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Frontiers of Structural and Civil Engineering

Front. Struct. Civ. Eng.    2020, Vol. 14 Issue (1) : 123-126     https://doi.org/10.1007/s11709-019-0582-y
RESEARCH ARTICLE
Factor analysis for the statistical modeling of earthquake-induced landslides
Jeng-Wen LIN1(), Meng-Hsun HSIEH2, Yu-Jen LI3
1. Department of Civil Engineering, Feng Chia University, Taichung 40724, China
2. School of Management, Fujian University of Technology, Fuzhou 350118, China
3. Ruentex Engineering & Construction Co., Ltd., Taipei 10492, China
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Abstract

Earthquake-induced landslides are difficult to assess and predict owing to the inherent unpredictability of earthquakes. In most existing studies, the landslide potential is statistically assessed by collecting and analyzing the data of historical landslide events and earthquake observation records. Unlike rainfall-induced landslides, earthquake-induced landslides cannot be predicted in advance using real-time monitoring systems, and the development of the models for these landslides should instead depend on early earthquake warnings and estimations. Hence, in this study, factor analysis was performed and the frequency distribution method was employed to investigate the potential risk of the landslides caused by earthquakes. Factors such as the slope gradient, lithology (geology), aspect, and elevation were selected and classified as influential factors to facilitate the construction of a landslide database for the area of study.

