基于信息量模型的滑坡灾害易发性评价——以重庆市为例

doi:10.16843/j.sswc.2023.06.006

Abstract
Figure/Table
References
Related Citation (13)

Download: PDF (9587 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract [Background] Affected by four types of factors: topography, geology, hydrological environment and human activities, landslide disasters occur frequently in Chongqing, with the distribution characteristics of “many points and wide areas”. The frequency of landslide disasters has caused huge casualties, property damage and ecological damage. Regional landslide susceptibility assessment is one of the effective measures for disaster prevention and control, which is of great significance to the government to carry out disaster risk management. The susceptibility evaluation was conducted at Chongqing city where landslide disaster seriously developed. [Methods] Elevation, slope, aspect, lithology, distance from construction, distance from water system, rainfall, soil type, land use, distance from road and the normalized difference vegetation index(NDVI) were selected as the influencing factors affecting the development of landslides. The band set statistical tool of ArcGIS was used to test the correlation, and the factors with strong correlation were eliminated to form a landslide susceptibility evaluation index system. Based on the sample data of 8 756 historical landslide disaster sites from 2000 to 2020, with the support of remote sensing(RS) and geographic information system(GIS), the weighted information value model was used to evaluate the landslide susceptibility in the study area. [Results] 1) Based on the results of relevant analysis, the elevation factor was eliminated. 2) The main factors affecting the landslide development in the study area were water system, NDVI and slope. Among which the top 5 values of weighted information were: the distance was between 200 m and 500 m from water system(0.809), the NDVI was between 8% and 38%(0.563), the slope was between 13°and 20°(0.500), the distance was between 0 m and 200 m from water system(0.429), the distance was between 500 m and 1 000 m from water system(0.428). 3) The high and relatively high susceptibility areas accounted for 17.26% and 31.82% of the study area respectively, and the spatial distribution of relatively high susceptibility areas was highly consistent with the distribution of water system. [Conclusions] The research area is mainly dominated by high susceptibility area and medium susceptibility area, and the assessment accuracy of the weighted information value model is about 78.20%, which can better reflect the landslide disaster situation in Chongqing. The results provide technical reference for the prediction of landslide disaster in Chongqing and the government's disaster prevention and mitigation work.

Key words： weighted information value model geographic information system landslide susceptibility assessment Chongqing city

Received: 04 November 2022

PACS:	S157.1
	P684

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WANG Jiani
	WANG Yunqi
	LI Yaoming
	WEI Shang
	LI Cheng
	WANG Yujie
	QI Haimei

Cite this article:

WANG Jiani,WANG Yunqi,LI Yaoming, et al. Landslide susceptibility assessment based on weighted information value model:A case study of Chongqing city[J]. SSWC, 2023, 21(6): 53-62.

URL:

http://journal12.magtechjournal.com/Jweb_stbc/EN/10.16843/j.sswc.2023.06.006 OR http://journal12.magtechjournal.com/Jweb_stbc/EN/Y2023/V21/I6/53

