Skip to main content
SpringerLink
Log in

Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake

  • Published:
Journal of Mountain Science Aims and scope Submit manuscript

Abstract

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas. The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability. Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone, with similar topographical and geological conditions. The two earthquakes are both featured by thrust fault and similar seismic mechanism. This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake. Six influencing parameters were taken into consideration: distance from the seismic fault, slope gradient, lithology, distance from drainage, elevation and Peak Ground Acceleration (PGA). The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan, Baoxing and Tianquan counties. The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work. The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area. The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the Environment 58(1): 21–44.

    Article  Google Scholar 

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65(1–2):15–31.

    Article  Google Scholar 

  • Aykut A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey. Landslide 9(1):93–106.

    Article  Google Scholar 

  • Brenning A (2005). Spatial prediction models for landslide hazards: review, comparison and evaluation. Natural Hazards and Earth System Sciences 5:853–862.

    Article  Google Scholar 

  • Chang M, Tang C, Li, WL, et al. (2013) Image interpretation and spatial analysis of geohazards induced by“4.20”Lushan earthquake in epicenter area. Journal of Chengdu University of Technology 40:275–281. (In Chinese)

    Google Scholar 

  • Chen X, Yu L, Wang M, et al. (2013) Brief communication: landslides triggered by the Ms=7.0 Lushan earthquake, China. Natural Hazards and Earth System Sciences (1): 3891–3918. DOI: 10.5194/nhessd-1-3891-2013.

    Google Scholar 

  • Chen ZH, Wang JF (2007) Landslide hazard mapping using logistic regression model in Mackenzie Valley, Canada. Nat Hazards 42(1):75–89.

    Article  Google Scholar 

  • China Seismological Bureau (2013a) The fault rupture of the Apr. 20, 2013, Lushan Earthquake is about 40km and the maximum displacement is 1.6m. (2013-04-23). Available online: http://www.cea.gov.cn/publish/dizhenj/468/553/100342/100343/20130423205445248545384/index.html. (2013-04-23) (In Chinese)

    Google Scholar 

  • China Seismological Bureau (2013b) There are 5084 recorded aftershocks after the Apr. 20, 2013, Ms 7.0 Lushan Earthquake. (2013-04-26). http://www.eqsc.gov.cn/zt/ljysdzzt_2191/yztj/201304/t20130426_26030.html. (In Chinese)

    Google Scholar 

  • China Seismological Bureau (2013c) The seismic intensity map of the Apr. 20, 2013, Lushan Earthquake. (2013-04-25). http://www.cea.gov.cn/publish/dizhenj/464/478/20130425153642550719811/index.html. (In Chinese)

    Google Scholar 

  • Chinese Academy of Sciences (2013) The preliminary results of the fault rupture process inversion. (2013-04-24). http://www.stdaily.com/special/content/2013-04/24/content_596813.htm. (In Chinese)

    Google Scholar 

  • Chinese Information Office of the State Council (2013) The press conference of 4.20 Ms 7.0 Lushan Earthquake holed by Chinese Information Office of the State Council. (2013-04-26). http://www.eqsc.gov.cn/zt/ljysdzzt_2191/zhbd/201304/t20130426_26027.html. (In Chinese)

    Google Scholar 

  • Chung CJF, Fabbri AG (2003) Validation of spatial prediction models foreland slide hazard mapping. Natural Hazards, 30(3):451–472.

    Article  Google Scholar 

  • Das I, Stein A, Kerle N, et al. (2012) Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models. Geomorphology 179:116–125.

    Article  Google Scholar 

  • Devkota KC, Regmi AD, Pourghasemi HR, et al. (2013) Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models and their comparison at a landslide prone area in Nepal Himalaya. Natural Hazards 65(1):135–165. DOI: 10.1007/s11069-012-0347-6

    Article  Google Scholar 

  • Dong JJ, Tung YH, Chen CC, et al. (2011) Logistic regression model for predicting the failure probability of a landslide dam. Engineering Geology 117:52–61.

    Article  Google Scholar 

  • Huang RQ, Li WL (2009a) Fault effect analysis of geo-hazards triggered by Wenchuan Earthquake. Journal of Engineering Geology, 2009, 17(1): 19–28. (In Chinese)

    Google Scholar 

  • Huang RQ, Li WL (2009b) Analysis of the geo-hazards triggered by the 12 May 2008 Wenchuan Earthquake, China. Bull of Engineering Geology and the Environment, 2009, 68: 363–371.

    Article  Google Scholar 

  • Huang RQ, Li WL (2009c) Development and distribution of geohazards triggered by the 5.12 Wenchuan Earthquake in China. Science in China Series E-Technological Sciences, 2009, 52(4): 810–19.