Keywords earthquake      factor analysis      slope landslides      statistical modeling     
Corresponding Authors: Jeng-Wen LIN   
Just Accepted Date: 20 September 2019   Online First Date: 19 November 2019    Issue Date: 21 February 2020
 Cite this article:   
Jeng-Wen LIN,Meng-Hsun HSIEH,Yu-Jen LI. Factor analysis for the statistical modeling of earthquake-induced landslides[J]. Front. Struct. Civ. Eng., 2020, 14(1): 123-126.
 URL:  
http://journal.hep.com.cn/fsce/EN/10.1007/s11709-019-0582-y
http://journal.hep.com.cn/fsce/EN/Y2020/V14/I1/123
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Articles by authors
Jeng-Wen LIN
Meng-Hsun HSIEH
Yu-Jen LI
authors year potential factors
gradient lithology aspect vegetation elevation peak ground acceleration distance to rivers distance to faults slope height distance to epicenter distance to roads distance to tectonic lines
Barredo et al. [19] 2000
Liao [16] 2000
Dai et al. [20] 2001
Lee et al. [21] 2002
Lin [22] 2003
Ercanoglu et al. [23] 2004
Suzen and Doyuran [24] 2004
Gomez and Kavzoglu [25] 2005
Wen [18] 2005
Feng [26] 2007
Chen [27] 2008
Chen [28] 2009
Lee [29] 2010
Liu [30] 2014
frequency of selection 72 66 52 32 39 13 28 23 5 4 7 2
Tab.1  Factors  extracted from the landslide-related articles from 1985 to 2014
item value
KMO MSA 0.6
Bartlett’s test of sphericity approximate chi-square value 119
significance 0
Tab.2  KMO  and Bartlett’s tests for the factors that affect the potential of slope landslides
Fig.1  Scree  plot for the 12 factors that affect the potential of slope landslides.
1 X P Bai, Y N Liu. Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method. Frontiers of Structural and Civil Engineering, 2016, 10(4): 462–471
https://doi.org/10.1007/s11709-016-0361-y
2 L Sun, J Chen, T Li. A MODIS-based method for detecting large-scale vegetation disturbance due to natural hazards: A case study of Wenchuan earthquake stricken regions in China. Stochastic Environmental Research and Risk Assessment, 2016, 30(8): 2243–2254
https://doi.org/10.1007/s00477-015-1160-z
3 H Takabatake, M Matsuoka. Origin of the anomalously large upward acceleration associated with the 2008 Iwate-Miyagi Nairiku earthquake. Earthquakes and Structures, 2012, 3(5): 675–694
https://doi.org/10.12989/eas.2012.3.5.675
4 J Torizin. Elimination of informational redundancy in the weight of evidence method: An application to landslide susceptibility assessment. Stochastic Environmental Research and Risk Assessment, 2016, 30(2): 635–651
https://doi.org/10.1007/s00477-015-1077-6
5 K K S Ho, R W M Cheung, C Y S Wong. Managing landslide risk systematically using engineering works. Proceedings of the Institution of Civil Engineers-Civil Engineering, 2016, 169(6): 25–34
https://doi.org/10.1680/jcien.15.00079
6 T Rabczuk, P M A Areias. A new approach for modelling slip lines in geological materials with cohesive models. International Journal for Numerical and Analytical Methods in Geomechanics, 2006, 30(11): 1159–1172
https://doi.org/10.1002/nag.522
7 W Wu, X Zhuang, H Zhu, X Liu, G Ma. Centroid sliding pyramid method for removability and stability analysis of fractured hard rock. Acta Geotechnica, 2017, 12(3): 627–644
https://doi.org/10.1007/s11440-016-0510-4
8 W Zheng, X Zhuang, D D Tannant, Y Cai, S Nunoo. Unified continuum/discontinuum modeling framework for slope stability assessment. Engineering Geology, 2014, 179: 90–101
https://doi.org/10.1016/j.enggeo.2014.06.014
9 G B Crosta, S Imposimato, D G Roddeman. Numerical modelling of large landslides stability and runout. Natural Hazards and Earth System Sciences, 2003, 3(6): 523–538
https://doi.org/10.5194/nhess-3-523-2003
10 B Di, C A Stamatopoulos, M Dandoulaki, E Stavrogiannopoulou, M Zhang, P Bampina. A method predicting the earthquake-induced landslide risk by back analyses of past landslides and its application in the region of the Wenchuan 12/5/2008 earthquake. Natural Hazards, 2017, 85(2): 903–927
https://doi.org/10.1007/s11069-016-2611-7
11 T F Fathani. The analysis of earthquake-induced landslides with a three-dimensional numerical model. In: Proceedings of Geotechnics symposium. Yogyakarta: Gajah Mada University, 2006, 159–165
12 S McDougall, O Hungr. A model for the analysis of rapid landslide motion across three-dimensional terrain. Canadian Geotechnical Journal, 2004, 41(6): 1084–1097
https://doi.org/10.1139/t04-052
13 M Pastor, B Haddad, G Sorbino, S Cuomo, V Drempetic. A depth-integrated coupled SPH model for flow-like landslides and related phenomena. International Journal for Numerical and Analytical Methods in Geomechanics, 2009, 33(2): 143–172
https://doi.org/10.1002/nag.705
14 C Stamatopoulos, B Di. Analytical and approximate expressions predicting post-failure landslide displacement using the multi-block model and energy methods. Landslides, 2015, 12(6): 1207–1213
https://doi.org/10.1007/s10346-015-0638-6
15 Y J Li. Development of earthquake-induced landslide fragility curves using an empirical statistical model. Thesis for the Master’s Degree. Taichung, China: Feng Chia University, 2016
16 H W Liao. Landslides triggered by Chi-Chi Earthquake. Thesis for the Master’s Degree. Taoyuan, China: Central University, 2000
17 W N Wang, C Y Yin, Z Q Chen, M Q Li. The current situation of landslide areas in the 921 earthquake and disaster prevention. In: Proceedings of the Sino-Japan Sediment Disaster Investigation and Management Symposium after the 921 Earthquake. Nantou: Soil and Water Conservation Bureau, 2000, 79–90
18 C Y Wen. A landslide model analysis with combining factors of earthquake and typhoon. Thesis for the Master’s Degree. Tainan, China: Cheng Kung University, 2005
19 J I Barredo, A Benavides, J Hervas, C J van Westen. Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain. International Journal of Applied Earth Observations & Geoinformation, 2000, 2(1): 9–23
https://doi.org/10.1016/S0303-2434(00)85022-9
20 C F Lee, J Li, Z W Xu, F C Dai. Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environmental Geology, 2001, 40(3): 381–391
https://doi.org/10.1007/s002540000163
21 S R Lee, U Chwae, K Min. Landslide susceptibility mapping by correlation between topography and geological structure: The Janghung area, Korea. Geomorphology, 2002, 46(3–4): 149–162
https://doi.org/10.1016/S0169-555X(02)00057-0
22 Y H Lin. Application of neural network to landslide susceptibility analysis. Thesis for the Master’s Degree. Taoyuan, China: Central University, 2003
23 M Ercanoglu, C Gokceoglu, Th W J van Asch. Landslide susceptibility zoning north of Yenice (NW Turkey) by multivariate statistical techniques. Natural Hazards, 2004, 32(1): 1–23
https://doi.org/10.1023/B:NHAZ.0000026786.85589.4a
24 M L Süzen, V Doyuran. A comparison of the GIS based landslide susceptibility assessment methods: Multivariate versus bivariate. Environmental Geology, 2004, 45(5): 665–679
https://doi.org/10.1007/s00254-003-0917-8
25 H Gómez, T Kavzoglu. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Engineering Geology, 2005, 78(1–2): 11–27
https://doi.org/10.1016/j.enggeo.2004.10.004
26 Z X Feng. Assessment of vegetation recovery for earthquake-induced landslides at the Chiufanershan Area. Thesis for the Master’s Degree. Changhua, China: Ming Dao University, 2007
27 Y S Chen. An influence of earthquake on the occurrence of landslide and debris flow. Dissertation for the Doctoral Degree. Tainan, China: Cheng Kung University, 2008
28 C H Chen. A study of the occurrence of landslides after the Chi-Chi Earthquake in the Lao-Nong River Watershed. Thesis for the Master’s Degree. Tainan, China: Cheng Kung University, 2009
29 S T Lee. The analysis of potential in heavy rainfall-induced landslides affected by the attenuation pattern of ground disturbing after a major seismic event. Dissertation for the Doctoral Degree. Tainan, China: Cheng Kung University, 2010
30 Y S Liu. Characteristics and spatial differences of debris flow and landslide occurrences in the Headstreams of Chenyoulan River: With the Hoshe Basin as an example. Dissertation for the Doctoral Degree. Taipei, China: Taiwan Normal University, 2014
31 W Z Liang, G Y Zhao, H Wu. Evaluating investment risks of metallic mines using an extended TOPSIS method with linguistic neutrosophic numbers. Symmetry, 2017, 9(8): 149
32 H Y Chiu, H D Bih, M Liou, K S Yang. Research methods on social and behavior science: Data analysis. Taipei, China: Tung Hua Book Co. Ltd., 2015
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