• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.98-103
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• 2009

The forecasting, mitigation and preparedness of the natural disaster impacts require relevant information regarding the disaster desirable in real time. In the meantime it is requiring the rapid and continuous data and information generation or gathering for possible prediction and monitoring of the natural disaster. Since disasters that cause huge social and economic disruptions normally affect large areas or territories and are linked to global change. The use of traditional and conventional methods for management of the natural disaster impact can not be effectively implemented for intial data col1ection with the further processing. The space technology or remote sensing tools offer excellent possibilities of collecting vital data. The main reason is capability of this technology of collecting data at global and regional scales rapidly and repetitively. This is unchallenged advantage of the space methods and technology. The satellite or remote sensing techniques can be used to monitor the current situation, the situation before based on the data in sight. as well as after disaster occurred. They can be used to provide baseline data against which future changes can be compared while the GIS techniques provide a suitable framework for integrating and analyzing the many types of data sources required for disaster monitoring. Developed GIS is an excellent instrument for definition of the social impact status of the natural disaster which can be undertaken in the future database developments. This methodology is a good source for analysis and dynamic change studies of the natural disaster impacts.

• 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.

• Journal of the Korean Society of Safety
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• v.38 no.6
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• pp.50-59
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• 2023

As the diversity of disasters continues to increase, the concept of "complex disasters" has gained prominence in various policies and studies related to disaster management. However, there has been a certain limitation in the availability of the systematic statistics or data in advancing policies and research initiatives related to complex disasters. This study aims to analyze the macro-level characteristics of the complex disasters that have occurred domestically utilizing a 30-year span of a news data. Initially, we categorize the complex disasters into the three types: "Natural disaster-Natural disaster", "Natural disaster-Social disaster", and "Social disaster-Social disaster". As a result, the "natural diaster-social disaster" type is the most prevalent. It is noted that "natual disaster-natural disaster" type has increased significantly in recent 10 years (2011-2020). In terms of specific disaster types, "Storm and Flood", "Collapse", "Traffic Accident", "National Infrastructure Paralysis", and "Fire⋅Explosion" occur the most in conjunction with other disasters in a complex manner. It has been observed that the types of disasters co-ocuuring with others have become more diverse over time. Parcicularly, in recent 10 years (2011-2020), in addition to the aforementioned five types, "Heat Wave", "Heavy Snowfall⋅Cold Wave", "Earthquake", "Chemical Accident", "Infectious Disease", "Forest Fire", "Air Pollution", "Drought", and "Landslide" have been notable for their frequent co-occurrence with other disasters. These findings through the statistical analysis of the complex disasters using long-term news data are expected to serve as crucial data for future policy development and research on complex disaster management.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.53-61
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• 2021

The quantified analysis of damages to wastewater treatment plants by natural disasters is essential to maintain the stability of wastewater treatment systems. However, studies on the quantified analysis of natural disaster effects on wastewater treatment systems are very rare. In this study, a total disaster index (DI) was developed to quantify the various damages to wastewater treatment systems from natural disasters using two statistical methods (i.e., AHP: analytic hierarchy process and PCA: principal component analysis). Typhoons, heavy rain, and earthquakes are considered as three major natural disasters for the development of the DI. A total of 15 input variables from public open-source data (e.g., statistical yearbook of wastewater treatment system, meteorological data and financial status in local governments) were used for the development of a DI for 199 wastewater treatment plants in Korea. The total DI was calculated from the weighted sum of the disaster indices of the three natural disasters (i.e., TI for typhoon, RI for heavy rain, and EI for earthquake). The three disaster indices of each natural disaster were determined from four components, such as possibility of occurrence and expected damages. The relative weights of the four components to calculate the disaster indices (TI, RI and EI) for each of the three natural disasters were also determined from AHP. PCA was used to determine the relative weights of the input variables to calculate the four components. The relative weights of TI, RI and EI to calculate total DI were determined as 0.547, 0.306, and 0.147 respectively.

• 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.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.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.309-319
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• 2007

Right comprehension of the natural disaster could reduce the damage of human life and property by explaining the cause of the disaster and considering a counterplan to decrease or prevent it. To do this, it should precede to clarify the category of the natural disaster and classification. Also, when the disaster occurs, swift site survey and the establishment of the data by the professionals should be done for clarifying the reason. Our classification of the natural disaster is written on the Law of the Nature Disaster Relief. But, this classification is made for the management of the disaster, so it is required to review the establishment of the technical information by the professionals. Therefore, the Korean type classification is required considered by the professionals who collect and study the information of the natural disaster for the other countries. If the DB of the natural disaster is made, it is able to get various services through the internet virtual space and it will be helpful to prepare the prevent countermeasures against the disaster. In this research, the korean type classification plan of the natural disaster is suggested which is suitable to the professional technology by collecting and analyzing the domestic and the international classification of the natural disaster.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1105-1115
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• 2015

Big data analysis for disaster have been recently started especially to text data such as social media. Social data usually supports for the final two stages of disaster management, which consists of four stages: prevention, preparation, response and recovery. Otherwise, big data analysis for meteorologic data can contribute to the prevention and preparation. This motivated us to review big data technologies dealing with non-text data rather than text in natural disaster area. To this end, we first explain the main keywords, big data, data mining and machine learning in sec. 2. Then we introduce the state-of-the-art machine learning techniques in meteorology-related field sec. 3. We show how the traditional machine learning techniques have been adapted for climatic data by taking into account the domain specificity. The application of these techniques in natural disaster response are then introduced (sec. 4), and we finally conclude with several future research directions.

• 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.

• 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.