不确定密度聚类分析算法的滑坡危险性评价
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摘要
针对雨量值无法有效刻画及聚类算法难以适用地质地貌较复杂的大范围滑坡危险程度评估模型建立等问题,采用UM-Chameleon算法建立区域滑坡危险性评估模型,并对延安宝塔区进行评估,试验结果表明,评估结果与实际一致,体现出区内滑坡灾害发育的整体特点,证明该模型的有效性及研究区适用范围的宽广性;其滑坡预测成功率比M-Chameleon算法高,证明该模型能有效刻画雨量值,从而能有效地提高滑坡危险性预测精度。
It is difficult to quantify the rainfall value and apply these assessment models of landslide hazards based on traditional clustering algorithms to large study area with complicated geology and the general configuration of the earth's surface. Taking the Baota district of Yan'an city as the study case, the assessment model of landslide hazards was constructed using UM-Chameleon algorithm. The results show that:(1)the evaluation results based on UM-Chameleon algorithm landslide assessment model are consistent with actual landslide development, which can properly reflect the general characteristics of regional landslide evolution, indicating that the new model is availability; 2) the success rate curve in landslide of UM-Chameleon algorithm is higher than that of the M-Chameleon's, indicating that the new model can better quantify the rainfall value to improve the accuracy of prediction.
It is difficult to quantify the rainfall value and apply these assessment models of landslide hazards based on traditional clustering algorithms to large study area with complicated geology and the general configuration of the earth's surface. Taking the Baota district of Yan'an city as the study case, the assessment model of landslide hazards was constructed using UM-Chameleon algorithm. The results show that:(1)the evaluation results based on UM-Chameleon algorithm landslide assessment model are consistent with actual landslide development, which can properly reflect the general characteristics of regional landslide evolution, indicating that the new model is availability; 2) the success rate curve in landslide of UM-Chameleon algorithm is higher than that of the M-Chameleon's, indicating that the new model can better quantify the rainfall value to improve the accuracy of prediction.
引文
[1] 龙建辉, 郭文斌, 李萍, 等. 黄土滑坡滑带土的蠕变特征[J]. 岩土工程学报, 2010, 32(7): 1023-1028.LONG Jianhui, GUO Wenbin, LI Ping, et al. Creep property of soil in sliding zone of loess landslide[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(7): 1023-1028. (in Chinese)
[2] 宋效东, 汤国安. 基于并行GVF Snake模型的黄土地貌沟沿线提取[J]. 中国矿业大学学报, 2013, 42(1): 134-140.SONG Xiaodong, TANG Guoan. Extraction of loess landform shoulder line based on parallel GVF Snake model [J]. Journal of China University of Mining & Technology, 2013, 42(1): 134-140. (in Chinese)
[3] 张茂省, 李同录. 黄土滑坡诱发因素及其形成机理研究[J]. 工程地质学报, 2011, 19(4): 530-540.ZHANG Maosheng, LI Tonglu. Triggering factors and forming mechanism of loess landslides[J]. Journal of Engineering Geology, 2011, 19(4): 530-540. (in Chinese)
[4] 韩流, 周伟. 软岩边坡平面滑动时效稳定性分析及结构优化[J]. 中国矿业大学学报, 2014, 43(3): 395-401.HAN Liu, ZHOU Wei. Study of plane sliding timeliness stability and structure optimization of soft rock slope[J]. Journal of ChinaUniversity of Mining & Technology, 2014, 43(3): 395-401. (in Chinese)
[5] 刘磊, 殷坤龙, 王佳佳, 等. 降雨影响下的区域滑坡危险性动态评价研究-以三峡库区万州主城区为例[J]. 岩石力学与工程学报, 2016, 35(3): 558-569.LIU Lei, YIN Kunlong, WANG Jiajia, et al. Dynamic evaluation of regional landslide hazard due to rainfall: a case study in Wanzhou central district, Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering, 2016, 35(3): 558-569. (in Chinese)
