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Landslides

, Volume 4, Issue 1, pp 33–41 | Cite as

Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

  • Saro Lee
  • Biswajeet Pradhan
Original Article

Abstract

The aim of this study is to evaluate the landslide hazards at Selangor area, Malaysia, using Geographic Information System (GIS) and Remote Sensing. Landslide locations of the study area were identified from aerial photograph interpretation and field survey. Topographical maps, geological data, and satellite images were collected, processed, and constructed into a spatial database in a GIS platform. The factors chosen that influence landslide occurrence were: slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, land cover, vegetation index, and precipitation distribution. Landslide hazardous areas were analyzed and mapped using the landslide-occurrence factors by frequency ratio and logistic regression models. The results of the analysis were verified using the landslide location data and compared with probability model. The comparison results showed that the frequency ratio model (accuracy is 93.04%) is better in prediction than logistic regression (accuracy is 90.34%) model.

Keywords

Landslide Frequency ratio Logistic regression GIS Remote sensing 

Notes

Acknowledgement

Authors would like to thank Malaysian Center for Remote Sensing and Department of Surveying, Malaysia for providing various datasets for this research. Thanks are also due to the Malaysian Meteorological Service Department for providing rainfall data for the research. Authors also would like to thank anonymous reviewers from Landslides Journal for reviewing the paper, which has brought it into its present form.

References

  1. Atkinson PM, Massari R (1998) Generalized linear modeling of susceptibility to land sliding 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 Landf 26:1251–1263CrossRefGoogle Scholar
  3. Carro M, De Amicis, M Luzi, 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
  4. Chung CF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472CrossRefGoogle 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 Turkey) 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, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113CrossRefGoogle Scholar
  14. Lee S, Chwae U, Min K (2002a) Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area, Korea. Geomorphology 46:149–162CrossRefGoogle Scholar
  15. Lee S, Choi J, Min K (2002b) Landslide susceptibility analysis and verification using the Bayesian probability model. Environ Geol 43:120–131CrossRefGoogle Scholar
  16. Lee S, Ryu JH, Min K, Won JS (2003a) Landslide susceptibility analysis using GIS and artificial neural network. Earth Surf Process Landf 27:1361–1376CrossRefGoogle Scholar
  17. 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
  18. Lee S, Choi U (2003c) Development of GIS-based geological hazard information system and its application for landslide analysis in Korea. Geosci J 7:243–252CrossRefGoogle Scholar
  19. 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
  20. Lee S, Choi J, Min K (2004b) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Intl J Remote Sens 25:2037–2052CrossRefGoogle Scholar
  21. Luzi L, Pergalani F, Terlien MTJ (2000) Slope vulnerability to earthquakes at sub regional scale: using probabilistic techniques and geographic information systems. Eng Geol 58:313–336CrossRefGoogle Scholar
  22. Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansa, USA. Eng Geol 69:331–343CrossRefGoogle Scholar
  23. 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
  24. Pistocchi A, Luzi L, Napolitano P (2002) The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods. Environ Geol 41:765–775CrossRefGoogle Scholar
  25. Rautelal P, Lakhera RC (2000) Landslide risk analysis between Giri and Tons rivers in Himachal Himalaya (India). International Journal of Applied Earth Observation and Geoinformation 2:153–160CrossRefGoogle Scholar
  26. Rece A, Capolongo D (2002) Probabilistic modeling of uncertainties in earthquake-induced landslide hazard assessment. Comput Geosci 28:735–749CrossRefGoogle Scholar
  27. Remondo J, Gonzalez A, Diaz de Teran JR, Cendrero A, Fabbri AG, Chung CJF (2003) Validation of landslide susceptibility maps: examples and applications from a case study in Northern Spain. Nat Hazards 30:437–449CrossRefGoogle Scholar
  28. Romeo R (2000) Seismically induced landslide displacements: a predictive model. Eng Geol 58:337–351CrossRefGoogle Scholar
  29. Rowbotham D, Dudycha DN (1998) GIS Modeling of slope stability in Phewa Tal watershed, Nepal. Geomorphology 26:151–170CrossRefGoogle Scholar
  30. 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
  31. Temesgen B, Mohammed MU, Korme T (2001) Natural hazard assessment using GIS and remote sensing methods, with particular reference to the landslides in the Wondogenet area, Ethiopia. Phys Chem Earth 26:665–675Google Scholar
  32. 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
  33. 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

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Geoscience Information CenterKorea Institute of Geoscience and Mineral Resources (KIGAM)Yusung-GuSouth Korea
  2. 2.Cilix CorporationKuala LumpurMalaysia

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