    Article  Google Scholar 

  • Huang RQ, Li WL (2009d) Analysis of the number and density of landslides triggered by the 2008 Wenchuan Earthquake, China. Journal of Geological Hazards and Environment Preservation, 2009, 20(3): 1–7. (In Chinese)

    Google Scholar 

  • Keefer DK (1984) Landslides caused by earthquakes. Geological Society of America Bulletin, 1984, 95: 406–421.

    Article  Google Scholar 

  • Li WL (2013) The rapid prediction maps of the geo-hazards triggered by Lushan earthquake Ya’an, China. (2013-04-22). http://www.sklgp.com/default.aspx?id=9&subid=2&newsid=616. (In Chinese)

    Google Scholar 

  • Li WL, Huang RQ, Tang C, et al. (2013) Co-seismic landslide inventory and susceptibility mapping in the 2008 Wenchuan earthquake disaster area, China. Journal of Mountain Science, 10(3): 339–354.

    Article  Google Scholar 

  • Lulseged A, Hiromitsu Y (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65(1–2):15–31.

    Google Scholar 

  • Pei XJ, Huang RQ (2013) Analysis of characteristics of geological hazards by “4.20” Lushan earthquake in Sichuan, China. Journal of Chengdu University of Technology. 40:257–263 (In Chinese)

    Google Scholar 

  • Pradhan B (2010a) Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia. Advances in Space Research 45(10):1244–1256.

    Article  Google Scholar 

  • Pradhan B (2010b) Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia. Advances in Space Research 45(10):1244–1256. DOI: 10.1016/j.asr.2010.01.006

    Article  Google Scholar 

  • Pradhan B (2011) Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modeling. Environmental and Ecological Statistics 18(3)4:71–493. DOI: 10.1007/s10651-010-0147-7

    Google Scholar 

  • Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: back propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling. Environmental Modeling and Software 25(6): 747–759. DOI: 10.1016/j.envsoft.2009.10.016

    Article  Google Scholar 

  • Ramani SE, Pitchaimani K, Gnanamanickam VR (2011). GIS based landslide susceptibility mapping of tevankarai Ar Subwatershed, Kodaikkanal, India using binary logistic regression analysis. Journal of Mountain Science 8:505–517.

    Article  Google Scholar 

  • Sichuan Bureau of Surveying and Geographic Information (2013) New interpretation result of co-seismic landslides triggered by Lushan earthquake until April 29, 2013. (2013-05-03). http://www.scbsm.com/cgxx/chyw/8450.htm. (In Chinese)

    Google Scholar 

  • Soeters R, Westen CJ (1996) Slope instability recognition, analysis, and zonation. In Turner, K.A. & Schuster, R.L. (eds), Landslides: investigation and mitigation 247:129–177. Washington, D.C.: Transport Research Board.

    Google Scholar 

  • Su FH, Cui P, Zhang JQ, et al. (2010) Susceptibility Assessment of Landslides Caused by Wenchuan earthquake Using a Logistic Regression Model. J. Mt. Sci. 7(3): 234–245.

    Article  Google Scholar 

  • USGS (2013) M6.6 — 52km WSW of Linqiong, China. (2013-04-20), http://earthquake.usgs.gov/earthquakes/eventpage/usb000gcdd#summary.

    Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. Praris: UNESCO Press.

    Google Scholar 

  • Wang WM, He JL, Yao ZX (2013) Preliminary result for rupture process of Apr. 20, 2013, Mw6.7 Earthquake, Lushan, Ya’an, China. (2013-04-20). http://www.igg.cas.cn/xwzx/zhxw/201304/t20130420_3823903.html. (In Chinese)

    Google Scholar 

  • Xu C, Xiao J (2013) Spatial analysis of landslides triggered by the 2013 Ms.7.0 Lushan earthquake: a case study of a typical rectangle area in the northeast of Taiping town. Seismology and Geology 35: 436–451. (In Chinese)

    Google Scholar 

  • Xu C, Xu XW, Dai FC, et al. (2012) Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China. Computers & Geosciences 46:317–329.

    Article  Google Scholar 

  • Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: A comparison of logistic regression and neural networks in a medium scale study, Handed region (Turkey). Engineering Geology 79(3–4): 251–266.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China

    Wei-le Li, Run-qiu Huang, Qiang Xu & Chuan Tang

Authors
  1. Wei-le Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Run-qiu Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qiang Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chuan Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei-le Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, Wl., Huang, Rq., Xu, Q. et al. Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake. J. Mt. Sci. 10, 699–715 (2013). https://doi.org/10.1007/s11629-013-2786-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11629-013-2786-2

Keywords

Search

Navigation