Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

Saro Lee, Joo Hyung Ryu, Joong-sun Won, Hyuck Jin Park

Research output: Contribution to journalArticle

366 Citations (Scopus)


The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

Original languageEnglish
Pages (from-to)289-302
Number of pages14
JournalEngineering Geology
Issue number3-4
Publication statusPublished - 2004 Jan 1


All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Geology

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