[1]	李玉生.重庆市三峡库区若干重大地质灾害隐患[J].中国地质灾害与防治学报,2010,21(1):133.LI Yusheng.Hidden dangers of some major geological hazards in the Three Gorges Reservoir Area of Chongqing[J].The Chinese Journal of Geological Hazard and Control,2010,21(1):133.
[2]	毛华锐,孙小飞,周颖智.基于频率比-投影寻踪模型的渝东北三峡库区滑坡敏感性制图[J].科学技术与工程,2022,22(5):1803.MAO Huarui,SUN Xiaofei,ZHOU Yingzhi.Mapping landslide susceptibility of the Three Gorges Reservoir Area in northeast Chongqing using the frequency ration and projection pursuit model[J].Science Technology and Engineering,2022,22(5):1803.
[3]	田春阳,张威,张戈,等.基于信息量法的西丰县地质灾害易发性评价[J].首都师范大学学报(自然科学版),2020,41(2):32.TIAN Chunyang,ZHANG Wei,ZHANG Ge,et al.Evaluation of geological disaster vulnerability in Xifeng County based on information content method[J].Journal of Capital Normal University:Natural Science Edition,2020,41(2):32.
[4]	郭子正,殷坤龙,付圣,等.基于GIS和WOE-BP模型的滑坡易发性评价[J].地球科学,2019,44(12):4299.GUO Zizheng,YIN Kunlong,FU Sheng,et al.Evaluation of landslide susceptibility based on GIS and WOE-BP model[J].Earth Science,2019,44(12):4299.
[5]	郭子正,殷坤龙,黄发明,等.基于滑坡分类和加权频率比模型的滑坡易发性评价[J].岩土力学与工程学报,2019,38(2):287.GUO Zizheng,YIN Kunlong,HUANG Faming,et al.Evaluation of landslide susceptibility based on landslide classification and weighted frequency ratio model[J].Chinese Journal of Rock Mechanics and Engineering,2019,38(2):287.
[6]	周超,殷坤龙,曹颖,等.基于集成学习与径向基神经网络耦合模型的三峡库区滑坡易发性评价[J].地球科学,2020,45(6):1865.ZHOU Chao,YIN Kunlong,CAO Ying,et al.Landslide susceptibility assessment by applying the coupling method of radial basis neural network and adaboost:A case study from the Three Gorges Reservoir Area[J].Earth Science,2020,45(6):1865.
[7]	吴润泽,胡旭东,梅红波,等.基于随机森林的滑坡空间易发性评价:以三峡库区湖北段为例[J].地球科学,2021,46(1):321.WU Runze,HU Xudong,MEI Hongbo,et al.Spatial susceptibility assessment of landslides based on random forest:A case study from Hubei section in the Three Gorges Reservoir Area[J].Earth Science,2021,46(1):321.
[8]	YESILNACAR C,TOPAL T.Landslide susceptibility mapping:A comparison od logistic regression and neural networks methods in a medium scale study,Hendek region (Turkey)[J].Engineering Geology,2005,79(3/4):251.
[9]	SUN Deliang,WEN Haijia,WANG Danzhou,et al.A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm[J].Geomorphology,2020,362:208201.
[10]	SAHANA M,SAJJAD H.Evaluating effectiveness of frequency ratio,fuzzy logic and logistic regression models in assessing landslide susceptibility:A case from Rudraprayag district,India[J].Journal of Mountain Science,2017,14(11):2150.
[11]	王佳佳,殷坤龙,肖莉丽.基于GIS和信息量的滑坡灾害易发性评价:以三峡库区万州区为例[J].岩土力学与工程学报,2014,33(4):797.WANG Jiajia,YIN Kunlong,XIAO Lili.Landslides susceptibility assessment based on GIS and weighted information value:A case study of Wanzhou district,Three Gorges Reservoir[J].Chinese Journal of Rock Mechanic and Engineering,2014,33(4):797.
[12]	黄发明,殷坤龙,蒋水华,等.基于聚类分析和支持向量机的滑坡易发性评价[J].岩土力学与工程学报,2018,37(1):156.HUANG Faming,YIN Kunlong,JIANG Shuihua,et al.Landslide susceptibility assessment based on clustering analysis and support vector machine[J].Chinese Journal of Rock Mechanic and Engineering,2018,37(1):156.
[13]	张俊.三峡库区万州区滑坡灾害风险评估研究[D].武汉:中国地质大学,2016:18.ZHANG Jun.Landslide risk assessment in Wanzhou county,Three Reservoir Region[D].Wuhan:China University of Geology,2016:18.
[14]	冯国建,王婷婷.某高速公路不同坡向情况下的边坡稳定性分析研究[J].北方交通,2021,335(3):44.FENG Guojian,WANG Tingting.Analysis and research on slope stability of an expressway under different aspects[J].Northern Communications,2021,335(3):44.
[15]	曹运江,黄润秋,郑海军,等.岷江上游某水电站工程边坡软岩的崩解特性研究[J].工程地质学报,2006,14(1):35.CAO Yunjiang,HUANG Runqiu,ZHENG Haijun,et al.Slaking characteristics of soft rock of the engineering slope in a hydroelectric station in the southwest of China[J].Journal of Engineering Geology,2006,14(1):35.
[16]	徐辉,刘海知.诱发滑坡的多尺度降雨特征[J].山地学报,2019,37(6):858.XU Hui,LIU Haizhi.Multi-scale rainfall characteristics of rainfall-induced landslides[J].Mountain Research,2019,37(6):858.
[17]	肖捷夫,李云安,胡勇,等.库水涨落和降雨条件下古滑坡变形特征模型试验研究[J].岩土力学,2021,42(2):471.XIAO Jiefu,LI Yun'an,HU Yong,et al.Model tests on deformation characteristics of ancient bank landslide under water level fluctuation and rainfall[J].Rock and Soil Mechanics,2021,42(2):471.
[18]	ELENA B M,SAMUELE S,VERONCIA T.Root reinforcement in slope stability models:A review[J].Geosciences,2021,11(5):212.
[19]	张晓东,刘湘南,赵志鹏,等.基于像元二分法的盐池县植被覆盖度与地质灾害点时空格局分析[J].国土资源遥感,2018,30(2):195.ZHANG Xiaodong,LIU Xiangnan,ZHAO Zhipeng,et al.Spatial-temporal pattern analysis of the vegetation coverage and geological hazards in Yanchi county based on dimidiate pixel model[J].Remote Sensing for Land & Resources,2018,30(2):195.