[6] 张茂省, 唐亚明. 地质灾害风险调查的方法与实践[J]. 地质通报, 2008, 32(8): 55-66.ZHANG Maosheng, TANG Yaming. Risk investigation method and practice geohazards[J]. Geological Bulletin of China, 2008, 32(8): 55-66. (in Chinese)
[7] 邓勇, 张正禄, 谢年生, 等. 模糊聚类及其在滑坡检测中的应用研究[J]. 测绘科学, 2010, 35(4): 163-165.DENG Yong, ZHANG Zhenglu, XIE Niansheng. Fuzzy clustering and its application in landslide detection research[J]. Science of Surveying and Mapping, 2010, 35(4): 163-165. (in Chinese)
[8] 桂蕾, 殷坤龙, 王佳佳. 基于聚类分析的滑坡灾害危险性区划研究[J]. 水文地质工程地质, 2013, 40(1): 100-105.DENG Lei, YIN Kunlong, WANG Jiajia. Landslide hazard zonation based on the clustering analysis[J]. Hydrogeology & Engineering Geology, 2013, 40(1): 100-105. (in Chinese)
[9] 丁明涛, 韦方强, 王欢, 等. 基于聚类分析的三江并流区泥石流危险性评价[J]. 资源科学, 2012, 34(7): 1257-1265.DING Mingtao, WEI Fangqiang, WANG Huan, et al. Hazard assessment of debris flow based on cluster analysis in three parallel rivers area[J]. Resources Science, 2012, 34(7): 1257-1265. (in Chinese)
[10] Ding M T, Hu K H. Susceptibility mapping of landslide in Beichuan Country using cluster and MLC methods[J]. Nat Hazards, 2014, 70(9): 755-766.
[11] Wan S. Entropy-based particle swarm optimization with clustering analysis on landslide susceptibility mapping[J]. Environmental Earth Science, 2013, 68(7): 1349-1366.
[12] Wan S, Jia Y Y, Lin C Y, et al. Construction of knowledge-based spatial decision support system for landslide mapping using fuzzy clustering and KPSO analysis[J]. Arabian Journal Geosciences, 2015, 8(1): 1041-1055.
[13] 龙真真, 张策, 刘飞裔, 等. 一种改进的Chameleon算法[J]. 计算机工程, 2009, 35(20): 189-191.LONG Zhenzhen, ZHANG Ce, LIU Feiyi, et al. An improved Chameleon clustering algorithm[J]. Computer Engineering, 2009, 35(20): 189-191. (in Chinese)
[14] 刘卫民, 张灿龙, 毛伊敏. 不确定DM-chameleon聚类算法在滑坡危险性预测中的研究与应用[J]. 计算机工程, 2017, 32(2): 156-163.LIU Weimin, ZHANG Canlong, MAO Yimin. Research and application of uncertain DM-chameleon clustering algorithm in landslide hazard prediction[J]. Computer Engineering, 2017, 32(2): 156-163. (in Chinese)
[15] 张茂省, 李林, 唐亚明. 基于风险理念的黄土滑坡调查与编图研究[J]. 工程地质学报, 2011, 19(1): 43-51.ZHANG Maosheng, LI Lin, TANG Yaming. Risk Management based Landslide investigation and Mapping in loss area[J]. Journal of Engineering Geology, 2011, 19(1): 43-51. (in Chinese)
[16] ZHANG M S, LIU J. Controlling factors of loess landslide in western China[J]. Environmental Earth Sciences, 2010, 59(6): 1671-1680.
[17] 陈晋音, 何辉豪. 基于密度的聚类中心自动确定的混合属性数据聚类算法研究[J]. 自动化学报, 2015, 41(10): 1798-1813.CHEN Jinyin, HE Huihao. Research on density-based clustering algorithm for mixed data with determine cluster centers automatically[J]. Acta Automatica Sinica, 2015, 41(10): 1798-1813. (in Chinese)
[18] 毛伊敏, 张茂省, 程秀娟. 基于不确定贝叶斯分类技术的滑坡危险性评价[J]. 中国矿业大学学报, 2015, 44(4): 769-774.MAO Yimin, ZHANG Maosheng, CHENG Xiujuan. Landslide hazards assessment based on uncertain Bayesian classification method[J]. Journal of China University of Mining &Technology, 2015, 44(4): 769-774. (in Chinese)
[19] Xu C, Xu X W, Dai C, et al. Landslide hazard mapping using GIS and weight of evidence model in Qingshui river watershed of 2008 Wenchuan earthquake struck region[J]. Journal of Earth Science, 2012, 23(1): 97-120.
