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Lee, Kwan-Hyoung;Yi, Waon-Ho;Yang, Won-Jik
- Journal of Korean Society of Disaster and Security
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- v.9 no.2
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- pp.15-21
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- 2016
According to the disaster statistics issued by the Ministry of Public Safety and Security, traffic accidents, fire, collapses and others are classified into twenty-three (23) categories. In the past, disasters were mainly caused by the influence of nature, such as typhoon or drought. On the other hand, as society has become city-centered, social disasters' types, frequencies and scales are becoming more diversified and ever-increasing. However, there are no specific criteria and assessment methods that can measure degrees of social disasters-related risks objectively. Therefore, this study targeted traffic accidents, fire and collapses from major social disasters, utilized data that are related to occurrence rate, scale of casualties and scale of property loss in past eight years, and calculated the disaster risk index using the distance (Euclidean distance) between two points on the 3D spatial coordinates, in order to make the objective assessment by social disaster type possible. These results will enable the objective evaluation of risk index of major social disaster to be used as the foundational data when building the national disaster management system.
https://doi.org/10.21729/ksds.2016.9.2.15 인용 PDF KSCI

Heo, Jungeun;Yang, Chang Hoon
- The Journal of the Korea Contents Association
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- v.18 no.11
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- pp.123-134
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- 2018
Recently, due to the rising incidence of disasters in the nation, there has been a growing interest in the relevance and role of science and technology in solving disaster and safety related issues. In addition, the necessities of securing the human rights of all citizens in disaster risk reduction, identifying fields of technology development for effective disaster response, and improving the efficiency of R&D investment for disaster and safety are becoming more important as the different types of disasters and stages of disaster and safety management process have been considered. In this study, we analyzed bipartite or two-mode networks constructed from an expert survey dataset of technology development for disaster and safety management. The results reveal that earthquake and fire are the two disasters affecting an individual and society at large and demonstrate that AI and big data analytics are effective supports in managing disaster and safety. We believe that such a network analytic approach can be used to explore some important implications exist for the national science and technology effort and successful disaster and safety management practices in Korea.
https://doi.org/10.5392/JKCA.2018.18.11.123 인용 PDF KSCI HTML