• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.149-157
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• 2016

Understanding regional characteristics in forest fire occurrence is important to establish effective forest fire prevention policy in Korea. This study analyzed the characteristics of forest fires occurred in 16 administrative districts for recent 25 years (1990~2014) to examine regional characteristics in forest fire occurrence. Forest fire occurrence reflects regional characteristics depending on climatic factors as well as region's society-cultural factors. Results showed that the first cause of forest fire occurrence was carelessness by human activities throughout all administrative districts, however, the second cause depends on regional characteristics. As the results of forest fire occurrence period analyzed for 10 days, the most forest fires occurred in the southern region during January to March, while forest fires in the northern region occurred mostly during March to April. We classified forest fire occurrence patterns into three types (centralized: Gyeonggi-do, dispersal: Busan, horizontally distributed: Gyeongsangnam-do) by multi-temporal analysis for forest fire occurrence period.

• Asian Journal of Atmospheric Environment
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• v.10 no.1
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• pp.22-31
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• 2016

Active fire products from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observation during the 16 years from 2000-2015 were analyzed to estimate spatial and temporal variations of wildland fires over East Asia (region of interest: $20^{\circ}N-55^{\circ}N$, $100^{\circ}E-150^{\circ}E$). GLOBCOVER 2009 land cover data were also used to investigate the trend in wildfire occurrence with respect to each land cover type. Statistical analysis showed that the highest number of wildland fires occurred in the evergreen and vegetation covered areas, and strong seasonal variations were found in these areas. Total numbers of fires were 283,683 and 202,543, respectively. In particular, the wildland fires in croplands occurred mainly during summer season and distinguishable increasing trends were found. The correlations between number of wildland fires and air pollutants, such as black carbon, organic matter, and carbon monoxide, were also calculated in order to investigate the intensity of the air pollution caused by the wildland fires. Positive correlation between total column carbon monoxide contents and the occurrence of wildland fire was found. In addition, this correlation was higher than the correlation between fire occurrence and black carbon or organic matter. These results indicate that a significant amount of carbon monoxide originated from the wildland fires and influenced the regional atmospheric environment in East Asia.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.37-46
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, we are making an effort to improve prevention measures for forest fires. The objective of this study is to classify hazard regions where forest fires occur based on the factors that contribute to the occurrence of forest fires. Forest fire sites in the Uiseong-gun, Gyeongsangbuk-do were surveyed according to the factors of forest type and topographic characteristics where the forest fires occurred. We used a correlation analysis to determine the forest fire occurrence factors and a conditional probability analysis and GIS to determine a forest fire danger index. The resulting forest fire danger index was used in the classification of forest fire occurrence risk regions.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.163-171
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• 2010

Forest fires have potentials to change the structure and function of forest ecosystems and significantly influence on atmosphere and biogeochemical cycles. Forest fire also affects the quality of public benefits such as carbon sequestration, soil fertility, grazing value, biodiversity, or tourism. The prediction of fire occurrence and its spread is critical to the forest managers for allocating resources and developing the forest fire danger rating system. Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behaviors and its spread. Thus, meteorological factors as well as social factors were considered in the fire danger rating systems. A total of 298 forest fires occurred during the fall season from 2002 to 2006 in South Korea were considered for developing a logistic model of forest fire occurrence. The results of statistical analysis show that only effective humidity and temperature significantly affected the logistic models (p<0.05). The results of ROC curve analysis showed that the probability of randomly selected fires ranges from 0.739 to 0.876, which represent a relatively high accuracy of the developed model. These findings would be necessary for the policy makers in South Korea for the prevention of forest fires.

• Fire Science and Engineering
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• v.25 no.5
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• pp.39-46
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• 2011

In order to consider the prevention countermeasure to the occurrence of forest fires, analysing characteristic of the past forest fire data is needed. This research analyzed distribution and characteristics of forest fires damage over 30 ha based on statistics data of forest fires in Korea between 1975 and 2010. As a result, the number of forest fires damage over 30 ha as 23 was most occurred in 1978. Forest fires show an upward tendency from 1970 to 2000. Forest fires of 30 ha~50 ha damaged area was most occurred. Forest fire in Gangwon province was occurred as the number of total 66 (37.0 %). Gangwon province was superior in point density analysis. The number of forest fire occurrence over 30 ha was most high to 114 (63.0 %) in April and to 44 (24.3 %) in Sunday. The occurrence number of forest fire and damage caused by forest fire is increasing more and more since 1975, appropriate authorities can use effectively in devising policy for forest fire prevention from this result.

• Fire Science and Engineering
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• v.19 no.3 s.59
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• pp.64-69
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• 2005

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, we are making an effort to improve prevention measures for forest fires. The objective of this study is developing the forest fire occurrence probability model by means of forest site characteristics such as soil type, topography, soil texture, slope, and drainage and forest fire sites. Conditional probability analysis and GIS were used in developing the forest fire occurrence probability model that was used in the classification of forest fire occurrence risk regions.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.57-64
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, the forest fire danger rating system was developed to estimate forest fire risk by means of weather, topography, and forest type. Forest fires occurrence prediction needs to improve continually. Logistic regression and spatial analysis was used in developing the forest fire occurrence probability model. The forest fire danger index in accordance to the probability of forest fire occurrence was used in the classification of forest fire occurrence risk regions.

• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.20-27
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• 2019

Purpose: In this study, the status and the risk of fire occurrence in domestic automobile were evaluated and the damage reduction effect by using the fire extinguishing mechanism was evaluated. Method: The analysis of the risk of the occurrence of Vehicle Fires in Korea and the damage of human and property by the use of fire extinguisher applied to fire extinguisher were investigated and analyzed. Results: The annual damage rate of the damage caused by the automobile fire is 4.74%, which shows an annual increase. As a result of the analysis of the personal injury caused by the passenger car in the car fire situation, the damage amount per 100 cases of the fire occurrence increased from 424.65 million won to 473.06 million won in the past 5 years (2012 ~ 2016). Conclusion: When fire extinguishers are used in the case of passenger Vehicle Fires, the average amount of property damage per fire occurrence is estimated to be about 307.5 million, emphasizing the importance and necessity of the initial fire fighting.

• The Journal of Bigdata
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• v.6 no.1
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• pp.133-144
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• 2021

This paper derives the fire risk of buildings in Seoul through the prediction of property damage and the occurrence of fires. This study differs from prior research in that it utilizes variables that include not only a building's characteristics but also its affiliated administrative area as well as the accessibility of nearby fire-fighting facilities. We use Ensemble Voting techniques to merge different machine learning algorithms to predict property damage and fire occurrence, and to extract feature importance to produce fire risk. Fire risk prediction was made on 300 buildings in Seoul utilizing the established model, and it has been derived that with buildings at Level 1 for fire risks, there were a high number of households occupying the building, and the buildings had many factors that could contribute to increasing the size of the fire, including the lack of nearby fire-fighting facilities as well as the far location of the 119 Safety Center. On the other hand, in the case of Level 5 buildings, the number of buildings and businesses is large, but the 119 Safety Center in charge are located closest to the building, which can properly respond to fire.