Relative effect method of landslide susceptibility zonation in weathered granite soil: a case study in Deokjeok-ri Creek, South Korea

The objective of this study was to produce and evaluate a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea. The relative effect (RE) method was used to determine the relationship between landslide causative factors (CFs) and landslide occurrence. To determine the effect of CFs on landslides, data layers of aspect, elevation, slope, internal relief, curvature, distance to drainage, drainage density, stream power index, sediment transport index, topographic wetness index, soil drainage character, soil type, soil depth, forest type, timber age, and geology were analyzed in a geographical information system (GIS) environment. A GIS-based landslide inventory map of 748 landslide locations was prepared using data from previous reports, aerial photographic interpretation, and extensive field work. A RE model was generated from a training set consisting of 673 randomly selected landslides in the inventory map, with the remaining 75 landslides used for validation of the susceptibility map. The results of the analysis were verified using the landslide location data. According to the analysis, the RE model had a success rate of 86.3 % and a predictive accuracy of 88.6 %. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. The results of this study can therefore be used to mitigate landslide-induced hazards and to plan land use.

[1]  Dorothy H. Radbruch,et al.  Map showing relative amounts of landslides in California , 1970 .

[2]  G. Wieczorek,et al.  Preparing a Detailed Landslide-Inventory Map for Hazard Evaluation and Reduction , 1984 .

[3]  R. Sidle,et al.  Hillslope stability and land use , 1985 .

[4]  I. Moore,et al.  Physical basis of the length-slope factor in the universal soil loss equation , 1986 .

[5]  M. H. de Freitas,et al.  A revision of the description and classification of weathered granite and its application to granites in Korea , 1989, Quarterly Journal of Engineering Geology.

[6]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .

[7]  I. Moore,et al.  Length-slope factors for the Revised Universal Soil Loss Equation: simplified method of estimation , 1992 .

[8]  C. J. van Westen,et al.  GIS in landslide hazard zonation : a review, with examples from the Andes of Colombia , 1994 .

[9]  E. Wohl,et al.  GEOLOGICAL HAZARD AND RISK EVALUATION USING GIS: METHODOLOGY AND MODEL APPLIED TO MEDELLIN, COLOMBIA , 1994 .

[10]  Modelling gully distribution on volcanic terrains in the Huasca area, central Mexico , 1994 .

[11]  Martin F. Price,et al.  Mountain Environments and Geographic Information Systems , 1995 .

[12]  P. Reichenbach,et al.  Gis Technology in Mapping Landslide Hazard , 1995 .

[13]  C. Gokceoğlu,et al.  Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques , 1996 .

[14]  Luis A. Garcia,et al.  Natural Hazard and Risk Assessment Using Decision Support Systems, Application: Glenwood Springs, Colorado , 1996 .

[15]  R. Soeters,et al.  Slope instability recognition, analysis, and zonation , 1996 .

[16]  R. Chander,et al.  Landslide zoning in a part of the Garhwal Himalayas , 1998 .

[17]  P. Reichenbach,et al.  Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy , 1999 .

[18]  Lucia Luzi,et al.  Slope Instability in Static and Dynamic Conditions for Urban Planning: the ‘Oltre Po Pavese’ Case History (Regione Lombardia – Italy) , 1999 .

[19]  C. Chung,et al.  Probabilistic prediction models for landslide hazard mapping , 1999 .

[20]  P. Aleotti,et al.  Landslide hazard assessment: summary review and new perspectives , 1999 .

[21]  R. Nagarajan,et al.  Landslide hazard susceptibility mapping based on terrain and climatic factors for tropical monsoon regions , 2000 .

[22]  Graciela Metternicht,et al.  Mapping and modelling mass movements and gullies in mountainous areas using remote sensing and GIS techniques , 2001 .

[23]  J. Corominas,et al.  Assessment of shallow landslide susceptibility by means of multivariate statistical techniques , 2001 .

[24]  Lee H. MacDonald,et al.  Runoff and road erosion at the plot and road segment scales, St John, US Virgin Islands , 2001 .

[25]  R. Soeters,et al.  Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment , 2003 .

[26]  T. Topal,et al.  GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey) , 2003 .

[27]  Andrea G. Fabbri,et al.  Validation of Spatial Prediction Models for Landslide Hazard Mapping , 2003 .

