• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.290-298
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• 2019

This study investigated a total of 22 types (15 types of natural disasters and seven types of social disasters) of disaster and safety data based on the National Daily Situation Report, Disaster Yearbook and annual Disaster Annals issued by the Ministry of Public Administration and Security. Disaster safety data were collected from the daily situation report of MOIS (Ministry of the Interior and Safety). The number of total data cases were 1,760, of which 656 were natural disasters and 1,104 were social disasters. The disasters were then patternized according to their characteristics. The patterning was conducted to set up the disaster and safety data system designed to keep disaster situations under prompt and effective management. The study analyzed the data associated with the activities in the response and recovery stages according to the disaster type. Furthermore, based on the management activities performed with the flow of time following a disaster, this study classified and proposed disaster and safety data patterns to achieve effective disaster management work by analyzing the characteristics of a disaster and safety data and disaster and safety management procedures. Disasters of high similarity were classified by merging and deleting them. This was done to consider the scalability and mutual linkage so that it can be used in the establishment of national statistical data, such as the disaster annual report and disaster annuity.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.891-894
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• 2010

Steep slope disasters accompany economic loss along with casualties, so the evaluation and the systematic management on the regions with slope collapse danger are required. A lot of manpower, time, and economic cost are needed to accumulate disaster history of steep slope areas by the national and small-sized region. As the method for this, it construed location data about each area with disaster occurrence by maknd elocation data of collapsed steep areas through high-resolution satellite image and collectnd edata on the regions with disasters through media and literature data such as a disaster annual report and a disaster comprehensive report. The study selected three shortest routes includnd ethe area with disaster in Jeolla province on literature and the collapsed area found by the image data, and constructed the results of the field survey as database.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.319-322
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• 2007

This study aims to find the characteristics of damage and states of natural disasters at the Korean Peninsula from 1985 to 2004. Using the data of Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration. we have analyzed the cause, elements, and vulnerable regions for natural disasters. Major causes of natural disaster at Korean Peninsula are four, such as a heavy rain, heavy rain typhoon, typhoon, storm snow, and storm. The frequency of natural disaster is the highest from June to September. The period from December to March also shows high frequency. The total amount of damage is high during the summer season(Jul.-Sept). The period from January to March shows relatively high amount of damage due to storm and storm snow The areas of Gangwon-do, Gyeongsangnam-do and Gyeongsangbuk-do are classified the vulnerable region for the natural disasters. By establishing mitigation plans which fit the type and characteristics of disaster for each region, damage from disaster can be reduced with efficient prevention activities.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.315-318
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• 2007

In order to reduce the amount of damage from natural disasters, we needs prevention meteorological database classified into the cause of disaster, damage elements etc. For this, we have analyzed four data, such as Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration and Recently 10 years for natural disaster damage and Statistics Yearbook from the Ministry of Government Administration and Human affairs. Through the analysis of disaster data, we have selected input variables, such as causes and elements, occurrence frequencies, vulnerable areas of natural disaster, etc. In order to reduce damage from natural disaster, the prevention activities and forecasting based on meteorological parameters and damage datas are required. In addition, it is necessary to process meteorological information for disaster prevention activities. Through these procedure, we have established the foundation of database about natural disasters. This database will be used to assess the natural disasters and build risk model and natural disasters mitigation plan.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.94-97
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• 2007

This study aims to find the characteristics of damage and states of natural disasters at Gimhae, Gyeongsangnam-do from 1985 to 2004. Using the data of Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration. we have analyzed the cause, elements, and vulnerable regions for natural disasters. Major causes of natural disaster at Gimhae are four, such as a heavy rain, heavy rain typhoon, typhoon, storm snow, and storm. The cause of disaster recorded the most amount of damage is typhoon. The areas of Hallim-myeon, Sangdong-myeon, and Saengnim-myeon are classified the vulnerable region for the natural disasters in Gimhae. Therefore, it seems necessary to build natural disaster mitigation plan each cause of disaster to control water resources and to reduce damage for these areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.668-675
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• 2018

The continuing urbanization and industrialization around the world has required a large amount of power. Therefore, construction of major infrastructure, including nuclear power plants in coastal areas, has accelerated. In addition, the intensity of natural disasters is increasing due to global warming and abnormal climate phenomena. Natural disasters are difficult to predict in terms of occurrence, location, and scale, resulting in human casualties and property damage. For these reasons, the disaster scale and damage estimation in coastal areas have become important issues. The present study examined the predictable weather data and regional ratings and developed estimating functions for wind wave damage based on the disaster statistics in the southern areas. The results of the present study are expected to help disaster management in advance of the wind wave damage. The NRMSE was used for verification. The accuracy of the NRMSE results ranged from 1.61% to 21.73%.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• Journal of the Society of Disaster Information
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• v.16 no.2
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• pp.223-236
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• 2020

Purpose: In this study, a strong wind damage prediction function was developed in order to be used as a contingency during disaster management (preventive-preventive-response-recovery). Method: The predicted strong wind damage function proposed in this study took into account the re-enactment boy power, weather data and local characteristics at the time of damage. The meteorological data utilized the wind speed, temperature, and damage history observed by the Korea Meteorological Administration, the disaster year, and the recovery costs, population, vinyl house area, and farm water contained in the disaster report as factors to reflect the regional characteristics. Result: The function developed in this study reflected the predicted weather factors and local characteristics based on the history of strong wind damage in the past, and the extent of damage can be predicted in a short time. Conclusion: Strong wind damage prediction functions developed in this study are believed to be available for effective disaster management, such as decision making by policy-makers, deployment of emergency personnel and disaster prevention resources.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.3
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• pp.41-49
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• 2007

In order to reduce the amount of damage from natural disasters and perform the natural disaster mitigation program, the prevention activities and forecasting based on meteorological parameters and disaster datas are required. In addition, it is necessary to process prevention meteorological information for prevention activities in advance. For this, we have analyzed four data, such as Statistical yearbook of calamities and Statistics Yearbook issued by the Ministry of Government Administration and Human affairs. And Annual Climatological Report issued by the Korea Meteorological Administration and Recently 10 years for natural disaster damage from the Central Disaster and Safety Countermeasures Headquarters. We analyzed the causes, elements, occurrence frequencies, and vulnerable areas of natural disaster, using the 4 disaster datas, but these datas was not consistent with their terminology and items. Through the analysis of a kind and damage of disaster, we have selected the disaster variables, such as causes and elements, the amount of damage, vulnerable areas of natural disaster, etc and made a database. This database will be used to assess the natural disasters and develop the risk model and natural disasters mitigation plan.

• Environmental Engineering Research
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• v.18 no.1
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• pp.9-20
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• 2013

In this paper, the rainfall elasticity of streamflow was estimated to quantify the effects of climate change on 5 river basins. Rainfall elasticity denotes the sensitivity of annual streamflow for the variations of potential annual rainfall. This is a simple, useful method that evaluates how the balance of a water cycle on river basins changes due to long-term climate change and offers information to manage water resources and environment systems. The elasticity method was first used by Schaake in 1990 and is commonly used in the United States and Australia. A semi-distributed hydrological model (SLURP, semi-distributed land use-based runoff processes) was used to simulate the variations of area streamflow, and potential evapotranspiration. A nonparametric method was then used to estimate the rainfall elasticity on five river basins of Korea. In addition, the A2 (SRES IPCC AR4, Special Report on Emission Scenarios IPCC Fourth Assessment Report) climate change scenario and stochastic downscaling technique were used to create a high-resolution weather change scenario in river basins, and the effects of climate change on the rainfall elasticity of each basin were then analyzed.