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Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea

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Abstract

The likelihood ratio, logistic regression, and artificial neural networks models are applied and verified for analysis of landslide susceptibility in Youngin, Korea, using the geographic information system. From a spatial database containing such data as landslide location, topography, soil, forest, geology, and land use, the 14 landslide-related factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression, and artificial neural network models. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the models. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The verification results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

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Acknowledgements

This research was supported by the Basic Research Project of the Korea Institute of Geoscience and Mineral Resources (KIGAM) funded by the Ministry of Science and Technology of Korea.

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Authors and Affiliations

  1. Geoscience Information Center, Korea Institute of Geoscience and Mineral Resources (KIGAM), 30 Gajeong-Dong, Yuseong-Gu, Daejeon, 305-350, South Korea

    Saro Lee

  2. Ocean Satellite Research Group, Korea Ocean Research and Development Institute (KORDI), 1270 Sa 2-dong, Sangnuk-Gu, Ansan-Si, 426-744, South Korea

    Joo-Hyung Ryu

  3. Domestic Exploration Team I, Korea National Oil Corporation (KNOC), 1588–14 Gwanyang-Dong, Dongan-Gu, Anyang-Si, 431-711, South Korea

    Ii-Soo Kim

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  1. Saro Lee
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  2. Joo-Hyung Ryu
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  3. Ii-Soo Kim
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Correspondence to Saro Lee.

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Lee, S., Ryu, JH. & Kim, IS. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides 4, 327–338 (2007). https://doi.org/10.1007/s10346-007-0088-x

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  • DOI: https://doi.org/10.1007/s10346-007-0088-x

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