• 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

• Applied Chemistry for Engineering
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• v.22 no.6
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• pp.636-641
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• 2011

Since the mid-1990s, the number of fires continue to increase and the size has been also larger. However, the pyrolysis and combustion characteristics of the various species of the medium such as fallen leaves, herbaceous plants, conifers and broadleaf trees have scarcely been studied. In this paper, we investigate the pyrolysis and combustion of the typical domestic needle-leaf tree of Pinus densiflora and thinning-out tree by thermogravimetric analysis (TGA). Pinus densiflora was ignited at $200^{\circ}C$ and pyrolysis from $230^{\circ}C$. In case of thinning-out tree was ignited and pyrolysis at $180^{\circ}C$ and $205^{\circ}C$, respectively. The values of activation energy for pyrolysis were increased as the conversion efficiency increasing from 10% to 80%, whereas the values was decreased during combustion.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.3
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• pp.15-24
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• 2022

In 2000, a total of 23,794ha of forest was lost due to the East Coast forest fire, and about 70% of the damaged area was concentrated in Samcheok. In 2001, artificial restoration and natural restoration were implemented in the damaged area. This study was conducted to understand the current vegetation structure 21 years after the restoration of forest fire damage in the Samcheok, Gumbong Mountain area. As a result of classifying the vegetation community, it was divided into three communities: Quercus variabilis-Pinus densiflora community, Pinus densiflora-Quercus mongolica community, and Pinus thunbergii community. Quercus variabilis, Pinus densiflora, and Pinus thunbergii planted in the artificial restoration site were found to continue to grow as dominant species in the local vegetation after restoration. As for the species diversity index of the community, the Quercus variabilis-Pinus densiflora community dominated by deciduous broad-leaf trees showed the highest, and the coniferous forest Pinus thunbergii community showed the lowest. Vegetation in areas affected by forest fires is greatly affected by reforestation tree species, and 21 years later, it has shown a tendency to recover to the forest type before forest fire. In order to establish DataBase for effective restoration and to prepare monitoring data, it is necessary to construct data through continuous vegetation survey on the areas affected by forest fires.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.1
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• pp.17-24
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• 2008

This study was performed to estimate non-$CO_2$ greenhouse gases (i.e., GHGs) emission from biomass burning at a local scale. Estimation of non-$CO_2$ GHGs emission was conducted using Landsat TM satellite imagery in order to assess the damage degree in burnt area and its effect on non-$CO_2$ GHGs emission. This approach of estimation was based on the protocol of the 2003 IPCC Guidelines. In this study, we used one of the most severe fire cases occurred Samcheock in April, 2004. Landsat TM satellite imageries of pre- and post-fire were used 1) to calculate delta normalized burn ratio (dNBR) for analyzing burnt area and burn severity of the Samcheok large-fire and 2) to quantify non-$CO_2$ GHGs emission from different size of the burnt area and the damage degree. The analysis of dNBR of the Samcheok large-fire indicated that the total burnt area was 16,200ha and the size of the burnt area differed with the burn severity: out of the total burnt area, the burn severities of Low (dNBR < 152), Moderate (dNBR = 153-190), and High (dNBR = 191-255) were 35%, 33%, and 32%, respectively. It was estimated that the burnt areas of coniferous forest, deciduous forest, and mixed forest were about 11,506ha (77%), 453ha (3%), and 2,978ha (20%), respectively. The magnitude of non-$CO_2$ GHGs emissions from the Samcheok large-fire differed significantly, showing 93% of CO (44.100Gg), 6.4% of CH4 (3.053Gg), 0.5% of $NO_x$ (0.238Gg), and 0.1% of $N_2O$ (0.038Gg). Although there were little changes in the total burnt area by the burn severity, there were differences in the emission of non-$CO_2$ GHGs with the degree of the burn severity. The maximum emission of non-$CO_2$ GHGs occurred in moderate burn severity, indicating 47% of the total emission.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.168-187
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• 2006

Windy meteorological conditions and dried fire fuels due to higher atmospheric instability and dryness in the lower troposphere can exacerbate fire controls and result in more losses of forest resources and residential properties due to enhanced large wildland fires. Long-term (1979-2005) climatology of the Haines Index reconstructed in this study reveals that spatial patterns and intra-annual variability of the atmospheric instability and dryness in the lower troposphere affect the frequency of wildland fire incidences over the Korean Peninsula. Exponential regression models verify that daily high Haines Index and its monthly frequency has statistically significant correlations with the frequency of the wildland fire occurrences during the fire season (December-April) in South Korea. According to the climatic maps of the Haines Index created by the Geographic Information System (GIS) using the Digital Elevation Model (DEM), the lowlands below 500m from the mean sea level in the northwestern regions of the Korean Peninsula demonstrates the high frequency of the Haines Index equal to or greater than five in April and May. The annual frequency of the high Haines Index represents an increasing trend across the Korean Peninsula since the mid-1990s, particularly in Gyeongsangbuk-do and along the eastern coastal areas. The composite of synoptic weather maps at 500hPa for extreme events, in which the high Haines Index lasted for several days consecutively, illustrates that the cold low pressure system developed around the Sea of Okhotsk in the extreme event period enhances the pressure gradient and westerly wind speed over the Korean Peninsula. These results demonstrate the need for further consideration of the spatial-temporal characteristics of vertical atmospheric components, such as atmospheric instability and dryness, in the current Korean fire prediction system.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.338-347
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• 2007