[28]  C. Gokceoglu,et al.  Landslide Susceptibility Zoning North of Yenice (NW Turkey) by Multivariate Statistical Techniques , 2004 .

[29]  L. Ayalew,et al.  Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan , 2004 .

[30]  Sang-Seom Jeong,et al.  Influence of rainfall-induced wetting on the stability of slopes in weathered soils , 2004 .

[31]  H. Kim,et al.  On Climate Variations and Changes Observed in South Korea , 2004 .

[32]  T. T. Lee,et al.  Response of a residual soil slope to rainfall , 2005 .

[33]  P. Reichenbach,et al.  Probabilistic landslide hazard assessment at the basin scale , 2005 .

[34]  A. Brenning.  Spatial prediction models for landslide hazards: review, comparison and evaluation , 2005 .

[35]  Dhruba Tripathi,et al.  Hydrological hazard mapping in Rupandehi district, west Nepal , 2006 .

[36]  Ramesh P. Singh,et al.  Estimation of stress and its use in evaluation of landslide prone regions using remote sensing data , 2006 .

[37]  B. Pradhan,et al.  Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models , 2007 .

[38]  M. Hutchinson,et al.  Digital terrain analysis. , 2008 .

[39]  H. A. Nefeslioglu,et al.  Extraction of potential debris source areas by logistic regression technique: a case study from Barla, Besparmak and Kapi mountains (NW Taurids, Turkey) , 2008 .

[40]  Sajidu,et al.  Groundwater fluoride levels in villages of Southern Malawi and removal studies using bauxite , 2008 .

[41]  Manfred F. Buchroithner,et al.  Utilization of optical remote sensing data and geographic information system tools for regional landslide hazard analysis by using binomial logistic regression model , 2008 .

[42]  B. Pradhan,et al.  Landslide risk analysis using artificial neural network model focussing on different training sites. , 2009 .

[43]  H. Saito,et al.  Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan , 2009 .

[44]  Shiuan Wan,et al.  A spatial decision support system for extracting the core factors and thresholds for landslide susceptibility map , 2009 .

[45]  Lee Cheol Ju,et al.  A Study on Debris Flow Landslide Disasters and Restoration at Inje of Kangwon Province, Korea , 2009 .

[46]  Abbas Alimohammadi,et al.  A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping , 2010, Comput. Geosci..

[47]  Young-Kwang Yeon,et al.  Landslide susceptibility mapping in Injae, Korea, using a decision tree , 2010 .

[48]  B. Pradhan,et al.  Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia , 2010 .

[49]  B. Pradhan,et al.  Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models , 2010 .

[50]  M. Marschalko,et al.  Landslide susceptibility assessment of the Kraľovany–Liptovský Mikuláš railway case study , 2010 .

[51]  Biswajeet Pradhan,et al.  Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling , 2010, Environ. Model. Softw..

[52]  B. Pradhan.  Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches , 2010 .

[53]  Fausto Guzzetti,et al.  Geographical Information Systems in Assessing Natural Hazards , 2010 .

[54]  B. Pradhan,et al.  Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey) , 2012, Environmental Monitoring and Assessment.

[55]  Biswajeet Pradhan,et al.  Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia , 2011 .

[56]  M. Bednarik,et al.  Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania) , 2011 .

[57]  Biswajeet Pradhan,et al.  Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area , 2011, Comput. Geosci..

[58]  Biswajeet Pradhan,et al.  Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia , 2011, Expert Syst. Appl..

[59]  B. Pradhan,et al.  Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models , 2012 .

[60]  R. Neelakantan,et al.  Relative effect-based landslide hazard zonation mapping in parts of Nilgiris, Tamil Nadu, South India , 2013, Arabian Journal of Geosciences.

[61]  R. Bai,et al.  Fractal dimension analysis of higher-order mode shapes for damage identification of beam structures , 2012 .

[62]  B. Pradhan,et al.  Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg–Marquardt and Bayesian regularized neural networks , 2012 .

[63]  B. Pradhan,et al.  Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran , 2012, Natural Hazards.

[64]  Biswajeet Pradhan,et al.  An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm , 2012, Comput. Geosci..

[65]  Soyoung Park,et al.  Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea , 2013, Environmental Earth Sciences.

[66]  B. Pradhan,et al.  Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran , 2012 .