• Journal of the Society of Disaster Information
• /
• v.14 no.2
• /
• pp.154-164
• /
• 2018

Purpose: Recent climate change makes weather-related disasters such as summer storms, heavy rains, winter snowfall disasters, and extreme cold temperature increase in trend. Heavy snowfall disasters requires speedy response due to various effects to traffic flows, buildings, and infrastructure. Heavy snowfall disaster response of South Korea is insufficient, even though heavy snowfall disasters affect urban safety. There have been lack of policy studies for heavy snowfall disasters. Method: This research analyzes case studies and explores implications using Information system technologies to snow removal vehicles and equipments for speedy snow removal during the heavy snowfall disasters. Results: Information system technology attachment to snow removal equipments can identify locations of snow removal vehicles and equipments for emergency period to support snow removal of adjacent jurisdictions. Conclusion: Case studies of this research can be further used for efficient application of snow removal tools of local governments.

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