1Department of Geology, National Environmental Agency, Ministry of Environment and Natural Resources Protection of Georgia, Tbilisi, Georgia 2Institute of Geo-Information Science and Earth Observation (ITC) of the University of Twente, Enschede, The Netherlands. Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China. Department of Public Works and Town & Country Planning, Ministry of Interior, Bangkok, Thailand. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China. School of Environmental Sciences, University of Guelph, Guelph, Canada.
To quantitatively assess the landslide hazard in Khelvachauri, Georgia, the statistic method of hazard index was applied. A spatial database was constructed in Geographic Information System (GIS) including topographic data, geologic maps, land-use, and active landslide events (extracted from the landslide inventory). After that, causal factors of landslides (such as slope, aspect, lithology, geomorphology, land-use and soil depth) were produced to calculate the corresponding weights, and thereby we defined a relevant set of spatial criteria for the latter landslide hazard assessment. On top of that, susceptibility assessment was performed in order to classify the area to low, moderate and high susceptible regions. Results showed that NW aspect, mountain geomorphology, private land-use, laterite loam and clay, slope between 19 to 24 degrees, and soil depth between 10 - 20 cm were found to have the largest contribution to high landslide susceptibility. The high success rate (72.35%) was obtained using area under the curve from the landslide susceptibility map. Meanwhile, effect analysis was carried out to assess the accuracy of the landslide susceptibility, indicating that the factor of slope played the most important role in determining the occurring probability of landslide although it did not deviate as much as other factors. Finally, the vulnerability analyses were carried out by means of the Spatial Multi-Criteria Estimation model, which in turn, led to the risk assessment. It turned out that not so much of the number of buildings (~ 34.13%) was associated with high-risk zone and that governmental and private land-use almost accounted for the same risk (39.9% and 40.9%, respectively).
Gaprindashvili, G. , Guo, J. , Daorueang, P. , Xin, T. and Rahimy, P. (2014) A New Statistic Approach towards Landslide Hazard Risk Assessment. International Journal of Geosciences, 5, 38-49. doi: 10.4236/ijg.2014.51006.
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