• Journal of Environmental Science International
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• v.17 no.4
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• pp.413-422
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• 2008

This study aims to find out a state of the damages and vulnerable areas from natural disasters in the Korean peninsula using the prevention meteorological database information made by Park(2007b). Through the correlation analysis between damage elements and total property losses, we investigate the damages of public facilities, which have high correlation coefficient, and the cause of disasters and want to propose the basic information to set up the disaster prevention measures in advance. As a result, because most of the total property losses is the damages of public facilities, we can reduce the damages of natural disasters if we can predict the damages of public facilities or carry out the prevention activities in advance. The most vulnerable area for the natural disasters are Cangwon-do and Gyeongsangnam-do provinces. The vulnerable areas for the damages of public facilities by typhoon are Daegu metropolitan city, Cangwon-do, and Gyeongsangbuk-do provinces. These vulnerable areas will take place more frequently due to the climate change including Gyeongsangnam-do province so that we need to set up the disaster prevention measures and natural disaster mitigation plan. Also, we think that it has effect on reducing the damages of natural disasters to predict the damage scale and strongly perform the prevention activities in advance according to typhoon track and intensity.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.12-19
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• 2011

Drawing on its extensive experience with natural disasters, Japan has been dispatching Japan Disaster Relief (JDR) team to disaster-stricken countries to provide specialist assistance in rescue and medical operations. The JDR team has assisted in the wake of disasters including the 2004 Indian Ocean Earthquake and the 2008 Sichuan Earthquake in China. Information about the affected area is essential for a rapid disaster response. However, it can be difficult to gather information on damages in the immediate post-disaster period. To help overcome this problem, we have built on an Earthquake Damage Estimation System. This system makes it possible to produce distributions of the earthquake's seismic intensity and structural damage based on pre-calculated data such as landform and site amplification factors for Peak Ground Velocity, which are estimated from a Digital Elevation Model, as well as population distribution. The estimation result can be shared with the JDR team and with other international organizations through communications satellite or the Internet, enabling more effective rapid relief operations.

• Journal of Environmental Policy
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• v.10 no.1
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• pp.151-173
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• 2011

Whenever several natural disasters hit Korea with huge damage of property loss and death toll, government spends huge sums of money for rehabilitation of devastated areas every year. It's time to discuss about a natural disaster insurance, which is a long-term as well as precautionary measure. It is advisable to discuss government involvement through the natural disaster insurance, implementation of countermeasures against natural disasters. The natural disasters insurance have to executed as follows, 1) introducing natural disaster insurance with characteristics of social welfare, which makes fast recovery and anxiety reduction in the low-income bracket. 2) advisable to mix the methods of microinsurance including the natural disaster and index insurance.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.1-7
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• 2022

In this paper, a study was conducted to predict natural disasters in Afghanistan based on machine learning. Natural disasters need to be prepared not only in Korea but also in other vulnerable countries. Every year in Afghanistan, natural disasters(snow, earthquake, drought, flood) cause property and casualties. We decided to conduct research on this phenomenon because we thought that the damage would be small if we were to prepare for it. The Azure Machine Learning Studio used in the study has the advantage of being more visible and easier to use than other Machine Learning tools. Decision Forest is a model for classifying into decision tree types. Decision forest enables intuitive analysis as a model that is easy to analyze results and presents key variables and separation criteria. Also, since it is a nonparametric model, it is free to assume (normality, independence, equal dispersion) required by the statistical model. Finally, linear/non-linear relationships can be searched considering interactions between variables. Therefore, the study used decision forest. The study found that overall accuracy was 89 percent and average accuracy was 97 percent. Although the results of the experiment showed a little high accuracy, items with low natural disaster frequency were less accurate due to lack of learning. By learning and complementing more data, overall accuracy can be improved, and damage can be reduced by predicting natural disasters.