The purpose of this study was to analyze a ripple effect of the regions, Samcheok city, Goseong county and Donghae city, in Gangwon province by government aid for forest fire restoration through the input-output analysis. These regions were devastated by forest fire in 2000. Direct production inducement effect was higher than indirect production inducement effect except for construction industry. Income inducement effect similarly showed production inducement effect Indirect employment inducement effect was higher than direct employment inducement effect. The efficiency of government aid took a side view of three effects. Production inducement effect and income inducement effect in Donghae were more efficient than these in Samcheok and Goseong. Employment inducement effect in Samcheok was more efficient than it in Goseong and Donghae.

• Journal of The Korean Society of Grassland and Forage Science
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• v.28 no.3
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• pp.245-250
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• 2008

On April 4 to 6, 2005, there was a huge fire in Yangyang-gun, Kangwon-do, Korea, which burned over 250ha of forests and 246 buildings including 160 houses. The effects of reseeding rate and timing on productivity and nutritive value of forages in the forest fire burnt pasture in this study were investigated. The effect of reseeding could not be seen in the burnt pastures in terms of forage productivity and quality in short term but there was a long-term effect particularly with higher reseeding rates at later days after the fire on forage botanical composition. We concluded that forest fire brought reduction in pasture forage yield for a short period but it did not make a significant effect for a long term.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.87-97
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• 2023

In this study, we examined the effects of a large wildfire in the coastal area of Uljin-gun. The analysis of water quality and the dominant species, species composition, and community structure of marine algal was conducted quarterly in 2022 at Nagok (F-1), Hujeong (F-2), Bongpyeong (F-3), and Gongse Port (F-C) in Uljin-gun. As a result of water quality analysis, the pH, a factor of wildfire impact was 8.07~8.30 and 8.12~8.48 in surface and bottom layers, respectively, which are normal values in coastal waters of the East Sea, suggesting no direct impact from wildfires. By marine algal species composition, the coastal areas show the following order: Rhodophyta (58.1%) > Ochrophyta (25.8%) > Chlorophyta (14.5%) > Magnoliophyta (1.6%). By season, Undaria pinnatifida was the most dominant at Nagok and Hujeong in March and June, which in September and November, Gelidium elegans and Lithophyllum sp. were the most dominant in Bongpyeong and Gongse Port, respectively. In the cluster analysis, the stations were divided into two groups according to presence and absence of specific marine algal by season. The dominant species were U. pinnatifida, G. elegans and D. divaricata in group A, and Lithophyllum sp. was mainly present in group B. Thus, the species composition and group structure reflected the normal seasonal change pattern with water temperature variation and showed little significant difference from the control site, suggesting no direct effects of the wildfire on algae distribution in Uljin.

• The Korean Journal of Soil Zoology
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• v.5 no.2
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• pp.47-62
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• 2000

This study investigated the effect of soil animals at forest fire area, and it carried out the mountain located at Jundae Ri, Houeng-chen Myen, Ha-dong Gun, Kyoung-Nam Province, southern part of Korea, where burned out about 50 hectars on April 11, 1997. Vegetation of the examined area absolutely dominated with the pines of 7-14 cm in diameter and 20 to 30 years old and the rest were covered with mixed forest with a shrub such as the oak (Quereus mongolia Fisch, Quereus variabilis BI, Quereus dentana Thunb), snowbell(Styrax japonica, S, et, z), lacquer tree (Rhus trichocarpa Mig), azalea (Rhododendron mucronulatum Turcz), etc. And there were simple area organized as a herbaceous plant, and the burnt area was poor experimental sites, where litter layer and herbaceous plant disappeard due to fire, and the unburnt area was rich in surface plant, dead leaves, twigs, etc. But the ground cover vegetations were poor in the unburnt area. The distribution of each animal groups, the seasonal fluctuation in population density, the biomass of meso$.$macroarthropods and the relationship between soil animal and some environmental factors were investigated and analyzed at each experimental area. The result are summarized as follow: 1. Identificated 257,087 individuals of soil microarthropods were classified into 7 classes and 24 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta., and identified 8,006 individuals of the total meso$.$macroarthropods were classified into 7 classes and 20 orders of Arachinida, Insecta, Chilopoda, Symphyla, Diplopoda, Isopoda and Oligochaeta. 2. Among the total soil microarthropods, Arachinida formed 70.9%, followed by Insecta for 28.4% and among the total meso$.$macroarthropod , Insecta formed 57.6%, followed by Chilopoda for 23.8%.