Environmental Geology

, Volume 50, Issue 6, pp 847–855 | Cite as

Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models

  • Saro Lee
  • Touch Sambath
Original Article


This study applied, tested and compared a probability model, a frequency ratio and statistical model, a logistic regression to Damre Romel area, Cambodia, using a geographic information system. For landslide susceptibility mapping, landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and a spatial database was constructed from topographic maps, geology and land cover. The factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from lineament were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite imagery. The relationship between the factors and the landslides was calculated using frequency ratio and logistic regression models. The relationships, frequency ratio and logistic regression coefficient were overlaid to make landslide susceptibility map. Then the landslide susceptibility map was compared with known landslide locations and tested. As the result, the frequency ratio model (86.97%) and the logistic regression (86.37%) had high and similar prediction accuracy. The landslide susceptibility map can be used to reduce hazards associated with landslides and to land cover planning.


Landslide Frequency ratio Logistic regression GIS Cambodia 


  1. Atkinson PM, Massari R (1998) Generalized linear modeling of susceptibility to landsliding in the central Apennines, Italy. Comput Geosci 24:373–385CrossRefGoogle Scholar
  2. Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth surf process landforms 26:251–1263CrossRefGoogle Scholar
  3. Bonham-Carter, GF (1994) Geographic information systems for geoscientists, modeling with GIS. Pergamon Press, Oxford, pp 398Google Scholar
  4. Carro M, De Amicis M, Luzi L, Marzorati S (2003) The application of predictive modeling techniques to landslides induced by earthquakes: the case study of the 26 September 1997 Umbria-Marche earthquake (Italy). Eng Geol 69:139–159CrossRefGoogle Scholar
  5. Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48:349–364CrossRefGoogle Scholar
  6. Dai FC, Lee CF (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228CrossRefGoogle Scholar
  7. Dai FC, Lee CF, Li J, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40:381–391CrossRefGoogle Scholar
  8. Donati L, Turrini MC (2002) An objective method to rank the importance of the factors predisposing to landslides with the GIS methodology: application to an area of the Apennines (Valnerina; Perugia, Italy). Eng Geol 63:277–289CrossRefGoogle Scholar
  9. Ercanoglu M, Gokceoglu C (2002) Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkye) by fuzzy approach. Environ Geol 41:720–730CrossRefGoogle Scholar
  10. Gokceoglu C, Sonmez H, Ercanoglu M (2000) Discontinuity controlled probabilistic slope failure risk maps of the Altindag (settlement) region in Turkey. Eng Geol 55:277–296CrossRefGoogle Scholar
  11. Guzzetti F, Carrarra A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study. Central Italy. Geomorphology 31:181–216CrossRefGoogle Scholar
  12. Jibson WR, Edwin LH, John AM (2000) A method for producing digital probabilistic seismic landslide hazard maps. Eng Geol 58:271–289CrossRefGoogle Scholar
  13. Lee S (2004e) Application of likelihood ratio and logistic regression model for landslide susceptibility mapping using GIS. Environ Manage 34:223–232CrossRefPubMedGoogle Scholar
  14. Lee S, Choi U (2003) Development of GIS-based geological hazard information system and its application for landslide analysis in Korea. Geosci J 7:243–252CrossRefGoogle Scholar
  15. Lee S, Choi J (2004) Application of a weight-of-evidence model to landslide susceptibility analysis. Int J Geogr Inf Sci 18:789–814CrossRefGoogle Scholar
  16. Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113CrossRefGoogle Scholar
  17. Lee S, Chwae U, Min K (2002a) Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area, Korea. Geomorphology 46:49–162Google Scholar
  18. Lee S, Choi J, Min K (2002b) Landslide susceptibility analysis and verification using the Bayesian probability model. Environ Geol 43:120–131CrossRefGoogle Scholar
  19. Lee S, Ryu JH, Min KD, Won JS (2003a) Landslide susceptibility analysis using GIS and artificial neural network. Earth Surf Process Landforms 27:1361–1376CrossRefGoogle Scholar
  20. Lee S, Ryu JH, Lee MJ, Won JS (2003b) Landslide susceptibility analysis using artificial neural network at Boun, Korea. Environ Geol 44:820–833CrossRefGoogle Scholar
  21. Lee S, Ryu JH, Won JS, Park HJ (2004a) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71:289–302CrossRefGoogle Scholar
  22. Lee S, Choi J, Woo I (2004b) The effect of spatial resolution on the accuracy of landslide susceptibility mapping: a case study in Boun, Korea. Geosci J 8:51–60CrossRefGoogle Scholar
  23. Lee S, Choi J, Min K (2004c) Landslide Hazard Mapping using GIS and Remote Sensing Data at Boun, Korea. Int J Remote Sens 25:2037–2052CrossRefGoogle Scholar
  24. Luzi L, Pergalani F, Terlien MTJ (2000) Slope vulnerability to earthquakes at subregional scale, using probabilistic techniques and geographic information systems. Eng Geol 58:313–336CrossRefGoogle Scholar
  25. Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343CrossRefGoogle Scholar
  26. Parise M, Jibson WR (2000) A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng Geol 58:251–270CrossRefGoogle Scholar
  27. Pistocchi A, Luzi L, Napolitano P (2002) The use of predictive modeling techniques for optimal exploitation of s patial databases: a case study in landslide hazard mapping with expert system-like methods. Environ Geol 41:765–775CrossRefGoogle Scholar
  28. Romeo R (2000) Seismically induced landslide displacements: a predictive model. Eng Geol 58:337–351CrossRefGoogle Scholar
  29. Shou KJ, Wang CF (2003) Analysis of the Chiufengershan landslide triggered by the 1999 Chi-Chi earthquake in Taiwan. Eng Geol 68:237–250CrossRefGoogle Scholar
  30. Zhou CH, Lee CF, LI J, Xu ZW (2002) On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong. Geomorphology 43:197–207CrossRefGoogle Scholar
  31. Zhou G, Esaki T, Mitani Y, Xie M, Mori J (2003) Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach. Eng Geol 68:373–386CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Geoscience Information CenterKorea Institute of Geoscience & Mineral Resources (KIGAM)DaejeonKorea
  2. 2.Department of Geology, General Department of Mineral ResourcesMinistry of Industry, Mines and EnergyPhnom PenhKingdom of Cambodia

Personalised recommendations