• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.617-626
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• 2021

Purpose: The purpose of this study is to evaluate the fire srpead risk of building exterior and roofing materials due to the firebrand of forest fire occurring in the urban areas. Method: In order to achieve this research purpose, by selecting building materials used for exterior and roofing materials of buildings, the time to ignition, total heat release, and heat release rate were investigated, and a forest fire firebrand system was established to the possibility of fire spread was confirmed. Result: As a result of the cone calorimeter test, the roofing material had a similar or faster ignition time due to radiant heat compared to the exterior material with the steel plate exposed to the outside, and showed a higher heat release rate and total heat release than the exterior material. Although it was affected by the flammable material, it was confirmed that it did not spread easily due to the limited amount of combustible material, and carbonization marks appeared inside. Conclusion: The cone calorimeter test method has been shown to be useful in understanding the combustion characteristics of building materials by radiant heat, but the fire spread due to a firebrand in a forest fire is directly affected by the flame due to the ignition of surrounding combustibles, so finding a direct correlation with the cone calorimeter method is difficult. It is judged that the roof material may be more vulnerable to the spread of fire due to the fire than the exterior material.

• Fire Science and Engineering
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• v.24 no.5
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• pp.26-31
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• 2010

In this study, attack process and aerial control line construction type which were considered forest fire type and a case of operations were suggested using the experience of aerial fire attack of all type of forest fires. As the spread rate of forest fire is effected by terrain, slope, wind speed, forest species and etc., we needed to analyze spreading direction, behavior type and intensity before heli-team constructed a aerial control line. Especially, It is important to consider safety of attack team as a their views were obstructed. In this study, we suggested a 13 methods from type A to type M about attack and construction of aerial indirect control line.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.1-12
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• 2014

Crown fire, the main propagation type of large forest fire, has caused extreme damage with the fast spread rate and the high flame intensity. In this paper, we developed the probability equation to predict the crown fires using the spatial features of topography, fuel and weather in damaged area by crown fire. Eighteen variables were collected and then classified by burn severity utilizing geographic information system and remote sensing. Crown fire ratio and logistic regression model were used to select related variables and to estimate the weights for the classes of each variables. As a results, elevation, forest type, elevation relief ratio, folded aspect, plan curvature and solar insolation were related to the crown fire propagation. The crown fire propagation probability equation may can be applied to the priority setting of fuel treatment and suppression resources allocation for forest fire.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.290-302
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• 2023

The aim of this study was to examine the changes in the initial tree growth characteristics of Q. variabilis planted in forest fire-damaged areas treated with soil moisturizers such as biochar and to identify the factors that affect tree growth. To evaluate the effectiveness of soil moisture treatment in the area planted with QV, an experimental plot was created according to the treatment method (spread and mix) and treatment ratio (0, 4, and 40 t/ha). The survival rate of QV was 20% higher in the treatment plot than in the control plot. The height and root collar diameter (RCD)growths of QV were high on the northern slope with spread treatment and on the southern slope with mix treatment. The relative growth rate (RGR) according to the soil moisturizer treatment method was higher in the mix treatment, showing a significant difference in RCD. The northern slope had a higher RGR and significant growth rate. This suggests that the growth improvement effect may depend on the soil moisturizer treatment method. The aspect or treatment method affectsthe drying conditions of the soil, which in turn affects its moisture content or nutrient dynamics. The present research results can be used to establish soil moisturizer treatment standards that are suitable for growth purposes. In addition, this study demonstrates that biochar treatment can be considered as an effective alternative to boost biomass and facilitate early restoration of forest fire-damaged areas.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.1-9
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• 2008

