• Journal of Distribution Science
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• v.16 no.6
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• pp.15-23
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• 2018

Purpose - This paper aims to explore the distribution and application of community-based disaster risk information and employ a case study as a qualitative research method to make some implications and suggestions for disaster management in the future. Research design, data, and methodology - This research has basically adopted an idiographic approaches to examine the basic policy of integrated flood risk management of Shiga prefecture in Japan. The methodology is based on a retrospective analysis, which starts from critical events and traces backwards processes to find out what goes well or wrong. Results - The results of this paper support that the multiple stakeholders in a community have to share and distribute disaster risk information in the proper time. The distribution and application of community-based disaster risk information cannot be overemphasized in that the local communities are culturally rich in traditional flood management knowledge, have voluntary organizations and have enjoyed mutual support and human network to cope with floods. Conclusions - The study results also imply that local residents of the community will be abe to have an important role in coping with natural disasters, which involves more proactive actions than passive actions for the enhancement of disaster management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.4
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• pp.765-773
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• 2017

With the end of the HFA (Hyogo Framework Action) in 2015, SFDRR (Sendai Framework for Disaster Risk Reduction) was adopted as a new agenda for disaster risk reduction at the 3th WCDRR (World Conference on Disaster Risk Reduction), held in March 2015. Continued understanding of the international agenda for reducing disaster risk is critical to disaster risk reduction at the national level as well as international level. Therefore, in this study, we analyzed major changes in the international agenda for disaster risk reduction as the transition from HFA to SFDRR, and analyzed South Korea's major achievements in the HFA and the implementation status of SFDRR in South Korea. In addition, SFDRR emphasizes the role of science and technology in policy making, and examined research trends in science and technology. 49.9% of the efforts were made to prevent the disasters during the disaster management stage, and plans related to priority 1 (40.4%) and 4 (35.8%) were mainly promoted. Science and technology research and development for disaster management were analyzed as active, but 79.7% of the tasks were related to priority 4, and it is necessary to develop all four priorities. Recently, disaster management using next-generation disaster prevention technologies such as satellite technology and big data is required, and it is expected that it will contribute effectively to mitigate disaster risk through establishment of education and policy to support it.

• Journal of the Society of Disaster Information
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• v.7 no.3
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• pp.220-228
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• 2011

Disaster sign data is confirmed data by the experts to the collected data from web and users. In this paper, we focused to make the risk scores to the data based on ontology technology. To analyse the data, first of all, we defined the ontological structure for 4 kinds of disaster types which consists of the bridges, workplaces, buildings, and walls. Base on the ontologies, collected the accidents examples, and then extract the risk rules from the examples. The rules are adjusted with frequencies and weights, and managed to the ontology DB. The rules apply to the disaster sign data, and then calculates the risk scores. It plays role of the index to the risk rates. The disaster sign data management system was implemented and the rules were verified to the system. Because the quality of the risk scores to the disaster sign data depends on the data of the accidents examples's qualities, we assure that the system's performance will be monotonic increasing following up the data upgrades. Continuously, data management is needed. Also the quality control of the rules are needed.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.5
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• pp.67-73
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• 2010

Relatively high density of population and buildings exists in urban area mainly because of broad job opportunities and conveniences available. In other words, if happened, there might be high possibility of disaster which can not be easily recovered. The purpose of this study is to show evaluation approach of the risk degree resulted from the disaster, which considers the attributes of urban area. Cheongju-city in Chungcheongbuk-do is selected as sample district to be estimated. The degree of overall risk including fire risk, building collapse risk, evacuation risk and gas explosion risk etc. is analyzed in the designated area. The analysis suggests the highest risk degree in Bukmun-ro district which also shows CBD decline phenomenon. Therefore, it can be not only predicted that this area as old downtown has not been provided with disaster prevention operation and urban renewal project, but also judged that administrative assistances for the disaster are required possibly soon.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.395-404
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• 2022

Purpose: Small-scale construction sites have insufficient systematic safety management activities, and due to the characteristics of the construction site, the production structure is complex due to external environmental factors, and the risk of construction equipment is very high. We would like to propose a checklist method among practical risk assessment techniques that can derive risk factors for disaster prevention at small construction sites and reduce disasters. Method: Risk factors were derived by analyzing literature research and disaster cases, and detailed work for a checklist of risk assessment suitable for small-scale construction sites was classified based on risk factor items. Result: Hazard factors were divided into 6 major categories, and 29 detailed types of work were classified based on actual work types, and 80 detailed works were classified accordingly. Conclusion: By arranging risk factors suitable for small-scale construction sites according to the classification system, the lack of expertise in the construction site can be supplemented, and risk factors can be derived more easily and disaster reduction can be expected through establishment of safety measures.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.1
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• pp.57-66
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• 2023

There is a strong association between poverty levels and the probability of natural disasters. East Java, however, exhibits a distinct pattern. While the rate of poverty is declining, natural disasters are becoming more severe. Considering that East Java is an area with a high risk of natural disasters and a high poverty rate, this study aims to estimate the effect of environmental preservation and the magnitude of the impact of disasters as measured by the Disaster Risk Index (IRBI) on poverty. The 3SLS model is used on secondary data from 38 districts/cities from 2015 to 2021 as an analytical database. Based on the estimation results, there are 3 findings in this study: (i) the role of government, population development, and economic activity have a strong influence on nature conservation; (ii) nature conservation has a strong influence on disaster risk; and (iii) the disaster risk index has a strong effect on poverty. As a result, areas with a high level of disaster risk have a slower rate of poverty reduction. The role of this research is to show the need for the government's role in improving the quality of natural disaster mitigation anticipation, economic activity, and the role of the population in a sustainable manner.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.828-838
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• 2022

Purpose: Through the establishment of a computerized system of risk assessment, the purpose is to analyze the case of whether the co-workers who are subject to the risk assessment at the construction site can easily fill it out and expect disaster reduction through efficient risk assessment activities. Method: By providing the risk factors and safety measures for the work by selecting the type of work, the risk estimation and the establishment of countermeasures can be made, and a system has been established to enable practical disaster prevention activities by presenting disaster cases for the work. Result: Through the analysis of the change in the scaled disaster rate for the years following the on-site application after the establishment of the risk assessment computer system of H Construction Company, it was confirmed that the scaled disaster rate of the domestic construction industry increased, while the conversion disaster rate of H Construction Company decreased. Conclusion: Through the computational systemization of risk assessments, workers in the field can easily access the risk assessment, evaluate the risk factors of the process and establish risk prevention measures, and it has been analyzed that there is an impact on the reduction of the disaster rate during the operational analysis period.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.81-96
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• 2021

Purpose: Based on the preceding studies in supply chain management, factors were analyzed to verify the effect of risk assessment and risk management factors of the business continuity management system (BCMS) on management performance. The purpose of this study is to establish a systematic risk management plan by deriving the risk factors of BCMS and evaluating unpredictable risks, and at the same time, contributing to a company's competitive advantage without interruption of work. Method: The structural relationship between risk assessment, risk management and management performance of BCMS was derived. To this end, a questionnaire survey was conducted of 124 managers and managers in Korean companies. Frequency analysis, validity analysis, reliability analysis, correlation analysis, and simple regression analysis were performed. Result: First, risk assessment had a positive (+) effect on risk management. Second, risk management had a positive (+) effect on management performance. Finally, risk assessment had a positive (+) effect on management performance. Conclusion: BCMS's risk assessment and risk management capabilities should be managed through financial performance, and risk management activities should be managed through non-financial performance.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.771-783
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• 2023

This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.