• Proceedings of the Fisheries Business Administration Society of Korea Conference
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• 2005.11a
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• pp.1-28
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• 2005

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.65-78
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• 2023

In recent times, the frequency and intensity of natural disasters, such as heavy rains and typhoons, have been increasing due to the impacts of climate change. This has led to a rise in social and economic damages. Rural areas, in particular, possess limited disaster response capabilities due to their underdeveloped infrastructure and are highly vulnerable to flooding. Therefore, it is crucial to establish preventative and responsive measures. In this study, an Inventory-Based Flood Loss Estimation (IB-FLE) method utilizing high-resolution spatial information was developed for estimating flood-related losses in rural areas. Additionally, the developed approach was applied to a study area and compared with the Multidimensional Flood Damage Analysis (MD-FDA) method. Compared to the MD-FDA, the IB-FLE enables faster and more accurate estimation of flood damages and allows for the assessment of individual building and agricultural land losses using up-to-date information. The findings of this study are expected to contribute to the rational allocation of budgets for rural flood damage prevention and recovery, as well as enhancing disaster response capabilities.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.154-163
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• 2018

Not only South Korea but also Global world show that the frequency and damages of large-scale natural disaster due to the rise of heavy rain event and typhoon or hurricane intensity are increasing. Natural disasters such as typhoon, flood, heavy rain, strong wind, wind wave, tidal wave, tide, heavy snow, drought, earthquake, yellow dust and so on, are difficult to estimate the scale of damage and spot. Also, there are many difficulties to take action because natural disasters don't appear precursor phenomena However, if scale of damage can be estimated, damages would be mitigated through the initial damage action. In the present study, therefore, wind wave damage estimation functions for the western coastal zone are developed based on annual disaster reports which were published by the Ministry of Public Safety and Security. The wind wave damage estimation functions were distinguished by regional groups and facilities and NRMSE (Normalized Root Mean Square Error) was analyzed from 1.94% to 26.07%. The damage could be mitigated if scale of damage can be estimated through developed functions and the proper response is taken.

• Spatial Information Research
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• v.17 no.2
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• pp.243-249
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• 2009

Damages from typhoon events have contributed more than 60 percent of total economic and social loss and the size of loss have been increased up to 800 million dollars per year in Korea, It is therefore necessary to make an effort to mitigate the loss of natural disasters. To facilitate the evaluation of damages in advance and to support the decision making to recover the damages, scientific methods have been adopted. With the effort, GIS data can provide various tools. Three components of hazard mapping are estimation of hazard, inventory for vulnerable features, and fragility of each feature. Vulnerability of natural disaster can be obtained by relation between loss and meteorological data such as precipitation and wind speed. Features can be categorized from other GIS data of public facilities and private properties, and then social and economic loss can be estimated. At this point, GIS data conversions for each model are required. In this study, we build a method to estimate typhoon risk based on GIS data such as DEM, land cover and land use map, facilities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.61-72
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• 2017

Due to the climate change, damages of human life and property caused by natural disaster have recently been increasing consistently. In South Korea, total damage by natural disasters over 20 years from 1994 to 2013 is about 1.0 million dollars. The 13% of total damage caused by heavy snow. This is smaller amount than the damage by heavy rainfall or typhoon, but still could cause severe damage in the society. In this study, the snow damage in Gangwon region was estimated using climate variables (daily maximum snow depth, relative humidity, minimum temperature) and scoio-economic variables (Farm population density, GRDP). Multiple regression analysis with enter method was applied to estimate snow damage. As the results, adjusted R-square is above 0.7 in some sub-regions and shows the good applicability although the extreme values are not predicted well. The developed model might be applied for the prompt disaster response.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.325-331
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• 2017

Due to the climate change, natural disaster has been occurred more frequently and the number of snow disasters has been also increased. Therefore, many researches have been conducted to predict the amount of snow damages and to reduce snow damages. In this study, snow damages over last 21 years on the Natural Disaster Report were analyzed. As a result, Chungcheong-do, Jeolla-do, and Gangwon-do have the highest number of snow disasters. The multiple linear regression models were developed using the snow damage data of these three provinces. Daily fresh snow depth, daily maximum, minimum, and average temperatures, and relative humidity were considered as possible inputs for climate factors. Inputs for socio-economic factors were regional area, greenhouse area, farming population, and farming population over 60. Different regression models were developed based on the daily maximum snow depth. As results, the model efficiency considering all damage (including low snow depth) data was very low, however, the model only using the high snow depth (more than 25 cm) has more than 70% of fitness. It is because that, when the snow depth is high, the snow damage is mostly caused by the snow load itself. It is suggested that the 25 cm of snow depth could be used as the snow damage threshold based on this analysis.

• Journal of the Korean Society of Safety
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• v.12 no.1
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• pp.51-59
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• 1997

These days leakage incidents of toxic materials cause serious effects on the nearby residents as well as the workers around the accidents accompanying massive material losses and human damages through widening influential areas. The risk measure through adequate quantitative analysis as well as the qualitative analysis of the leakage incidents of toxic materials becomes an urgent issue. The damage of the leakage incident on the surrounding area of the dangerous toxic material facilities was calculated quantitatively by adopting several models in this research. First, the calculations of the leakage velocity from the factories were performed by using source model for the assessment of the influential area, and the damages on the nearly residents were calculated by using the dispersion model and the effort model. The probability of the Incidents was computed based on "The manual for classification and priorization of major incidents" published by IAEA( International Atomic Energy Agency ). Above calculated damage area and incident probability were further adopted in this study to induce the individual and societal risk, quantitatively. The calculated data of the real Incident of the toxic material leakage showed reasonable agreements to the actual damage of the incidents, which showed a validity of this study. The result of this study might be a helpful measure for predicting damages and preparing safety systems for similar kinds of incidents.incidents.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.1 s.94
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• pp.53-62
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• 2005

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.625-632
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• 2004

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.2
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• pp.65-73
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• 2008

Since the damages caused by disasters increase every year associated with wrenching climatic changes and the diversification of the social structure, the efficient management system is required to reduce damages and an assessment of the vulnerable disaster areas is necessary to prevent and mitigate the damages. In this paper, we have estimated the vulnerable disaster areas based on the records of the past damage histories and performed the risk assessment of the social infrastructures in Busan city to provide the fundamental information for the real-time monitoring system and the systematic approach for disaster prevention system to build V-City model. These results are illustrated by using Geographical Information System (GIS) and the order of vulnerable disaster areas are also estimated.