[20] Feizizadeh B, Roodposhti M S, Blaschke T, et al. Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping[J]. Arabian Journal of Geosciences, 2017, 10(7): 122-132.
[21] 刘希林, 陈宜娟. 泥石流点密度和面密度对区域泥石流危险度的影响-对比研究[J]. 自然灾害学报, 2011, 20(2): 36-44.LIU Xilin, CHEN Yijuan. Influence of debris flow spot and area densities on regional hazardousness of debris flow: a comparative study[J]. Journal of Natural Disasters, 2011, 20(2): 36-44. (in Chinese)
[22] Rossi M, Guzzetti F, Reichenbach P, et al. Optimal landslide susceptibility zonation based on multiple forecasts[J]. Geomorphology, 2010, 114(4/5): 129-142.
[2] 宋效东, 汤国安. 基于并行GVF Snake模型的黄土地貌沟沿线提取[J]. 中国矿业大学学报, 2013, 42(1): 134-140.SONG Xiaodong, TANG Guoan. Extraction of loess landform shoulder line based on parallel GVF Snake model [J]. Journal of China University of Mining & Technology, 2013, 42(1): 134-140. (in Chinese)
[3] 张茂省, 李同录. 黄土滑坡诱发因素及其形成机理研究[J]. 工程地质学报, 2011, 19(4): 530-540.ZHANG Maosheng, LI Tonglu. Triggering factors and forming mechanism of loess landslides[J]. Journal of Engineering Geology, 2011, 19(4): 530-540. (in Chinese)
[4] 韩流, 周伟. 软岩边坡平面滑动时效稳定性分析及结构优化[J]. 中国矿业大学学报, 2014, 43(3): 395-401.HAN Liu, ZHOU Wei. Study of plane sliding timeliness stability and structure optimization of soft rock slope[J]. Journal of ChinaUniversity of Mining & Technology, 2014, 43(3): 395-401. (in Chinese)
[5] 刘磊, 殷坤龙, 王佳佳, 等. 降雨影响下的区域滑坡危险性动态评价研究-以三峡库区万州主城区为例[J]. 岩石力学与工程学报, 2016, 35(3): 558-569.LIU Lei, YIN Kunlong, WANG Jiajia, et al. Dynamic evaluation of regional landslide hazard due to rainfall: a case study in Wanzhou central district, Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering, 2016, 35(3): 558-569. (in Chinese)
[6] 张茂省, 唐亚明. 地质灾害风险调查的方法与实践[J]. 地质通报, 2008, 32(8): 55-66.ZHANG Maosheng, TANG Yaming. Risk investigation method and practice geohazards[J]. Geological Bulletin of China, 2008, 32(8): 55-66. (in Chinese)
[7] 邓勇, 张正禄, 谢年生, 等. 模糊聚类及其在滑坡检测中的应用研究[J]. 测绘科学, 2010, 35(4): 163-165.DENG Yong, ZHANG Zhenglu, XIE Niansheng. Fuzzy clustering and its application in landslide detection research[J]. Science of Surveying and Mapping, 2010, 35(4): 163-165. (in Chinese)
[8] 桂蕾, 殷坤龙, 王佳佳. 基于聚类分析的滑坡灾害危险性区划研究[J]. 水文地质工程地质, 2013, 40(1): 100-105.DENG Lei, YIN Kunlong, WANG Jiajia. Landslide hazard zonation based on the clustering analysis[J]. Hydrogeology & Engineering Geology, 2013, 40(1): 100-105. (in Chinese)
[9] 丁明涛, 韦方强, 王欢, 等. 基于聚类分析的三江并流区泥石流危险性评价[J]. 资源科学, 2012, 34(7): 1257-1265.DING Mingtao, WEI Fangqiang, WANG Huan, et al. Hazard assessment of debris flow based on cluster analysis in three parallel rivers area[J]. Resources Science, 2012, 34(7): 1257-1265. (in Chinese)
[10] Ding M T, Hu K H. Susceptibility mapping of landslide in Beichuan Country using cluster and MLC methods[J]. Nat Hazards, 2014, 70(9): 755-766.
