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

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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.

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Acknowledgments

This work has been funded by the National Natural Science Foundation of China (Grant No. 41101164 and 41371185), the Project Group of Knowledge Innovation Program of Chinese Academy Sciences (KZCX2-YW-Q03-5) and the National Basic Research Program of China (973 Program) (Grant No. 2011CB409902).

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Correspondence to Kaiheng Hu.

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Ding, M., Hu, K. Susceptibility mapping of landslides in Beichuan County using cluster and MLC methods. Nat Hazards 70, 755–766 (2014). https://doi.org/10.1007/s11069-013-0854-0

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  • DOI: https://doi.org/10.1007/s11069-013-0854-0

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