, 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


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.


Landslide Frequency ratio Logistic regression GIS Remote sensing 



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.


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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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