• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.259-266
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• 2014

Understanding the forest fire patterns is necessary to comprehend the stability of the forest ecosystems. Thus, researchers have suggested the simulation models to mimic the forest fire spread dynamics, which enables us to predict the forest damage in the scenarios that are difficult to be experimentally tested in laboratory scale. However, many of the models have the limitation that many of them did not consider the complicated environmental factors, such as fuel types, wind, and moisture. In this study, we suggested a simple model with the factors, especially, the geomorphological structure of the forest and two types of fuel. The two fuels correspond to susceptible tree and resistant tree with different probabilities of transferring fire. The trees were randomly distributed in simulation space at densities ranging from 0.5 (low) to 1.0 (high). The susceptible tree had higher value of the probability than the resistant tree. Based on the number of burnt trees, we then carried out the sensitivity analysis to quantify how the forest fire patterns are affected by the structure and tree density. We believe that our model can be a useful tool to explore forest fire spreading patterns.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.481-487
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• 2005

In this study, a GIS model to simulate the behavior of surface forest fires was developed on the basis of forest fire growth prediction algorithm. This model consists of three modules for data-handling, simulation and report writing. The data-handling module was designed to interpret such forest fire environment factors as terrain, fuel and weather and provide sets of data required in analyzing fire behavior. The simulation module simulates the fire and determines spread velocity, fire intensity and burnt area over time associated with terrain slope, wind, effective humidity and such fuel condition factors as fuel depth, fuel loading and moisture content for fire extinction. The module is equipped with the functions to infer the fuel condition factors from the information extracted from digital vegetation map sand the fuel moisture from the weather conditions including effective humidity, maximum temperature, precipitation and hourly irradiation. The report writer has the function to provide results of a series of analyses for fire prediction. A performance test of the model with the 2002 Chungyang forest fire showed the predictive accuracy of 61% in spread rate.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.1
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• pp.30-35
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• 2003

The study of the scars formed on the bark of pine trees damaged by forest fire was carried out in the burned area of Samchuk and Donghae in 2000. Fire scars were formed on the bark of trees when fire passed by the tree. Fire scarring is usually found on the windward and leeward sides of the tree. Fire spread was analyzed topographically using the fire scars formed at the tree stem. Fire spread was closely related to the shape, slope and direction of the forestland. Four fire direction types are classified according to the shapes of the forestland. The height of the fire scar was higher on the leeward side than on the windward side of the trees studied. The burnt area of the total bark of the tree was over 30% in dead trees and below 12% in living trees. The regression model of the burnt stem area using the height of the fire scar, the diameter of breast height and the height of tree was Y=-2.484${\times}$Height＋0.04199${\times}$D.B.H-1.686${\times}$Windward＋11.172${\times}$Leeward＋23.432(r=0.936, F=409.968, P＞0.0001).

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.267-270
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• 2006

본 논문은 국산 고해상도 위성화상의 활용 일환으로 산불피해림의 정밀정성정보를 제공하기 위한 낙엽송 및 리기다 소나무의 산불피해등급 육안판독열쇠에 관한 연구이다. 본 육안 판독열쇠는 낙엽송과 리기다 소나무의 산불피해등급 판별을 위해 4가지 요소, 즉 색, 형태, 구조 그리고 질감에 기초로 개발하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.221-232
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• 2011

Applicability of three soil erosion models for burnt hillslopes was evaluated. The models were estimated with the data from plots established after tremendous wildfire occurred in the east coastal region. Soil erosion and surface runoff were simulated by the Water Erosion Prediction Project (WEPP) and the Revised Universal Soil Loss Equation (RUSLE) of application mode for disturbed forest areas and the Soil Erosion Model for Mountain Areas (SEMMA) developed for burnt hillslopes. Simulated sediment yield and surface runoff were compared with the measured those. In maximum value of sediment yield, three models was under-predicted and RUSLE and WEPP had difference of over two times. SEMMA showed the best model response coefficient, determination coefficient and the model efficiency. In application of models to the soil erosion according to the elapsed year after wildfire, all models were underestimated in initial stage disturbed by wildfire. Evaluation of models in this burnt hillslopes was shown the tends to under-predict soil erosion for larger measured values. Although a lot of sediment can be generated in small rainfall event as fine-grained soil of the high water repellency was exposed excessively right after wildfire, this under-prediction was shown that those models have a limit to estimate the weighted factors by wildfire.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.175-175
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• 2023

Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.178-185
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• 2013

Forest fires are expected to increase in severity and frequency under global climate change and thus better understanding of fire dynamics is critical for mitigation and adaptation. Researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed various simulation models to reproduce forest fire spread dynamics. However, these models have limitations in the fire spreading because of the complicated factors such as fuel types, wind, and moisture. In this study, we suggested a simple model considering the wind effect and two different fuel types. The two fuels correspond to susceptible tree and resistant tree with different probabilities of transferring fire. The trees were randomly distributed in simulation space with a density ranging from 0.0 (low) to 1.0 (high). The susceptible tree had higher value of the probability than the resistant tree. Based on the number of burnt trees, we then carried out the sensitivity analysis to quantify how the forest fire patterns are affected by wind and tree density. The statistical analysis showed that the total tree density had greatest effect on the forest fire spreading and wind had the next greatest effect. The density of the susceptible tree was relatively lower factor affecting the forest fire. We believe that our model can be a useful tool to explore forest fire spreading patterns.

• Fire Science and Engineering
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• v.23 no.4
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• pp.32-39
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• 2009

In this study, 18 plots were selected for particular investigation on Gangneung area and Samcheok area and Uljin area, where forest fire was occurred after thinning in 2007. After selection, a relationship between a damage of forest fire and thinning were compared and analyzed. Many factor such as a damaged species, a thinning or non-thinning, a direction of forest fire head, DBH, a height of tree, a mortality of tree, a leeward scorching ratio, a crown damage ratio, a forest tree standing crop density, a crown base height, a leaving of thinning slash, a location of plot (GPS), elevation, an aspect of slope, an angle of slope, and a topography were measured. Therefore, we analyzed a relationship with forest fire. In the result of this analysis, it was founded that the leeward scorching ratio was 24.7% on thinning area whereas 60.2% on non-thinning area. Subsequently, leeward scorching ratio on thinning area was increased by about 35.5% more than on non-thinning area. In the result of analysis about tree species, a forest of pine tree was more damaged than forest of oak tree. The mortality of tree was increased by about 41.4% on non-thinning area. When stands were close to thinning slashes, these were more damaged by 10${\sim}$20% than other stands for increasing of amount of a combustion material. Especially, as potential of re-ignition increased for more cumulated thinning slash, it will be more important to require a method for a periodical removing or practical utilization of slash.

• Journal of Korea Water Resources Association
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• v.38 no.1
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• pp.59-71
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• 2005

Mountain watersheds are a lot of problems about soil erosion because of frequent wildfire occurrence. Runoff and soil erosion caused by the rain on a hillslope after wildfire are dependent on cover factor. And these has been a decrease by the cover factor recovery following time passage. The present paper defines the dynamic sensitivity of runoff and soil erosion that is the rate of runoff volume and soil erosion weight to rainfall energy and analyzes characteristics of the sensitivity for variation of cover factor, In according to the correlation analysis between other parameters and sensitivities, the sensitivity is the most dependent on the cover factor and the relation is exponential. The sensitivities after wildfire have suitable relation with treatment method for the mitigation of burnt forest and wildfire intensity. It was confirmed that the variation of soil erosion sensitivities come upon the range of stability in 5 years after wildfire.

• Journal of the Korea Organic Resources Recycling Association
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• v.13 no.2
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• pp.85-90
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• 2005

Changes of biochemical and genetic diversity of microbial communities in the soil damaged by a forest fire were analyzed. Soil samples were collected from Gangnung area where a forest fire was broken out in 2000. Two soil samples were from the burnt area, one from the naturally restoring soil (NS) and the other from the artificially restoring soil (AS). A normal, unaffected soil sample (US) was also included as a control. For the biochemical diversity, each sample was directly applied to the BIOLOG system, and the cluster analysis through a statistic process (SPSS) were performed. Genetic diversity was analyzed through DGGE using 16S-rDNA amplified from soil DNA. Among the samples tested, top soils of US and NS, and sub soil of NS revealed more than 70% of the similarity value in biochemical diversity. In case of genetic diversity, however, the similarity value was found to be in the range of 53% to 68% in all samples. This result indicates that the biochemical diversity is not always correlated with the genetic diversity in the analysis of microbial communities.