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Spatial Landslide Hazard Prediction Using Rainfall Probability and a Logistic Regression Model

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Abstract

The aims of this study were to apply and validate a logistic regression model for landslide hazard, considering rainfall probability and using a geographic information system. The study focused on the Deokeokri and Karisanri areas of Inje, South Korea. We chose logistic regression for its mathematical rigor and its use of implementation in GIS software. Rainfall probability is analyzed for a quantitative prediction of rainfall changes in the study area. The rainfall probability was calculated using the Gumbel distribution. Then, the probabilities of landslides in the study area in target years (1, 3, 10, 50, and 100 years in the future) were calculated assuming that landslides are triggered by daily rainfall of 202 mm or 3-day cumulative rainfall of 449 mm. Landslide hazard maps were developed for the two study areas, and the logistic regression coefficients for one area were applied to the other area to validate the method. In Karisanri, all recorded landslides were used for validation. Validation results for the 202-mm daily precipitation threshold in Karisanri showed an average accuracy of 79.14 %, whereas those for the 449-mm 3-day cumulative precipitation threshold showed an average accuracy of 81.31 %. A combination of rainfall probability and logistic regression with a GIS is an effective method for analyzing the possibility of future landslides.

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Acknowledgments

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, ICT & Future Planning, and the Development Project of Environmental Technology for Climate Change by the Korea Environmental Industry & Technology Institute.

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Authors and Affiliations

  1. Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124, Gwahang-no, Yuseong-Gu, Daejeon, 305-350, South Korea

    Saro Lee

  2. Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon, 305-350, Korea

    Saro Lee

  3. Department of Earth System Sciences, Yonsei University, 134 Shinchon-dong, Seoul, Korea

    Joong-Sun Won & Moung Jin Lee

  4. Korea Environment Institute, 290 Jinheungno, Eunpyeong-gu, Seoul, 122-706, Korea

    Seong Woo Jeon & Moung Jin Lee

  5. Department of Geoinformatics, University of Seoul, Siripdae-gil 13, Dongdaemun-gu, Seoul, 130-743 , Republic of Korea

    Inhye Park

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  1. Saro Lee
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  2. Joong-Sun Won
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  3. Seong Woo Jeon
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  4. Inhye Park
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  5. Moung Jin Lee
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Correspondence to Moung Jin Lee.

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Lee, S., Won, JS., Jeon, S.W. et al. Spatial Landslide Hazard Prediction Using Rainfall Probability and a Logistic Regression Model. Math Geosci 47, 565–589 (2015). https://doi.org/10.1007/s11004-014-9560-z

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  • DOI: https://doi.org/10.1007/s11004-014-9560-z

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