• International Journal of Highway Engineering
• /
• v.20 no.1
• /
• pp.35-45
• /
• 2018

PURPOSES : This study examines the performance changes of road networks according to the strength of a disaster, and proposes a method for estimating the quantitative resilience according to the road-network performance changes and damage scale. This study also selected high-influence road sections, according to disasters targeting the road network, and aimed to analyze their hazard resilience from the network aspect through a scenario analysis of the damage recovery after a disaster occurred. METHODS : The analysis was conducted targeting Sejong City in South Korea. The disaster situation was set up using the TransCAD and VISSIM traffic-simulation software. First, the study analyzed how road-network damage changed the user's travel pattern and travel time, and how it affected the complete network. Secondly, the functional aspects of the road networks were analyzed using quantitative resilience. Finally, based on the road-network performance change and resilience, priority-management road sections were selected. RESULTS : According to the analysis results, when a road section has relatively low connectivity and low traffic, its effect on the complete network is insignificant. Moreover, certain road sections with relatively high importance can suffer a performance loss from major damage, for e.g., sections where bridges, tunnels, or underground roads are located, roads where no bypasses exist or they exist far from the concerned road, including entrances and exits to suburban areas. Relatively important roads have the potential to significantly degrade the network performance when a disaster occurs. Because of the high risk of delays or isolation, they may lead to secondary damage. Thus, it is necessary to manage the roads to maintain their performance. CONCLUSIONS : As a baseline study to establish measures for traffic prevention, this study considered the performance of a road network, selected high-influence road sections within the road network, and analyzed the quantitative resilience of the road network according to scenarios. The road users' passage-pattern changes were analyzed through simulation analysis using the User Equilibrium model. Based on the analysis results, the resilience in each scenario was examined and compared. Sections where a road's performance loss had a significant influence on the network were targeted. The study results were judged to become basic research data for establishing response plans to restore the original functions and performance of the destroyed and damage road networks, and for selecting maintenance priorities.

• Journal of the Society of Disaster Information
• /
• v.17 no.3
• /
• pp.556-567
• /
• 2021

Purpose: In this study, various methods of deep learning-based automatic damage analysis technology were reviewed based on images taken through Unmanned Aerial Vehicle to more efficiently and reliably inspect the exterior inspection and inspection of railway bridges using Unmanned Aerial Vehicle. Method: A deep learning analysis model was created by defining damage items based on the acquired images and extracting deep learning data. In addition, the model that learned the damage images for cracks, concrete and paint scaling·spalling, leakage, and Reinforcement exposure among damage of railway bridges was applied and tested with the results of automatic damage analysis. Result: As a result of the analysis, a method with an average detection recall of 95% or more was confirmed. This analysis technology enables more objective and accurate damage detection compared to the existing visual inspection results. Conclusion: through the developed technology in this study, it is expected that it will be possible to analysis more accurate results, shorter time and reduce costs by using the automatic damage analysis technology using Unmanned Aerial Vehicle in railway maintenance.

• Journal of Cadastre & Land InformatiX
• /
• v.50 no.2
• /
• pp.81-100
• /
• 2020

The purpose of this study was to propose applicability of spatial data and quality check criteria for estimating damage from storm and flood. Using the data from the National Disaster Management System and National Spatial Data Infrastructure, spatial database for estimation of storm and flood damage has been mapped to each type of damage. This was proposed as the quality check criteria for damage analysis. Through this study, it is possible to utilize the spatial database for estimating storm and flood damage. The reliability of analysis results are ensured through the quality check criteria.

• Journal of Korean Society of Disaster and Security
• /
• v.14 no.1
• /
• pp.51-59
• /
• 2021

In Korea, where 64% of the soil is mountainous, typhoons and local rains concentrated in the summer season are frequent in mountainous disasters such as landslides and debris flow. The area of study was the area where the damage to the debris flow was caused by typhoon Mitag in October 2019, and all the houses located in the downstream area were damaged. In this study, numerical simulations were conducted on the area where the damage of earth and stone flow occurred using Hyper KANAKO model that can consider erosion and sedimentation, and the applicability of the model was examined by comparing the actual damage area and the analysis results of the model. As a result of the numerical simulation, the damage area of the debris flow in the target area was 53,875 m², the maximum flow depth was 2.4 m, and the average flow depth was 1.7 m.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.2
• /
• pp.125-136
• /
• 2018

Heavy snowfall disasters are the third most serious natural disasters, after typhoon and heavy rainfall disasters, in terms of economic disaster damage in South Korea. The average annual economic damage of heavy snowfall disasters was approximately eighty-eight billion won during the period of 2005-2014. In spite of significant economic damage, there have been few economic studies regarding heavy snowfall disasters in South Korea. The objective of this research is to identify the association between economic damage of heavy snowfall disasters and damage effect factors of snowfall amounts, snowfall days, population densities, and non-urban area ratios using a regression analysis model. Economic damage data sets of heavy snowfall disasters during the period of 2005-2014 were obtained from the Natural Disaster Yearbook published by the Ministry of Public Safety and Security. Weather-related data sets, such as snowfall amounts and snowfall days were collected from the Korea Meteorological Administration. Demographic and urban data sets, including population densities and non-urban area ratios, were provided by the Local Government Yearbook. Outcomes of this study can assist with heavy snowfall disaster management policies of South Korea.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_2
• /
• pp.861-871
• /
• 2019

