International Journal of Geosciences, 2014, 5, 38-49 Published Online January 2014 (http://www.scirp.org/journal/ijg ) http://dx.doi.org/10.4236/ijg.2014.51006 A New Statistic Approach towards Landslide Hazard Risk Assessment George Gaprindashvili 1,2* , Jianping Guo 3 , Panisara Daorueang 4 , Tian Xin 5 , Pooyan Rahimy 6 1 Department of Geology, National Environmental Agency, Ministry of Environment and Natural Resources Protection of Georgia, Tbilisi, Georgia 2 Institute of Geo-Information Science and Earth Observation (ITC) of the University of Twente, Enschede, The Netherlands 3 Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China 4 Department of Public Works and Town & Country Planning, Ministry of Interior, Bangkok, Thailand 5 Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China 6 School of Environmental Sciences, University of Guelph, Guelph, Canada Email: * gaprinda1609@yahoo.com , * gaprindashvili.george@gmail.com Received November 13, 2013; revised December 15, 2013; accepted January 3, 2014 Copyright © 2014 George Gaprindashvili et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property George Gaprindashvili et al. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. ABSTRACT 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, pri- vate 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 ob- tained 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 im- portant 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). KEYWORDS Landslide; Weight; Susceptibility; Vulnerability; Statistic 1. Introduction Nowadays, quantitative landslide assessment is still in- adequate due to too limited resources available for re- search, such as historic records of landslides and detailed socio-economic elements at risk. In particular, there are no enough data available in order to construct a proba- bilistic model of landslides at different magnitudes that leads to a quantitative risk assessment. Most convention- al landslide studies are descriptive and qualitative; there- fore, it is imperative for data-driven assessment in com- bination with in-depth knowledge of all the causal factors for landslide. The quantitative approach applied in this study, is of great importance for the benefit of the gov- ernment decision-makers, the urban planners and ulti- * Corresponding author. OPEN ACCESS IJG