[1]张向营,张春山,孟华君,等.基于Random Forest 和AHP的贵德县北部山区滑坡危险性评价[J].水文地质工程地质,2018,45(04):142.[doi:10.16030/j.cnki.issn.1000-3665.2018.04.21]
 ZHANG Xiangying,ZHANG Chunshan,MENG Huajun,et al.Landslide hazard evaluation in the northern mountainous area of Guide County based on Random Forest and AHP[J].Hydrogeology & Engineering Geology,2018,45(04):142.[doi:10.16030/j.cnki.issn.1000-3665.2018.04.21]
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基于Random Forest 和AHP的贵德县北部山区滑坡危险性评价()
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《水文地质工程地质》[ISSN:1000-3665/CN:11-2202/P]

卷:
45卷
期数:
2018年04期
页码:
142
栏目:
环 境 地 质
出版日期:
2018-07-15

文章信息/Info

Title:
Landslide hazard evaluation in the northern mountainous area of Guide County based on Random Forest and AHP
文章编号:
1000-3665(2018)04-0142-08
作者:
张向营123张春山12孟华君12王雪冰12赵伟康124郑满城124
1.中国地质科学院地质力学研究所, 北京100081;2.自然资源部新构造运动与地质灾害重点实验室,北京100081;3.北京城建勘测设计院有限责任公司,北京100101;4.中国地质大学(北京)地球科学与资源学院,北京100083
Author(s):
ZHANG Xiangying123 ZHANG Chunshan12 MENG Huajun12 WANG Xuebing12 ZHAO Weikang124 ZHENG Mancheng124
1.Institute of Geomechanics, Chinese Academy of Geological sciences, Beijing100081, China;2.Key Laboratory of Neotectonic Movement & Geohazard, Ministry of Natural Resources,Beijing100081, China; 3.Beijing Urban Construction Survey and Design Institute, Co.Ltd, Beijing100101, China; 4.College of Earth Science and Resources, China University of Geosciences, Beijing100083, China
关键词:
滑坡危险性组合赋权模型层次分析法随机森林法
Keywords:
landslide hazard combined weight process Analytic Hierarchy Process Random Forest
分类号:
P642.22
DOI:
10.16030/j.cnki.issn.1000-3665.2018.04.21
文献标志码:
A
摘要:
滑坡危险性评价是滑坡灾害防治和管理的重要依据。文章基于层次分析法和随机森林模型,结合距离函数法,探索性地提出了一种新的组合赋权法(RF-AHP)。采用RF-AHP对青海省贵德县北部山区滑坡进行了危险性评价,对比探讨了AHP、RF和RF-AHP三种模型评价结果与实际滑坡灾害的吻合性,结果表明:(1)RF-AHP在高危险区和极高危险区面积占比38.38%的情况下,包括了60.13%的滑坡灾害,结果准确性相比AHP和RF两种模型有较大提升;(2)随着危险性等级的逐步提高,RF-AHP区划结果中相应分区的灾害实际发生的比率也随之增高,并对三种方法出现结果差异的客观原因进行了分析讨论,证明RF-AHP适用于滑坡危险性评价工作。
Abstract:
Evaluation of landslide susceptibility provide an importance evidence of landslide disaster prevention and landslide warning. A new combined weight process(RF-AHP) based on random forest(RF), analytic hierarchy process(AHP) and distance functions is proposed. The model is applied to the northern mountainous area of Guide County. The compatibility and applicability of three models are discussed. The results show that (1) the RF-AHP model accounts for 38.38% of the high risk area and the extremely high risk area, it includes 60.13% of the landslide disasters, is greatly improved compared to the two models of AHP and RF. (2)With the gradual increase in risk levels, the actual rate of the corresponding disasters in the results of RF-AHP also gradually increases. The objective causes of the difference in results between the three methods were discussed. It can be concluded from the case study that combined weight process is suitable for evalution of landslide susceptibility.

参考文献/References:

[1]王森,许强,罗博宇,等.基于分形理论的南江县滑坡敏感性分析与易发性评价[J].水文地质工程地质,2017,44(3):119-126.
[WANG S,XU Q,LUO B Y,et al. Vulnerability analysis and susceptibility evaluation of landslides based on fractal theory in Nanjiang County[J].Hydrogeology & Engineering Geology,2017,44(3):119-126.(in Chinese)]
[2]张春山,张业成,马寅生. 黄河上游地区崩塌、滑坡、泥石流地质灾害区域危险性评价[J]. 地质力学学报, 2003,9(2): 143-153.
[ZHANG C S, ZHANG Y C, MA Y S. Regional dangerous on the geological hazards of collapse, landslide and debris flows in the upper reaches of yellow river. [J]. Journal of Geomechanics, 2003,9(2): 143-153. (in Chinese)]
[2]王涛,吴树仁,石菊松. 国际滑坡风险评估与管理指南研究综述[J]. 地质通报,2009, 28(8): 1006-1019.
[WANG T, WU S R, SHI J S. A review of international landslide risk assessment and management guidelines[J]. Geological Bulletin of China,2009, 28(8): 1006-1019. (in Chinese)]
[3]阮沈勇,黄润秋. 基于GIS的信息量法模型在地质灾害危险性区划中的应用[J]. 成都理工学院学报, 2001(1): 89-92.
[RUAN S Y, HUANG R Q. Application of GIS-based information model on assessment of geological hazards risk[J]. Journal of Chengdu University of Technology ,2001(1): 89-92. (in Chinese)]
[4]许冲, 戴福初, 徐素宁,等. 基于逻辑回归模型的汶川地震滑坡危险性评价与检验[J]. 水文地质工程地质, 2013, 40(3):98-104.
[XU C, DAI F C, XU S N. Application of logistic regression model on the Wenchuan earthquake triggered landslide hazard mapping and its validation[J]. Hydrogeology & Engineering Geology, 2013, 40(3):98-104. (in Chinese)]
[5]许冲,徐锡伟,于贵华. 基于证据权方法的玉树地震滑坡危险性评价[J]. 地震地质,2013(1): 151-164.
[XU C, XU X W, YU G H. The Yushu earthquake triggered landslide hazard evaluation based on weight of evidence method[J]. Seismology and Geology,2013(1): 151-164. (in Chinese)]
[6]乔建平,石莉莉,王萌. 基于贡献权重叠加法的滑坡风险区划[J]. 地质通报,2008,27(11): 1787-1794.
[QIAO J P, SHI L L, WANG M. Landslide risk zoning based on the contributing weight stack method[J]. Geological Bulletin of China, 2008,27(11): 1787-1794. (in Chinese)]
[7]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.
[GUI L,YIN K L,WANG J J. Landslide hazard zonation based on cluster analysis[J].Hydrogeology & Engineering Geology,2013,40(1):100-105. (in Chinese)]
[8]向喜琼,黄润秋. 基于GIS的人工神经网络模型在地质灾害危险性区划中的应用[J]. 中国地质灾害与防治学报,2000,11(3): 26-30.
[XIANG X Q, HUANG R Q. Application of GIS-based artificial neural networks on assessment of geohazards risk[J]. The Chinese Journal of Geological Hazard and Control,2000,11(3): 26-30. (in Chinese)]
[9]Yalcin A. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations[J]. Catena,2008, 72(1): 1-12.
[10]Pourghasemi H R, Pradhan B, Gokceoglu C. Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran[J]. Natural Hazards,2012, 63(2): 965-996.
[11]Breiman L. Random Forests[J]. Machine Learning. 2001, 45(1): 5-32.
[12]李欣海. 随机森林模型在分类与回归分析中的应用[J]. 应用昆虫学报, 2013, 50(4): 1190-1197.
[LI X H. Using “random forest” for classification and regression[J]. Chinese Journal of Applied Entomology, 2013, 50(4): 1190-1197. (in Chinese)]
[13]李亭,田原,邬伦,等. 基于随机森林方法的滑坡灾害危险性区划[J]. 地理与地理信息科学, 2014,30(6): 25-30.
[LI T, TIAN Y, WU L, et al. Landslide susceptibility mapping using random forest[J]. Geography and Geo-Information Science, 2014,30(6): 25-30. (in Chinese)]
[14]Hong H, Pourghasemi H R, Pourtaghi Z S. Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models[J]. Geomorphology, 2016, 259: 105-118.
[15]薛毅,陈立萍. 统计建模与R软件[M]. 北京:清华大学出版社, 2007.
[XUE Y, CHEN L P. Statistical modeling and R software[M]. Beijing:Tsinghua University Press, 2007. (in Chinese)]
[16]Bradley A P. The use of the area under the ROC curve in the evaluation of machine learning algorithms[J]. Pattern Recognition,2008, 30(7): 1145-1159.
[17]邓雪, 李家铭, 曾浩健,等. 层次分析法权重计算方法分析及其应用研究[J]. 数学的实践与认识, 2012, 42(7):93-100.
[DENG X, LI J M, ZENG H Q, et al. Research on computation methods of AHP weight vector and its applications[J]. Mathematics in Practice and Theory, 2012, 42(7):93-100. (in Chinese)]
[18]张甫仁,朱方圆,彭清元,等. 重庆主城区浅层地温能适宜性分区评价[J]. 重庆交通大学学报(自然科学版),2013, 32(4): 647-651.
[ZHANG F R, ZHU F Y, PENG Q Y, et al. Adaptive partition evaluation of shallow geothermal energy in urban area of Chongqing[J]. Journal of Chongqing Jiaotong University(Natural Science),2013, 32(4): 647-651. (in Chinese)]
[19]陈燕平. 基于GIS的贵州省滑坡地质灾害易发性多模型综合评价[D]. 长沙:中南大学, 2010.[CHEN Y P. GIS based landslide susceptibility assessment of Guizhou province using multi-model comprehensive evaluation[D].Changsha: Central South University, 2010.(in Chinese)]
[20]张晨,王清,陈剑平,等. 金沙江流域泥石流的组合赋权法危险度评价[J]. 岩土力学, 2011,32(3): 831-836.
[ZHANG C, WANG Q, CHEN J P, et al. Evaluation of debris flow risk in Jinsha river based on combined weight process[J]. Rock and Soil Mechanics,2011,32(3): 831-836. (in Chinese)]
[21]Ahmed O S, Franklin S E, Wulder M A, et al. Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2015, 101: 89-101.
[22]Horning N. Random Forests: An algorithm for image classification and generation of continuous fields data sets[J]. 2010.

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 CHEN Yu ping,YUAN Zhi qiang,ZHOU Bo,et al.Application of back propagation neural networks with optimization of genetic algorithms to landslide hazard prediction[J].Hydrogeology & Engineering Geology,2012,39(04):114.

备注/Memo

备注/Memo:
收稿日期: 2017-10-10; 修订日期: 2018-01-09
基金项目: 中国地质调查局项目(DD20160267);国家自然科学基金资助项目(41502339)
第一作者: 张向营(1993-),男,硕士研究生,主要从事地质灾害研究。E-mail:dzzxy2011@163.com
通讯作者: 张春山(1964-),男,研究员,博士,主要从事地质灾害、地应力、环境地质等方面的工作。E-mail:zhangcs401@sina.com
更新日期/Last Update: 2018-07-15