Landsat satellite images have been increasingly used for disaster damage analysis and disaster monitoring because they can be used for periodic and broad observation of disaster damage area. However, periodic disaster monitoring has limitation because of areas having missing data due to clouds as a characteristic of optical satellite images. Therefore, a study needs to be conducted for restoration of missing areas. This study detected and removed clouds and cloud shadows by using the quality assessment (QA) band provided when acquiring Landsat-8 images, and performed image restoration of removed areas through a spatial and temporal adaptive reflectance fusion (STARFM) algorithm. The restored image by the proposed method is compared with the restored image by conventional image restoration method throught MLC method. As a results, the restoration method by STARFM showed an overall accuracy of 89.40%, and it is confirmed that the restoration method is more efficient than the conventional image restoration method. Therefore, the results of this study are expected to increase the utilization of disaster analysis using Landsat satellite images.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.5
• /
• pp.39-47
• /
• 2016

The houses are formed in the lower part of the mountain slope face in most agricultural areas of Korea, and old residents accounting for a large portion of the agricultural populations cannot respond to the evacuation quickly when the landslide happens, and the possibility the life damage occurs is high. Therefore, it is urgent to arrange the measure on this. This study is intended to develop the personal disaster evacuation apparatus that can be installed in the house to minimize the life damage by the landslide and to develop the self-initiative evacuation apparatus. This study suggested the load applicable to the personal disaster evacuation apparatus by quantitatively analyzing the effect of the load of rockslides and avalanches caused by the landslide on the structure. Also, the material property of materials was calculated through the tension and bending intensity test after making the specimen of glass fiber reinforced plastic (GFRP) member. The load weight and material property drawn from this study can be used as the basic material for the stability analysis of the personal disaster evacuation apparatus.

• Journal of the Korea Institute of Building Construction
• /
• v.16 no.5
• /
• pp.437-445
• /
• 2016

Since typhoon is a critical meteorological disaster, some advanced countries have developed typhoon damage prediction models. However, although South Korea is vulnerable to typhoons, there is still shortage of study in typhoon damage prediction model reflecting the vulnerability of domestic building and features of disaster. Moreover, many studies have been only focused on the characteristics and typhoon and regional characteristics without various influencing factors. Therefore, the objective of this study is to analyze typhoon damage by path and develop to prediction model for building damage ratio by using multiple regression analysis. This study classifies the building damages by typhoon paths to identify influencing factors then the correlation analysis is conducted between building damage ratio and their factors. In addition, a multiple regression analysis is applied to develop a typhoon damage prediction model. Four categories; typhoon information, geography, construction environment, and socio-economy, are used as the independent variables. The results of this study will be used as fundamental material for the typhoon damage prediction model development of South Korea.

• Tunnel and Underground Space
• /
• v.25 no.1
• /
• pp.37-45
• /
• 2015

Recently, many cities have always been affected by large natural disasters such as floods and landslides. As climate change causes more frequent localized heavy rains exceeding the conveyance capacity of sewer, flood damage is expected to increase. For the sake of reducing the urban flood damage by changed rainfall, there has been many trials on installation of runoff-reducing facilities. Therefore, it was required to study about reasonable analysis and countermeasure of rainwater storage facility project for extending it. This study was to review the status of rainwater storage facility project for the urban disaster prevention in Busan, to find out problems, and to propose the countermeasure of rainwater storage facility project for the urban disaster prevention.

• Journal of the Korean Society of Safety
• /
• v.35 no.2
• /
• pp.84-93
• /
• 2020

In recent years, the scale of damage from disasters such as earthquakes and large-scale fires and floods that are occurring in Korea is increasing. Accordingly, interest in urban disaster prevention that combines living infrastructure such as roads and parks is boosting, and it is urgent to prepare measures to reduce the damage scale of local cities. The purpose of this study is to derive implications for disaster prevention measures in areas where disaster prevention safety of local cities is weak through examples of disaster prevention safety of local cities in case of disaster. To this end, this study analyzed the regional characteristics, current status, and disaster prevention problems of regional cities in Japan, and selected disaster-vulnerable areas, and considered the distance relationship between disaster prevention bases through road network analysis. In addition, road closure simulation using ArcGIS Network Analyst was conducted to analyze disaster prevention safety in the area. As a result, the situation of the village which has a high possibility of isolation by natural disasters was grasped in advance. Through this, the suburbs confirmed the necessity of supplementing the disaster prevention function through transportation maintenance such as forest roads, and it was found that the city needs to prepare a risk management system. Furthermore, this study suggests the need for research on areas with a high possibility of isolation, especially in areas where disaster prevention functions are weak in local cities in case of disaster, and shows countermeasures for disaster prevention measures and resident education.