• Smart Structures and Systems
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• v.11 no.1
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• pp.69-86
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• 2013

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.90-95
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• 2012

Remotely sensed data provide valuable information on land monitoring due to multi-temporal observation over large areas. Especially, high resolution imagery with 0.6~1.0 m spatial resolutions contain a wealth of information and therefore are very useful for thematic mapping and monitoring change in urban areas. Recently, remote sensing technology has been successfully utilized for natural disaster monitoring such as forest fire, earthquake, and floods. In this paper, an efficient change detection method based on texture differences observed from high resolution multi-temporal data sets is proposed for mapping disaster damage and extracting damage information. It is composed of two parts: feature extraction and detection process. Timely and accurate information on disaster damage can provide an effective decision making and response related to damage.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.846-853
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• 2005

The whole death by disaster is totalized to 1,515 person from 1993 to 2004 year in our country. In this section life damages by landslide is totalized 357 people(about 24% of whole life damage). About 36 people are died by landslide(such as cutting area failure every year). Kangwon-do need a lot of interests and prevention because dangerous area that landslide occurrence is more than other area at summer localized downpour or thawing season and there is landslide occurrence possibility area more than other area. Kangwon-do area is higher than other area in natural disaster incidence and damage scale because topography and a lot of rainfalls by summer localized in Kangwon-Do than other area. In this study, dangerous area of landslide occurrence possibility is analyzed and compared Kangwon-Do with other areas in our country. as a result, every year we have experienced landslide occurrence and natural disaster. accordingly, we urgently need to prevent landslide occurrence and natural disaster by analy-zed source about landslide occurrence and condition of disaster in Kangwon-Do and suitable engineering method and construction work.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.71-83
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• 2013

Recently frequencies and scales in natural disasters have been significantly increased and enlarged and that leads to increase interests on preventing disasters. As natural disasters occur, it is difficult to fulfill the scale of natural disasters using ordinary stocks in a local government. Thus, it is necessary to establish a system that commonly uses protection resources according to regional characteristics in order to rapidly implement labor mobilization and equipment distribution based on the damage of natural disasters. In this study, regional characteristics in Korea provinces are analyzed and 'a way of composing a local government consortium for common disaster responses' is proposed. First, a disaster map that represents the amount of damage for each local government published in the disaster yearbook from 2002 to 2011 is produced using GIS. Then, the whole land is divided into five different sections according to administrative regions and that are divided into 12 clusters again based on the geographical and humanistic characteristics and the analysis of the scale of damage in typhoons and heavy rainfalls. Finally, disaster protection base stations for each region are selected. The data of analyzing disaster damages may be used as a reference material for establishing disaster prevention plans.

• Journal of Korean Society of societal Security
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• v.1 no.2
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• pp.73-78
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• 2008

Recently, large scale natural disasters such as floods and typhoons due to climate change have been occurring all over the world causing severe damages. Among the various efforts to reduce and recover damages, recently, advanced information technology and remote sensing techniques are applied in disaster management. In this study, a real-time automated damage estimation system using information technology and spatial imagery was developed to accomplish prompt and accurate disaster damage estimation. This system is able to estimate the damage amounts of public facilities such as roads, rivers, bridges automatically through spatial imageries including ground based digital images, aerial photos, satellite images of disaster sites. Based on these spatial imageries, the damage amounts are analyzed in the Web-GIS based analysis system. Consequently, the digital damage reports such as digital disaster information sheets and damage maps can be made promptly and accurately. This system can be a useful tool to carry out prompt disaster damage estimation and efficient disaster recovery.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.318-321
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• 2004

The damage scale and damage area in the coast have been increased dramatically because of calamities such as typhoon. tidal wave. flood and storm. Especially. 409 cases. which reach to about $40.9\%$ of natural disasters of 1,000 cases for the recent 15 years have happened on coast area. More than $40\%$ of natural disasters also occurred every year is happening in coastland. Therefore, there is a great need to construct all related GIS database such as atmospheric phenomena (typhoon. tidal wave, flood and storm). harbor facility, harbor traffic and ebb and flow. Furthermore. the certain system should be developed and integrated with NDMS (National Disaster Management System) by using 3D web GIS technology. In this study. the coast disaster area management system was designed and developed by using 3D web GIS technique so that the coast disaster area could be monitored and managed in real time and in visual. Finally. the future disaster in coast area could be predicted scientifically.