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1 Journal of Environmental Impact Assessment, Vol. 22, No. 1(2013) pp.39~50 Prediction of Landslides Occurrence Probability under Climate Change using MaxEnt Model Kim, Hogul* Lee, Dong-Kun** Mo, Yongwon* Kil, Sungho* Park, Chan*** Lee, Soojae**** Graduate School, Seoul National University* Department of Landscape Architecture and Rural System Engineering, Seoul National University** National Institute of Environmental Research, Climate Change Research Division***, Korea Environment Institute**** (Manuscript received 27 November 2012; accepted 16 January 2013) Abstract Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall. Keywords : maximum entropy model, RCP 8.5 scenario, heavy rainfall, landslide susceptibility Corresponding Author: Lee, Dong-kun, Department of Landscape Architecture and Rural System Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-Gu, Seoul, , Korea Tel: Fax:

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11 Elith J., Ferrier S., Huettmann F., and Leathwick J., 2006, The evaluation strip: A new and robust method for plotting predicted responses from species distribution models, Ecol Model 186(3), Felicisimo, A., Cuartero A., Remondo J. and Quiros E., 2012, Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a comparative study, Landslides (7 March 2012), pp Mathewson, C.C., Keaton, J.R. and Santi, P.M., 1990, Role of Bedrock Ground Water in the Initiation of Debris Flows and Sustained Post-Flow Stream Discharge, Bulletin of the Association of Engineering

12 Geologists 27(1), Phillips, S.J., Anderson R.P. and Schapire R.E., A maximum entropy approach to species distribution modeling. In: Proceedings of the Twenty-First International Conference on Machine Learning, Banff, Alberta, Canada, p. 83 ff. Phillips, S.J. and Dudik, M., Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31, Pradhan B. and Lee S., 2010, Delineation of landslide hazard areas on Penang Island, Environment Earth Science 60, Vorpahl, P., Helmut E., Michael M. and Boris S., 2012, How can statistical models help to determine driving factors of landslides?, Ecological Modelling 239,

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