide hazard evaluation of Wanzhou based on GIS information value method in the Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering，2006，25(5)：991–996.(in Chinese))
[19]	戴悦. 基于信息量模型的三峡库区滑坡区域危险性评价方法研究[硕士学位论文][D]. 北京：清华大学，2013.(DAI Yue. Study on the method of regional early warning of landslide in Three Gorges Area based on information model[M. S. Thesis][D]. Beijing：Tsinghua University，2013.(in Chinese)) " target="_blank">
[31]	POURGHASEMI H R，JIRANDEH A G，PRADHAN B，et al. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province，Iran[J]. Journal of Earth System Science，2013，122(2)：349–369. " target="_blank">
[3]	王进，郭靖，王卫东，等. 权重线性组合与逻辑回归模型在滑坡易发性区划中的应用与比较[J]. 中南大学学报：自然科学版，2012，43(5)：1 932–1 939.(WANG Jin，GUO Jing，WANG Weidong，et al. Application and comparison of weighted linear combination model and logistic regression model in landslide susceptibility mapping[J]. Journal of Central South University：Science and Technology，2012，43(5)：1 932–1 939.(in Chinese)) " target="_blank">
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[5]	王志旺，李端有，王湘桂. 区域滑坡空间预测方法研究综述[J]. 长江科学院院报，2012，29(5)：78–85.(WANG Zhiwang，LI Duanyou，WANG Xianggui. Review of researches on regional landslide susceptibility mapping model[J]. Journal of Yangtze River Scientific Research Institute，2012，29(5)：78–85.(in Chinese))
[21]	张桂荣，殷坤龙，刘传正，等. 基于 GIS 的陕西省旬阳地区滑坡灾害危险性区划[J]. 中国地质灾害与防治学报，2003，14(4)：42–46.(ZHANG Guirong，YIN Kunlong，LIU Chuanzheng，et al. The hazard zoning of landslide supported by GIS in Xunyang region of Shaanxi province[J]. The Chinese Journal of Geological Hazard and Control，2003，14(4)：42–46.(in Chinese)) " target="_blank">
[22]	张桂荣，殷坤龙. 区域滑坡空间预测方法研究及结果分析[J]. 岩石力学与工程学报. 2005，24(23)：4 297–4 302.(ZHANG Guirong，YIN Kunlong. Study on spatial prediction method for regional landslides and results analysis[J]. Chinese Journal of Rock Mechanics and Engineering，2005，24(23)：4 297–4 302.(in Chinese)) " target="_blank">
[23]	OHLMACHER G C，DAVIS J C. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas，USA[J]. Engineering Geology，2003，69(3/4)：331–343. " target="_blank">
[24]	肖桐. 基于GIS的兰州市滑坡空间模拟研究[硕士学位论文][D]. 兰州：兰州大学，2007.(XIAO Tong. GIS-based research on spatial simulation of landslide in Lanzhou[M. S. Thesis][D]. Lanzhou：Lanzhou University，2007.(in Chinese)) " target="_blank">
[25]	AYALEW L，YAMAGISHI H. The application of GIS based logistic regression for landslide susceptibility mapping in the Kakuda Yahiko Mountains，Central Japan[J]. Geomorphology，2005，65(8)：15–31. " target="_blank">
[26]	丛威青，潘懋，李铁锋，等. 基于GIS的滑坡、泥石流灾害危险性区划关键问题研究[J]. 地学前缘，2006，13(1)：185–190.(CONG Weiqing，PAN Mao，LI Tiefeng，et al. Key research on landslide and debris flow hazard zonation based on GIS[J]. Earth Science Frontiers，2006，13(1)：185–190.(in Chinese)) " target="_blank">
[15]	范林峰，胡瑞林，曾逢春，等. 加权信息量模型在滑坡易发性评价中的应用——以湖北省恩施市为例[J]. 工程地质学报，2012，20(4)：508–513.(FAN Linfeng，HU Ruilin，ZENG Fengchun，et al. Application of weighted information value model to landslide susceptibility assessment——a case study of Enshi city，Hubei province[J]. Journal of Engineering Geology，2012，20(4)：508–513.(in Chinese))
[17]	牛全福，程维明，兰恒星，等. 基于信息量模型的玉树地震次生地质灾害危险性评价[J]. 山地学报，2011，29(2)：243–249.(NIU Quanfu，CHENG Weiming，LAN Hengxing，et al. Susceptibility assessment of secondary geological disaster based on information value methodology for Yushu earthquake region[J]. Journal of Mountain Science，2011，29(2)：243–249.(in Chinese)) " target="_blank">
