Environmental Earth Sciences

, Volume 61, Issue 5, pp 1049–1064 | Cite as

Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya

  • Chandra Prakash Poudyal
  • Chandong Chang
  • Hyun-Joo Oh
  • Saro LeeEmail author
Original Article


This study considers landslide susceptibility mapping by means of frequency ratio and artificial neural network approaches using geographic information system (GIS) techniques as a basic analysis tool. The selected study area was that of the Panchthar district, Nepal. GIS was used for the management and manipulation of spatial data. Landslide locations were identified from field survey and aerial photographic interpretation was used for location of lineaments. Ten factors in total are related to the occurrence of landslides. Based on the same set of factors, landslide susceptibility maps were produced from frequency ratio and neural network models, and were then compared and evaluated. The weights of each factor were determined using the back-propagation training method. Landslide susceptibility maps were produced from frequency ratio and neural network models, and they were then compared by means of their checking. The landslide location data were used for checking the results with the landslide susceptibility maps. The accuracy of the landslide susceptibility maps produced by the frequency ratio and neural networks is 82.21 and 78.25%, respectively.


Landslide susceptibility GIS Frequency ratio Artificial neural networks Nepal 



This research was supported by the Basic Research Project of the Korea Institute of Geoscience and Mineral Resources (KIGAM) funded by the Ministry of Knowledge and Economy of Korea. We thank Mr. Surya P. Poudel for the landslide data collection in the field.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Chandra Prakash Poudyal
    • 1
  • Chandong Chang
    • 1
  • Hyun-Joo Oh
    • 2
  • Saro Lee
    • 2
    Email author
  1. 1.Department of Earth and Environmental ScienceChungnam National UniversityDaejeonKorea
  2. 2.Geoscience Information CenterKorea Institute of Geoscience and Mineral Resources (KIGAM)DaejeonKorea

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