• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.242-249
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• 2004

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for the practical purpose of forecasting forest fire danger. Forest fire in South Korea is highly influenced by humidity, wind speed, and temperature. To effectively forecast forest fire occurrence, we need to develop a forest fire danger rating model using weather factors associated with forest fire. Forest fore occurrence patterns were investigated statistically to develop a forest fire danger rating index using time series weather data sets collected from 8 meteorological observation centers. The data sets were for 5 years from 1997 through 2001. Development of the forest fire occurrence probability model used a logistic regression function with forest fire occurrence data and meteorological variables. An eight-province probability model by was developed. The meteorological variables that emerged as affective to forest fire occurrence are effective humidity, wind speed, and temperature. A forest fire occurrence danger rating index of through 10 was developed as a function of daily weather index (DWI).

• Fire Science and Engineering
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• v.28 no.2
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• pp.82-90
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• 2014

According to recent government's 3.0 operating paradigm for the opening and sharing of public information, relationship between humidity, temperature and fire occurrence were analyzed using the data in National Weather Service and National Emergency Management Agency. In order to analyze the relationships between humidity, temperature and fire occurrence, hourly frequency of fire occurrence compared with humidity and temperature ranges was suggested as an analysis method. Tendencies of fire occurrence frequencies were examined through this and characteristics of detailed attributes could be statistically identified. Results about hourly frequencies of fire occurrence by classifying the humidity ranges in each region showed increasing frequencies in all areas where the humidity is lower. Hourly frequencies of fire occurrence according to temperature ranges were identified to be similar in each area as well. In addition, characteristics of objects' attributes were analyzed including types of fire, igniting source of fire, initial complex, reasons of fire occurrence, and distinctive directions were suggested. Suggested method in this paper could be practically used when suggesting the frequency in each category in fire occurrence statistics of National Fire Information System.

• Atmosphere
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• v.20 no.1
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• pp.27-35
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• 2010

This study analyzes the climate change in Korea and its impact on the occurrence of forest fire events. The forest fire occurrences in Korea tend to concentrate around large cities. In addition, the spatial distribution of the forest fire occurrence seems to agree with local climate conditions. Though the occurrence of the forest fire shows strong interannual variation, it also exhibits a positive trend. Because the forest fire frequently occurs during early spring, we examined long term climate variability in Korea for the early spring seasons. The climate change in Korea generally has brought warmer, drier, and less precipitable conditions during the early spring. The changes of the atmospheric conditions provide favorable condition for the forest fire. The climate changes in Korea also depict distinct spatial variability according to the atmospheric variables. We compared the regional trend of the fire occurrence with the climate trends. The results show the sharpest growing in the forest fire occurrence over southwest of Korea. This study suggests that the decrease in the precipitation day might affect the sharp increasement of the forest fire occurrence in the southwest of Korea.

• 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.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.166-168
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• 2009

In this paper, we studied fire sensing and position tracing system in fire region. The coordinates of fire position is communicated to fire suppression system immediately. And the fire is suppressed by this system effectively. For the purpose, the fire occurrence region images are extracted with two different CCD surveillance cameras and fire occurrence are sensed, I suggested a method to measure the fire occurrence position. It was able to be sensed early experiment result fire outbreak and, I was able to understand a fire outbreak position coordinate at the moment when a fire occurred and, I confirmed that I could accomplish warning official announcement and fire suppression in an auto.

• Journal of Korean Society of Forest Science
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• v.95 no.2
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• pp.160-167
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• 2006

Most of the forest fires that occur in South Korea are caused by human. We partitioned South Korea into nine districts and used observed weather data and daily fire occurrence records for the 1994 to 2003 period to develop a human-caused fire occurrence model of South Korea. Logistic regression analysis techniques were used to relate the probability of a fire day to Fine Fuel Moisture Code (FFMC) component of the Canadian Forest Fire Danger Rating System. The probability of the number of fire day was increased as FFMC increased in the nine districts of South Korea.

• 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.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.101-112
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• 2018

A lot of manpower and budgets are being used to prevent fires, and only a small portion of the data generated during this process is used for disaster prevention activities. This study develops a prediction model of fire occurrence probability based on data mining in order to more actively use these data for disaster prevention activities. For this purpose, variables for predicting fire occurrence probability of various buildings were selected and data of construction administrative system, national fire information system, and Korea Fire Insurance Association were collected and integrated data set was constructed. After appropriate data cleansing and preprocessing, various data mining methodologies such as artificial neural network, decision trees, SVM, and Naive Bayesian were used to develop a prediction model of the fire occurrence probability of buildings. The most accurate model among the derived models is Linear SVM model which shows 68.42% as experimental data and 63.54% as verification data and it is the best model to predict fire occurrence probability of buildings. As this study develops the prediction model which uses only the set values of the specific ranges, future studies may explore more opportunites to use various setting values not shown in this study.

• Journal of Korean Society of Forest Science
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• v.85 no.1
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• pp.15-23
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• 1996

Preparing the era of forest resources management requires studies on forest fire. This study attempted to develop forest fire occurrence model using meteorological characteristics for the practical purposes of forecasting forest fire danger rate. To accomplish this goal, the relationships between forest fire occurrence and meteorological characteristics are estimated. In the process, the forest fire occurrence pattern of the study region(Taegu-Kyungpook) is categorized by employing qualification IV method. The study region was divided into three areas such as, Taegu, Andong and Pohang area. The meteorological variables emerged as affective to forest fire occurrence are relative humidity, longitude of sunshine, and duration of precipitation. To estimate the probability of forest fire danger, forest fire occurrence of three areas are regressed on the time series data of affective meteorological variables using logistic and probit model. The effectiveness of the models estimated are tested and showed acceptable degree of goodness. Those models developed would be helpful to increase the efficiency of forest fire management such as detection of forest fire occurrence and effective disposition of forest fire fight equipments.