[18]	杜军，杨青华，严嘉，等. 基于GIS与信息量模型的汶川次生地质灾害危险性评价[J]. 地球科学：中国地质大学学报，2010，35(2)：324–330.(DU Jun，YANG Qinghua，YAN Jia，et al. Hazard evaluation of secondary geological disaster based on GIS and information value method[J]. Earth Science：Journal of China University of Geosciences，2010，35(2)：324–330.(in Chinese)) " target="_blank">
[20]	殷坤龙. 滑坡灾害预测预报[M]. 武汉：中国地质大学出版社，2004：26–29.(YIN Kunlong. Landslide hazard prediction and evaluation[M]. Wuhan：China University of Geosciences Press，2004：26–29.(in Chinese)). " target="_blank">
[27]	薛薇，陈欢歌. CLEMENTINE数据挖掘方法及应用[M]. 北京：电子工业出版社，2010：270–271.(XUE Wei，CHEN Huange. CLEMENTINE data mining methods and applications[M]. Beijing：Electronic Industry Press，2010：270–271.(in Chinese)) " target="_blank">
[30]	梁彦冰，崔雪松. SPSS15.0统计分析与实践应用宝典[M]. 北京：中国铁道出版社，2010：141–148.(LIANG Yanbing，CUI Xuesong. SPSS15.0 statistical analysis and practical application[M]. Beijing：China Railway Press，2010：141–148.(in Chinese)) " target="_blank">
[32]	PRADHAN B. A comparative study on the predictive ability of the decision tree，support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS[J]. Computers and Geosciences，2013，51：350–365. " target="_blank">
[33]	TIEN B D，PRADHAN B，LOFMAN O，et al. Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province，Vietnam[J]. Natural Hazards，2013，66(2)：707–730.
[28]	高惠璇. 应用多元统计分析[M]. 北京：北京大学出版社，2005：246–252.(GAO Huixuan. Application of multivariate statistical analysis[M]. Beijing：Peking University Press，2005：246–252.(in Chinese)) " target="_blank">
[29]	彭令. 三峡库区滑坡灾害风险评估研究[博士学位论文][D]. 武汉：中国地质大学，2013.(PENG Ling. Landslide risk assessment in the Three Gorges Reservoir[Ph. D. Thesis][D]. Wuhan：China University of Geosciences，2013.(in Chinese)) " target="_blank">
[7]	REGMI A D，DEVKOTA K C，YOSHIDA K，et al. Mapping at Haraz watershed，Iran and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya[J]. Arabian Journal of Geosciences，2014，7：725–742. " target="_blank">
[10]	ALTHUWAYNEE O F，PRADHAN B，PARK H，et al. A novel ensemble decision tree-based CHi-squared automatic interaction detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping[J]. Landslides，2014，11(6)：1 063–1 078. " target="_blank">
[11]	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. " target="_blank">
[13]	PENG L，NIU R，HUANG B，et al. Landslide susceptibility mapping based on rough set theory and support vector machines：A case of the Three Gorges area，China[J]. Geomorphology，2014，204(2)：287–301. " target="_blank">
[14]	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))
[1]	殷坤龙，朱良峰. 滑坡灾害空间区划及GIS应用研究[J]. 地学前缘，2001，8(2)：279–284.(YIN Kunlong，ZHU Liangfeng. Landslide hazard zonation and application of GIS[J]. Earth Science Frontiers，2001，8(2)：279–284.(in Chinese)) " target="_blank">
[2]	中华人民共和国国土资源部. 全国地质灾害通报(2014年)[EB/OL]. http：//www.cgs.gov.cn/UploadFiles/2015_01/21/20150121111239365.pdf，2015–01–21.(Ministry of Land and Resource of the People?s Republic of China. Geological hazards bulletin of China(2014)[EB/OL]. http：//www.cgs.gov.cn/UploadFiles/2015_01/21/20150121111239365.pdf，2015–01–21.(in Chinese)) " target="_blank">
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