• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.21-33
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• 2020

Purpose: The objective of this research is to classify snowfall area types with consideration of past regional snowfall characteristics and times for the effective local snow removal response systems of 229 local government districts. Method: This research first collected snowfall data of South Korea meteorological stations, and classified regional types using successive snowfall time. This research finally produced GIS maps using regional type information of snowfalls by applying GIS analysis methods. Result: This research provides five types of snowfall regions including 'frequent heavy snowfall regions', 'frequent light snowfall regions', 'rare heavy snowfall regions', 'average snowfall regions', and 'rare light snowfall regions' based on analysis results. Conclusion: Results of this research can be used as basic information for regional demand estimations of snow removal equipments, materials, vehicles, and personnel for the efficient snow removal response systems.

• Journal of the Society of Disaster Information
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• v.13 no.2
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• pp.163-172
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• 2017

Because of abnormal weather, a heavy snow on the Northern latitudes occurs frequently. This has resulted in significant damage and recovery costs. In korea, it has been declared a special disaster area due to heavy snowfall in Gangneung and Pohang 2004, 2005 and 2011, so there was a revision of action instruction for the road snow removal. Although, in our current system, snow removing methodology, regional equipment holdings, and snow responsible interval, respectively, has been classified by the National Highway, near cities and provinces support system not yet prepared. Only, if snow removing is not possible within the region itself, which contained the contents of "support and assistance to military or nearby offices requests". In this thesis, we studied the disaster scenario development according to heavy snow and the response and support system to the features of each regional. For the scenario deduction, we preferentially collected day snowfall and disaster yearbook data to regionals, classified similar pattern and plotted GIS snow map. We also classified heavy snow disaster by region and type and we deduced five-step scenario. The five-step scenario is nationwide(1st-stage), the National Capital region(2nd-stage), the Chungcheong Provinces(3rd-stage), the Kangwon province(4th-stage) and the Ch?l a provinces(5th-stage). Therefore we build near provinces support system according to five-step scenario.