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Journal of Mountain Science

, Volume 10, Issue 3, pp 339–354 | Cite as

Co-seismic landslide inventory and susceptibility mapping in the 2008 Wenchuan earthquake disaster area, China

  • Wei-le LiEmail author
  • Run-qiu Huang
  • Chuan Tang
  • Qiang Xu
  • Cees van Westen
Article

Abstract

The Ms 8.0 May 12, 2008 Wenchuan earthquake triggered tens of thousands of landslides. The widespread landslides have caused serious casualties and property losses, and posed a great threat to post-earthquake reconstruction. A spatial database, inventoried 43,842 landslides with a total area of 632 km2, was developed by interpretation of multi-resolution remote sensing images. The landslides can be classified into three categories: swallow, disrupted slides and falls; deep-seated slides and falls, and rock avalanches. The correlation between landslides distribution and the influencing parameters including distance from co-seismic fault, lithology, slope gradient, elevation, peak ground acceleration (PGA) and distance from drainage were analyzed. The distance from co-seismic fault was the most significant parameter followed by slope gradient and PGA was the least significant one. A logistic regression model combined with bivariate statistical analysis (BSA) was adopted for landslide susceptibility mapping. The study area was classified into five categories of landslide susceptibility: very low, low, medium, high and very high. 92.0% of the study area belongs to low and very low categories with corresponding 9.0% of the total inventoried landslides. Medium susceptible zones make up 4.2% of the area with 17.7% of the total landslides. The rest of the area was classified into high and very high categories, which makes up 3.9% of the area with corresponding 73.3% of the total landslides. Although the susceptibility map can reveal the likelihood of future landslides and debris flows, and it is helpful for the rebuilding process and future zoning issues.

Keywords

Wenchuan Earthquake Landslide Inventory Susceptibility mapping Logistic regression 

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Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Wei-le Li
    • 1
    • 2
    Email author
  • Run-qiu Huang
    • 1
  • Chuan Tang
    • 1
  • Qiang Xu
    • 1
  • Cees van Westen
    • 2
  1. 1.State key Laboratory of Geohazard Prevention and Geoenvironment ProtectionChengdu University of TechnologyChengduChina
  2. 2.Faculty of Geoinformation Science and Earth Observation (ITC)University of TwenteEnschedeThe Netherlands

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