• Fire Science and Engineering
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• v.27 no.2
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• pp.54-61
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• 2013

Aerial fire fighting is more effective on forest fire suppression than ground fire fighting. So, Aerial fire fighting is important to prevent large fire. United States suppression the joint fixed-wing and rotorcraft (Helicopter) but Helicopter only in Korea. At this point, we need to research about ground water drop pattern and coverage level for aerial fire fighting effectiveness by helicopter. In this study, we experimented water-dropping S-64E, Ka-32T, AS-350B2 of three of helicopter to operate the Forest Service and suggested efficient ground water drop pattern and coverage level. Using these study results, recognition of pilots who suppression more efficient aerial fire fighting at the scene of Forest fire.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.137-138
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• 2012

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.669-683
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• 2022

The frequency and damage of forest fires have tended to increase over the past 20 years. In order to effectively respond to forest fires, information on forest fire damage should be well managed. However, information on the extent of forest fire damage is not well managed. This study attempted to present a method that extracting information on the area of forest fire in real time and quasi-real-time using visible infrared imaging radiometer suite (VIIRS) images. VIIRS data observing the Korean Peninsula were obtained and visualized at the time of the East Coast forest fire in March 2022. VIIRS images were classified without supervision using iterative self-organizing data analysis (ISODATA) algorithm. The results were reclassified using the relationship between the burned area and the location of the flame to extract the extent of forest fire. The final results were compared with verification and comparison data. As a result of the comparison, in the case of large forest fires, it was found that classifying and extracting VIIRS images was more accurate than estimating them through forest fire occurrence data. This method can be used to create spatial data for forest fire management. Furthermore, if this research method is automated, it is expected that daily forest fire damage monitoring based on VIIRS will be possible.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.120-124
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• 2012

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1273-1283
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• 2022

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.3
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• pp.41-50
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• 2001

Recently our nature of environment has destroyed by a large scaled forest fire. In order to manage these forest fires, forecasting of it is considered as the most important thing. In this paper the database related to forest fire was first built and the efficient forest fire information management system was implemented by using GIS. The main goal of this system is that forest fire managers have GUI(graphic user interface) to analyze data of forest fire effectively and update and retrieve information in database. For the efficient GUI, this system is built in Visual Basic 6.0 and Map Object 2.0. Map Object 2.0 is combined to have various and powerful functionality of GIS analysis as component ware. The Oracle 8.0 is used as DBMS in this study to manage all the spatial and attributed information in database effectively. In the future, this system will play a critical role as making a decision supporting system for scientific forest fire protection and help real time forest fire hazard information offers service for public welfare administration business management.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.785-798
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• 2023

Recently, forest fires have become frequent due to climate change, and the size of forest fires is also increasing. Forest fires in Korea continue to cause more than 100 ha of forest fire damage every year. It was found that 90% of the large-scale wildfires that occurred in Gangwon-do over the past five years were concentrated in the east coast area. The east coast area has a climate vulnerable to forest fires such as dry air and intermediate wind, and forest conditions of coniferous forests. In this regard, studies related to various forest fire analysis, such as predicting the risk of forest fires and calculating the risk of forest fires, are being promoted. There are many studies related to risk analysis for forest areas in consideration of weather and forest-related factors, but studies that have conducted risk analysis for forest-friendly areas are still insufficient. Management of forest adjacent areas is important for the protection of human life and property. Forest-adjacent houses and facilities are greatly threatened by forest fires. Therefore, in this study, a grid-based forest fire-related disaster risk map was created using factors affected by forest-neighboring areas using national branch numbers, and differences in risk ratings were compared for forest areas and areas adjacent to forests based on Gangneung forest fire cases.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.123-127
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• 2020

In order to obtain the overall fire line information of medium and large forest fires at night, the ground control system was developed to determine whether forest fires occurred through real-time video clips and to calculate the location of the forest fires determined using the location of drones, angle information of video cameras, and altitude information on the map to reduce the time required for regular video matches obtained after the completion of the mission. To verify the reliability of the developed function, the error distance of the aiming position information of the flight altitude star and the image camera was measured, and the location information within the reliable range was displayed on the map. As the function developed in this paper allows real-time identification of multiple locations of forest fires, it is expected that overall fire line information for the establishment of forest fire extinguishing measures will be obtained more quickly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.209-217
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• 2021

Although forest fires are more often triggered by artificial causes than by natural causes, the combustion conditions that spread forest fire damage over a large area are affected by natural phenomena. Therefore, using partial least squares structural equation modeling (PLS-SEM), which can analyze the dependent and causal relationships between various factors, this study evaluated the causal relationships and relative influences between forest fire, weather, and drought, taking Gangwon Province as our sample region. The results indicated that the impact of drought on forest fires was 27 % and that of the weather was 38 %. In addition, forest fires in spring accounted for about 60 % of total forest fires. This indicatesthat along with meteorological factors, the autumn and winter droughts in the previous year affected forest fires. In assessing the risk of forest fires, if severe meteorological droughts occur in autumn and winter, the probability of forest fires may increase in the spring of the following year.