IJG  Vol.5 No.1 , January 2014
A New Statistic Approach towards Landslide Hazard Risk Assessment
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, 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).


Cite this paper
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.
References
[1]   A. Clerici, S. Perego, C. Tellini and P. Vescovi, “A Procedure for Landslide Susceptibility Zonation by the Conditional Analysis Method,” Geomorphology, Vol. 48, No. 4, 2002, pp. 349-364.
http://dx.doi.org/10.1016/S0169-555X(02)00079-X

[2]   E. M. Lee and D. K. C. Jones, “Landslide Risk Assessment,” Thomas Telford, London, 2004.
http://dx.doi.org/10.1680/lra.31715

[3]   W. J. Kockelman, “Some Techniques for Reducing Landslide Hazards,” Association of Environmental and Engineering Geologists, Vol. 23, No. 1, 1986, pp. 29-52

[4]   UNDRO, “Mitigating Natural Disasters,” Phenomena, Effects and Options United Nations, New York, 1991.

[5]   C. J. Van Westen and M. T. J. Terlien, “An Approach towards Deterministic Landslide Hazard Analysis in GIS: A Case Study from Manizales, Colombia,” Earth Surface Processes and Landforms, Vol. 21, No. 9, 1996, pp. 853-868.

[6]   V. Moon and H. Blackstock, “A Methodology for Assessing Landslide Hazard Using Deterministic Stability Models,” Natural Hazards, Vol. 32, No. 1, 2004, pp. 111-134.
http://dx.doi.org/10.1023/B:NHAZ.0000026793.49052.87

[7]   J. W. Godt, R. L. Baum, W. Z. Savage, D. Salciarini, W. H. Schulz and E. L. Harp, “Transient Deterministic Shallow Landslide Modeling: Requirements for Susceptibility And Hazard Assessments in a GIS Framework,” Engineering Geology, Vol. 102, No. 3-4, 2008, pp. 214-226.
http://dx.doi.org/10.1016/j.enggeo.2008.03.019

[8]   A. Carrara, M. Cardinali, R. Detti, F. Guzetti, V. Pasqui and P. Reichenbach, “GIS Techniques and Statistical Models in Evaluating Landslide Hazard,” Earth Surface Processes and Landforms, Vol. 16, No. 5, 1991, pp. 427-445. http://dx.doi.org/10.1002/esp.3290160505

[9]   L. Luzi and P. Floriana, “Application of Statistical and GIS Techniques to Slope Instability Zonation (1: 50,000 Fabriano Geological Map Sheet),” Soil Dynamics and Earthquake Engineering, Vol. 15, No. 2, 1996, pp. 83-94.
http://dx.doi.org/10.1016/0267-7261(95)00031-3

[10]   A. Burton and J. C. Bathurst, “Physically Based Modeling of Shallow Landslide Sediment Yield at a Catchment Scale,” Environmental Geology, Vol. 35, No. 2-3, 1998, pp. 89-99. http://dx.doi.org/10.1007/s002540050296

[11]   F. Guzzetti, A. Carrarra, M. Cardinali and P. Reichenbach, “Landslide Hazard Evaluation: A Review of Current Techniques and Their Application in a Multi-Scale Study, Central Italy,” Geomorphology, Vol. 31, No. 1-4, 1999, pp. 181-216.
http://dx.doi.org/10.1016/S0169-555X(99)00078-1

[12]   J. Choi, H. J. Oh, J. S. Won and S. Lee, “Validation of an Artificial Neural Network Model for Landslide Susceptibility Mapping,” Environmental Earth Sciences, Vol. 60, 3, 2010, pp. 473-483.
http://dx.doi.org/10.1007/s12665-009-0188-0

[13]   B. Pradhan and S. Lee, “Regional Landslide Susceptibility Analysis Using Back-Propagation Neural Network Model at Cameron Highland, Malaysia,” Landslides, Vol. 7, No. 1, 2010, pp. 13-30.
http://dx.doi.org/10.1007/s10346-009-0183-2

[14]   K. Sassa, S. Tsuchiya, K. Ugai, A. Wakai and T. Uchimura, “Landslides: A Review of Achievements in the First 5 Years (2004-2009),” Landslides, Vol. 6, No. 4, 2009, pp. 275-286.
http://dx.doi.org/10.1007/s10346-009-0172-5

[15]   E. A. Castellanos Abella and C. J. Van Western, “Generation of a Landslide Risk Index Map for Cuba Using Spatial Multi-Criteria Evaluation,” Landslides, Vol. 4, No. 4, 2007, pp. 311-325.
http://dx.doi.org/10.1007/s10346-007-0087-y

[16]   R. Chowdhury and P. Flentje, “Role of Slope Reliability Analysis in Landslide Risk Management,” Bulletin of Engineering Geology and the Environment, Vol. 62, No. 1, 2003, pp. 41-46.

[17]   S. Lee and J. A. Talib, “Probabilistic Landslide Susceptibility and Factor Effect Analysis,” Environmental Geology, Vol. 47, No. 7, 2005, pp. 982-990.
http://dx.doi.org/10.1007/s00254-005-1228-z

[18]   E. A. Castellanos Abella and C. J. Van Western, “Qualitative Landslide Susceptibility Assessment by Multicriteria Analysis: A Case Study from San Antonio del Sur, Guantánamo, Cuba,” Geomorphology, Vol. 94, No. 3-4, 2008, pp. 453-466.
http://dx.doi.org/10.1016/j.geomorph.2006.10.038

[19]   C. F. Chung and A. G. Fabbri, “Probabilistic Prediction Models for Landslide Hazard Mapping,” Photogrammetric Engineering & Remote Sensing, Vol. 65, No. 12, 1999, pp. 1389-1399.

[20]   J. Duan and G. E. Grant, “Shallow Landslide Delineation for Steep Forest Watersheds Based on Topographic Attributes and Probability Analysis,” In: J. P. Wilson and J. C. Gallant, Ed., Terrain Analysis—Principles and Applications, John Wiley & Sons: New York, 2000, pp. 311-329.

[21]   S. Lee and N. T. Dan, “Probabilistic Landslide Susceptibility Mapping in the Lai Chau Province of Vietnam: Focus on the Relationship between Tectonic Fractures and Landslides,” Environmental Geology, Vol. 48, No. 6, 2005, pp. 778-787.
http://dx.doi.org/10.1007/s00254-005-0019-x

[22]   S. Lee, “Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping in GIS,” Environmental Management, Vol. 34, No. 2, 2004, pp. 223-232.
http://dx.doi.org/10.1007/s00267-003-0077-3

[23]   R. Dahal, S. Hasegawa, A. Nonomura, M. Yamanaka, T. Masuda and K. Nishino, “GIS-Based Weights-of-Evidence Modelling of Rainfall-Induced Landslides in Small Catchments for Landslide Susceptibility Mapping,” Environmental Geology, Vol. 54, No. 2, 2008, pp. 314-324.
http://dx.doi.org/10.1007/s00254-007-0818-3

 
 
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