[11] Wan S. Entropy-based particle swarm optimization with clustering analysis on landslide susceptibility mapping[J]. Environmental Earth Science, 2013, 68(7): 1349-1366.
[12] Wan S, Jia Y Y, Lin C Y, et al. Construction of knowledge-based spatial decision support system for landslide mapping using fuzzy clustering and KPSO analysis[J]. Arabian Journal Geosciences, 2015, 8(1): 1041-1055.
[13] 龙真真, 张策, 刘飞裔, 等. 一种改进的Chameleon算法[J]. 计算机工程, 2009, 35(20): 189-191.LONG Zhenzhen, ZHANG Ce, LIU Feiyi, et al. An improved Chameleon clustering algorithm[J]. Computer Engineering, 2009, 35(20): 189-191. (in Chinese)
[14] 刘卫民, 张灿龙, 毛伊敏. 不确定DM-chameleon聚类算法在滑坡危险性预测中的研究与应用[J]. 计算机工程, 2017, 32(2): 156-163.LIU Weimin, ZHANG Canlong, MAO Yimin. Research and application of uncertain DM-chameleon clustering algorithm in landslide hazard prediction[J]. Computer Engineering, 2017, 32(2): 156-163. (in Chinese)
[15] 张茂省, 李林, 唐亚明. 基于风险理念的黄土滑坡调查与编图研究[J]. 工程地质学报, 2011, 19(1): 43-51.ZHANG Maosheng, LI Lin, TANG Yaming. Risk Management based Landslide investigation and Mapping in loss area[J]. Journal of Engineering Geology, 2011, 19(1): 43-51. (in Chinese)
[16] ZHANG M S, LIU J. Controlling factors of loess landslide in western China[J]. Environmental Earth Sciences, 2010, 59(6): 1671-1680.
[17] 陈晋音, 何辉豪. 基于密度的聚类中心自动确定的混合属性数据聚类算法研究[J]. 自动化学报, 2015, 41(10): 1798-1813.CHEN Jinyin, HE Huihao. Research on density-based clustering algorithm for mixed data with determine cluster centers automatically[J]. Acta Automatica Sinica, 2015, 41(10): 1798-1813. (in Chinese)
[18] 毛伊敏, 张茂省, 程秀娟. 基于不确定贝叶斯分类技术的滑坡危险性评价[J]. 中国矿业大学学报, 2015, 44(4): 769-774.MAO Yimin, ZHANG Maosheng, CHENG Xiujuan. Landslide hazards assessment based on uncertain Bayesian classification method[J]. Journal of China University of Mining &Technology, 2015, 44(4): 769-774. (in Chinese)
[19] Xu C, Xu X W, Dai C, et al. Landslide hazard mapping using GIS and weight of evidence model in Qingshui river watershed of 2008 Wenchuan earthquake struck region[J]. Journal of Earth Science, 2012, 23(1): 97-120.
[20] Feizizadeh B, Roodposhti M S, Blaschke T, et al. Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping[J]. Arabian Journal of Geosciences, 2017, 10(7): 122-132.
[21] 刘希林, 陈宜娟. 泥石流点密度和面密度对区域泥石流危险度的影响-对比研究[J]. 自然灾害学报, 2011, 20(2): 36-44.LIU Xilin, CHEN Yijuan. Influence of debris flow spot and area densities on regional hazardousness of debris flow: a comparative study[J]. Journal of Natural Disasters, 2011, 20(2): 36-44. (in Chinese)
[22] Rossi M, Guzzetti F, Reichenbach P, et al. Optimal landslide susceptibility zonation based on multiple forecasts[J]. Geomorphology, 2010, 114(4/5): 129-142.