Susceptibility mapping of landslides in Beichuan County using cluster and MLC methods

Mingtao Ding () and Kaiheng Hu ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2014, vol. 70, issue 1, 755-766

Abstract: Cluster analysis and maximum likelihood classification (MLC) are exploited to map the post-earthquake landslide susceptibility in Beichuan County that was affected by the Ms 8.0 Wenchuan earthquake. The methodology is applicable even if there is short of training data. Six effective factors are chosen for mapping the susceptibility, including land use, seismic intensity, average annual rainfall, relative relief, slop gradient and lithology. Four clusters are grouped from sampling grid cells by k-means clustering approach. MLC classifies all the cells in the study area into the four clusters according to their statistical characteristics. Four susceptibility classes (extreme low, low, moderate and high) are assigned to these clusters applying expert experience and hazard density. The final map gives a reasonable assessment of post-earthquake landslide susceptibility in Beichuan County. Comparing with the pre-earthquake susceptibility map made in Beichuan County geological disaster survey project, the result t using cluster and MLC classification has a better agreement with the dot density value of post-earthquake landslides in Beichuan County. The susceptibility map can be used to identify safety spots within the high danger area, which are suitable for habitations and facilities. It is also found that more landslides are densely concentrated at the boundary between high and moderate regions, and between high and extreme low regions. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Susceptibility mapping; Landslide; Clustering analysis; Beichuan County (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11069-013-0854-0 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:70:y:2014:i:1:p:755-766

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-013-0854-0

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().