• Journal of Korean Society of Forest Science
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• v.97 no.4
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• pp.392-397
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• 2008

To characterize the root strength changes of Pinus densiflora by elapsed years after forest fire, we measured and analyzed the tensile force and strength of the roots using the universal testing machine for 4 years. The deterioration rate of the root strength was higher in small diameter class than that in large diameter class. Especially, the deterioration was highest of the root strength at the second year in all surveyed diameter classes and the mean deterioration rate of the root strength was 61% by that time. The tensile strength based on the simulation by ordinary differential equations deteriorated more than 50% in all diameter classes within 2 years after forest fire.

• Journal of Environmental Science International
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• v.29 no.9
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• pp.915-924
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• 2020

The purpose of this study was to conduct a forest healing program for victims affected by the large forest fires of 2017 in Gangneung and to investigate its effects on the stress and physical health promotion of the victims. From January to March 2019, three forest therapy programs were conducted on 49 residents of four villages that suffered forest fires in the National Center for Forest Therapy, Daegwallyeong. The results showed that the degree of stress of forest fire victims decreased significantly by means of these programs. Furthermore, autonomic nerve activity, stress resistance, stress index, and fatigue decreased significantly and average heart rate and heart stability also improved.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.305-306
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• 2006

To avoid the large scale of damage when fire occurs in the tunnel, it is necessary to have a system to minimize the damage, and early discovery of the problem. In this paper, we have proposed algorithm using the image processing, which is the high-speed detection for the occurrence of fire or smoke in the tunnel. The fire detection is different to the forest fire detection as there are elements such as car and tunnel lightings and other variety of elements different from the forest environment. Therefore, an indigenous algorithm should be developed.The two algorithms proposed in this paper, are able to complement with each other and also they can detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout this experiment, we have proved the propriety of algorithm.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.219-220
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• 2007

In this paper, we proposed image processing technique for automatic real time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurred in the tunnel, it is necessary to have a system to minimize and to discover the incident as fast as possible. The fire and smoke detection is different from the forest fire detection as there are elements such as car and tunnel lights and others that are different from the forest environment so that an indigenous algorithm has to be developed. The two algorithms proposed in this paper, are able to detect the exact position, at the earlier stage of incident.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1031-1034
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• 2005

This paper introduces a novel sensor network protocol, R-WSLP(Realtime Wireless Sensor Line Protocol), which has extremely low latency characteristic in large-scale WSN. R-WSLP is proposed to implement realtime forest fire monitoring system. We propose Distributed TDMA method for the multiple channel access and Time Synchronized Forwarding Mechanism instead of routing technique to achieve low latency network. Also, R-WSLP provides extremely low power operation which we accomplished by reducing idle listening. In our experimentation, we get successful results at the forest fire monitoring system with our protocol.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1107-1115
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• 2019

Satellite data play a major role in supporting knowledge about forest fire by delivering rapid information to map areas damaged. This study, we used 7 Sentinel-2A images to detect change area in forests of Sokcho on April 4, 2019. The process of classify forest fire severity used 7 levels from Sentinel-2A dNBR(differenced Normalized Burn Ratio). In the process of classifying forest fire damage areas, the study selected three areas with high regrowth of vegetation level and conducted a detailed spatial analysis of the areas concerned. The results of dNBR analysis, regrowth of coniferous forest was greater than broad-leaf forest, but NDVI showed the lowest level of vegetation. This is the error of dNBR classification of dNBR. The results of dNBR time series, an area of forest fire damage decreased to a large extent between April 20th and May 3rd. This is an example of the regrowth by developing rare-plants and recovering broad-leaf plants vegetation. The results showed that change area was detected through the change detection of danage area by forest category and the classification errors of the coniferous forest were reached through the comparison of NDVI and dNBR. Therefore, the need to improve the precision Korean forest fire damage rating table accompanied by field investigations was suggested during the image classification process through dNBR.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.6
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• pp.160-168
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• 2003

In Korea, a large portion of aerial power-transmission cables is installed in the mountains. In the case of a fire in the mountains, steel wires coated with zinc and aluminum wires of those power cables exposed to the fire or near around will be deteriorated by the blaze and the high temperature. Deterioration proceeds by interactions of a variety of factors like quality, manufacturing process, the condition of installation and exposure environment of a wire, and so on. Generally, the characteristic of a conductor affect by a forest fire can not be analyzed without the effect through simulating a forest fire. However, there are little research accomplishments of that kind of simulation about it, and there's been no analysis of a sample exposed to an actual forest fire. This thesis shows the experimental results that apply to a new wire by an artificial flame-maker because it's difficult to directly analyze the characteristic of deterioration by a forest fire. Those results include the intensity of extension and wrench for a conductor. In addition, there's been an experiment and analysis about the mechanical characteristics of the wire of ACSR 480[$\textrm{mm}^2$] which was removed from Pohang area by a forest fire. Then, the database will be made to predict the state of deteriorated wires by a forest fire using those two data, and data necessary to diagnose the life state of an ACSR wire affected by a forest fire will be given.

• Korean journal of applied entomology
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• v.52 no.3
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• pp.205-213
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• 2013

Forest fires disturb communities of forest-dwelling insects by killing or dispersal. Species diversity, species composition, and functional guilds of ant communities will be changed following forest fires. A survey of ants was conducted to find changes in ant communities after a large fire occurred in Goseong within Gwangwon province in South Korea in 1996. In total, 1,308 ants representing 16 species were collected; 696 ants representing 15 species were collected at the burned site, and 612 ants representing 13 species were collected at the unburned site. Contrary to the general expectation which predicts a decrease of diversity and abundance after fire, abundance, species diversity, species composition, and functional guilds of ant communities did not differ between the burned site and the unburned site. Furthermore, estimated species richness was significantly higher at the burned site than at the unburned site. However, monthly occurrences of ants (abundant species and pooled) were different between the burned site and the unburned site. Ants were more abundant at the burned sites than the unburned site just after the fire (May 1996). However, they were more abundant at the unburned site than the burned site in autumn (September and October 1996). This phenomenon might be caused by environmental change (e.g., decrease of soil moisture). In conclusion, the fire did not significantly change ant fauna, as fire in spring cannot destroy ant colonies that are wintering in deep soils.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.501-514
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• 2023

Forest fires can generate numerous pollutants through the combustion of vegetation and cause serious environmental problems. The global warming and climate change will increase the frequency and scale of forest fires across the world. In Korea, many nuclear power plants (NPPs) are located in the East Coast where large-scale forest fires frequently occur. Therefore, understanding the sorption and transport characteristics of radionuclides in the forest fire areas is required against the severe accidents in NPPs. This article reviewed the physiochemical changes and contamination of groundwater and soil environments after forest fires, and discussed sorption and transport of radionuclides in the subsurface environment of burned forest area. We considered the geochemical factors of subsurface environment changed by forest fire. Moreover, we highlighted the need for studies on changes and contamination of subsurface environments caused by forest fires to understand more specific mechanisms.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.