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Earthquake induced landslide (EIL) is the most hazardous secondary disaster triggered by the earthquake. To reduce the secondary damage of EIL, we need to know where is more susceptible to EIL and take actions. And this can be projected using the information of EIL points after one earthquake and the natural conditions in the related area. The aim of this study is to make a map of an area about where it is more susceptible to EIL.
Workflow
Workflow
The Wenchuan earthquake of Ms 8.0 on May 24th, 2008, was studied for this project. Beichuan County, which suffered the most in the earthquake, was selected as the study area.
Data
Data
A landslide inventory was needed to show where the landslide points triggered by Wenchuan Earthquake are. This was provided in ScienceBase.
A series of contributing factors should be utilised to analyse the susceptibility based on the landslide inventory. Six factors were selected:
Land Cover: from ESA Climate Change Initiative
Geology Period: from National Geology Archives of China
Peak Ground Acceleration: form USGS
Elevation: SRTM data from International Centre for Tropical Agriculture
Slope: Derived from DEM in QGIS
Aspect: Derived from DEM in QGIS
Method
Method
The frequency ratio (FR) method was introduced to calculate the landslide susceptibility index (LSI) of Beichuan county. The basic principle was to reclassify the contributing factors to be the sub-classes first, calculate the FR value using Eq.1 and get the LSI value using Eq.2 . The calculation was based on each pixel. And the result was mapped based on the classification of LSI.
Result
Result
By Natural Breaks
By Natural Breaks
Natural Breaks result showed very salient and compact high susceptibility area, which could make decision-making for risk management more focused and economical. It could also reflect the distribution of LSI value. But sometimes the extreme value would interfere the visualisation in other areas. And the extreme value could come from coincidence in this project like the Cambrian period zone may overlap this narrow high susceptibility area by accident.
By Quantiles
By Quantiles
The Quantile result, influenced less by extreme value, fitted well with the landslides points and covered some details. But it showed more high susceptibility areas, resulting in more costly decision-making. It is suitable for the general mark of the susceptibility level. So, for the preferences of different groups, I reserved both maps as my results.
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