It is necessary to examine relationship between spatial patterns of forest types and characteristics of forest fires for efficient management of fire and forest. By the ecoregions of South Korea, we computed landscape indices for whole types of forests(landscape level) and pine forests(class level), and analyzed characteristics of forest fires using statistics of forest fires from 1991 to 2006. We performed canonical correlation analysis to model the relationship between the landscape indices and the statistics of forest fires. At landscape level, forest patches were larger and more complex in the ecoregions which had higher percentage of forest area. At class level, pine forest patches were more complex and closer to neighbor patches in the coastal ecoregions. The ecoregions including metropolitan areas and cities had more frequent fire occurrences per 1,000ha, while mountainous coastal ecoregions had more burned areas and faster spread of fire growth rate. The canonical correlation between the landscape indices for pine forests and the statistics of forest fires was statistically significant at the 0.05 level and explained more than 70% of the variation in fire variables. The results showed that combustion time per fire was longer in the ecoregions which had larger and more aggregated pine forest patches.

• Fire Science and Engineering
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• v.23 no.6
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• pp.10-15
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• 2009

Flame height calculation in a forest fire is a crucial part of predicting horizontal or vertical flame spread flared by radiation heat transfer. Flame height, which is one of the flame characteristics, can be estimated by the average height of luminous flame. This research relied on flame height observation test on P. densiflora surface fuel bed, which are surface combustibles in a forest, and calorimeter to measure Heat Release Rate, thus produced $H_f=0.027(\dot{Q'})^{2/3}$, flame height calculation equation for surface fuel. The research did not take into consideration such conditions as external velocity, slope and other variables that could affect flame height. According to comparison among experiment results, calculation results of the above formula and those of existing Heskestad formula (1998), it was found that standard error in fallen pine needles between experimental results and calculation results of the above formula amounts to 0.08, whereas standard error in same plant between experimental results and calculation results of existing Heskestad formula amounts to 0.23.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.235-245
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• 2023

Forest fuel moisture content is a crucial factor influencing the combustion rate and fuel consumption during forest fires, significantly impacting the occurrence and spread of wildfires. In this study, meteorological data were gathered using a meteorological measuring device (HOBO data logger) installed in the south and north slopes of Kangwon National University Forest, as well as on bare land outside the forest, from November 1, 2021, to October 31, 2022. The objective was to analyze the relationship between meteorological data and fuel moisture content. Fuel moisture content from the ground cover on the south and north slopes was collected. Fallen leaves on the ground were utilized, with a focus on broad-leaved trees (Prunus serrulata, Quercus dentata, Quercus mongolica, and Castanea crenata) and coniferous trees (Pinus densiflora and Pinus koraiensis), categorized by species. Additionally, correlation analysis with fuel moisture content was conducted using temperature (average, maximum, and minimum), humidity (average, minimum), illuminance (average, maximum, and minimum), and wind speed (average, maximum, and minimum) data collected by meteorological measuring devices in the study area. The results indicated a significant correlation between meteorological factors such as temperature, humidity, illuminance, and wind speed, and the moisture content of fuels. Notably, exceptions were observed for the moisture content of the on the north slope and that of the ground cover of Prunus serrulata and Castanea crenata.

• Convergence Security Journal
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• v.21 no.1
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• pp.191-200
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• 2021

Artificial intelligence technology is developing in an environment where a lot of data is produced due to the development of computing technology, a cloud environment that can store data, and the spread of personal mobile phones. Among these artificial intelligence technologies, the deep neural network provides excellent performance in image recognition and image classification. There have been many studies on image detection for forest fires and fire prevention using such a deep neural network, but studies on detection of cigarette smoking were insufficient. Meanwhile, military units are establishing surveillance systems for various facilities through CCTV, and it is necessary to detect smoking near ammunition stores or non-smoking areas to prevent fires and explosions. In this paper, by reflecting experimentally optimized numerical values such as activation function and learning rate, we did the detection of smoking pictures and non-smoking pictures in two cases. As experimental data, data was constructed by crawling using pictures of smoking and non-smoking published on the Internet, and a machine learning library was used. As a result of the experiment, when the learning rate is 0.004 and the optimization algorithm Adam is used, it can be seen that the accuracy of 93% and F1-score of 94% are obtained.