• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.819-829
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• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

• Journal of Environmental Science International
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• v.14 no.6
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• pp.613-619
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• 2005

Recently, we are suffered enormous loss from a natural disaster and making an effort to prepare measures for dealing with disasters. This study shows the major causes of natural disasters and stricken area with the analysis of meteorological data based on the Korean Meteorological Administration and the Central Disaster Relief Center records during 1987-2003 and classifies natural disasters according to the causes and damaged conditions. In this study, the most damaged area were Gangwon, Gyeongnam and Gyeongi province as a result of a typhoon and a localized heavy rain. To establish an effective disaster measure for these area, detailed prevention plans should be established by its causes after investigating precise regional damage data analysis.

• International Journal of Highway Engineering
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• v.16 no.3
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• pp.59-66
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• 2014

PURPOSES : This study is to suggest heavy snow risk analysis in Seoul. METHODS : Recently, the increase of extreme weather caused by global warming raises the occurrences of unpredictable natural disasters and the loss potential of human disasters by land use facilities accumulation. It is necessary to develop the risk analysis for the natural and human disasters. RESULTS : In this study, heavy snow risk analysis among natural disasters in Seoul was suggested. The spatial unit of risk analysis level was established for the lines and administrative districts. CONCLUSIONS : The risk analysis was performed using risk matrix of disaster occurrence score and disaster damage score. The components affecting the risk disaster analysis by types were analyzed and the application of heavy snow risk analysis was suggested.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.309-312
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• 2008

In Korea, although the damage from disaster (flood and storm) is increasing, the early stage warning and countermeasure are not in operation rapidly. The research areas of transportation engineering arenot diverse, so once the road is flooded and interrupted, drivers, the system operators and managers are in panic, and nearby roads are in terrible traffic congestion. In case of Korea, the research of evacuation is highly needed, because it is very necessary and easy to apply in real field. In this paper, we establish the concept of transportation disaster prevention system and suggest the directions of it. In addition, based on this research, we choose one example of disasters and establish an example of the transportation disaster prevention system. Our goal is to make steps; prevention, preparation, countermeasure and restoration in the view of minimizing on social chaos and damages emphasizing aspect of transportation countermeasure. This research will be the good precedent of approach, analysis and countermeasure when the disasters are occurred, and a basis of transportation disaster prevention system and manual in Korea.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.227-232
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• 2022

Disasters are now becoming commonplace and especially the vulnerable group such as the disabled, the elderly, children and foreigners are in a state of overlapping disasters. In this situation, ATSC 3.0-based UHDTV disaster information service for the visually and hearing impaired has been developing. This study focuses on the demand data collected through in-depth interview with the impaired. The demand analysis data is very important to development process of technology. The results of the interview show that it is essential to link the UHDTV disaster signals with home-network, IoT, wearable devices, and various assistive devices for the impaired (hearing aid, smart light bulbs, warning light, etc.). In outdoor space, UHDTV disaster information must be connected to public display media, digital signage, kiosk, screens in bus or taxi. If communication aids for the visually and hearing impaired are equipped with a function that can transmit and receive disaster information, it will help to minimize disaster damage.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.565-576
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• 2024

In this study, the earthquake risk assessment of single-story RC precast buildings in Turkey was carried out using loss curves. In this regard, Kocaeli, a seismically active city in the Marmara region, and this building class, which is preferred intensively, were considered. Quality and period parameters were defined based on structural and geometric properties. Depending on these parameters, nine main sub-classes were defined to represent the building stock in the region. First, considering the mean fragility curves and four different central damage ratio models, vulnerability curves for each sub-class were computed as a function of spectral acceleration. Then, probabilistic seismic hazard analyses were performed for stiff and soft soil conditions for different earthquake probabilities of exceedance in 50 years. In the last step, 90 loss curves were derived based on vulnerability and hazard results. Within the scope of the study, the comparative parametric evaluations for three different earthquake intensity levels showed that the structural damage ratio values for nine sub-classes changed significantly. In addition, the quality parameter was found to be more effective on a structure's damage state than the period parameter. It is evident that since loss curves allow direct loss ratio calculation for any hazard level without needing seismic hazard and damage analysis, they are considered essential tools in rapid earthquake risk estimation and mitigation initiatives.

• Smart Structures and Systems
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• v.26 no.1
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• pp.23-33
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• 2020

Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

• Economic and Environmental Geology
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• v.47 no.2
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• pp.133-146
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• 2014

There are many studies for the economic impact assessment of natural disasters, but there are few for volcanic disasters. Domestic academic research is not under active discussion because of the lack of national and social interest for volcanic eruption. This study investigated the research methodology for the economic impact assessment of natural disasters and discussed whether these can be applied to the economic impact analysis for the Baekdu Mountain volcanic disaster. The main findings are as follows: Firstly, Asia-Pacific region is the most affected by natural disasters and has the largest scale of damage. Asian and American Continent have the most economic damage. Secondly, Considering the types of damage caused by natural disasters and its complex structure, several methodologies that could be possible to estimate economic consequential damages have been compared. When applying each methodology to the Baekdu Mountain volcanic disaster, the scale of damage is likely to be over-estimated or under-estimated because of model-specific features. Thus, estimated values should be compared to each other after calculating the damage results. Thirdly, Japanese academic research on the volcanic disaster will be used as the starting point of the economic impact assessment studies for Baekdu Mountain. Using computer SW such as Hazus which is used in United States and RiskScape from New Zealand is also a good method to predict economic impact of the Baekdu Mountain volcanic disaster.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.493-504
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• 2020

Purpose: The purpose of this study is to propose an analytical methodology for selecting the priority of preventive projects in the course of carrying out disaster prevention projects that improve disaster-hazardous areas. Method: Data analysis was performed using RFM model which can divide data grade and perform target marketing based on Recency, Frequency, and Monetary. Result: The top 10% of the area with high RFM value was mainly in the East Sea and the South Sea coast, and the number of damage in private facilities was high. Conclusion: In this study, we used the RFM model to select the priority of disaster risk and to implement the regional disaster risk using GIS. These results are expected to be used as basic data for selecting priority project sites for disaster prevention projects and as basic data in the decision-making process for disaster prevention projects.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.340-343
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• 2009

Recently, the lightning damage to human and structure is increasing steadily and many countries try to reduce lightning-caused casualties and economical loss through special disaster management system. The organization of warning system and management system for lightning damage in developed countries were investigated in this paper. The organization of central government for disaster management and cooperation system with local government in USA, Japan, the Britain, and Germany were introduced and the division of roles with meteorological administration were described.