• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.367-374
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• 2005

Recently, forest damage has occurred often and made big issues. Among them, the damage by forest fire is not only damage of itself but also being connected with secondary damage like a flood. This is the fact that a forest fire is caused rather artificially by people than nature. In this study, we try to investigate damage of a forest fire through spectral reflectance of a plant community surveyed using a near infrared CCD camera and a SPM (Spectral Radiometer) as advanced work to use satellite image data. That is, damage of a forest fire by the naked eye observation was divided into the No damage, the light damage, the serious damage and we estimated activity of forest and grasped revival possibility of forest. Through correlation analysis between the spectral reflectance by SPM and the near infrared CCD camera, we could get high correlation in the No damage and light damage. Therefore, when we surveyed damage of a forest fire, we could grasp damage, that is hardly observed by the naked eye by, using jointly the spectral radiometer and the near infrared CCD camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.351-357
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• 2019

UAV (Unmanned Aerial Vehicle) images can be exploited for rapid forest fire damage assessment by virtue of UAV systems' advantages. In 2019, catastrophic forest fire occurred in Goseong and Sokcho, Korea and burned 1,757 hectares of forests. We visited the town in Goseong where suffered the most severe damage and conducted UAV flights for forest fire damage assessment. In this study, economic and rapid damage assessment method for forest fire has been proposed using UAV systems equipped with only a RGB sensor. First, forest masking was performed using automatic elevation thresholding to extract forest area. Then ExG (Excess Green) vegetation index which can be calculated without near-infrared band was adopted to extract damaged forests. In addition, entropy filtering was applied to ExG for better differentiation between damaged and non-damaged forest. We could confirm that the proposed forest masking can screen out non-forest land covers such as bare soil, agriculture lands, and artificial objects. In addition, entropy filtering enhanced the ExG homogeneity difference between damaged and non-damaged forests. The automatically detected damaged forests of the proposed method showed high accuracy of 87%.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.43-57
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• 2022

This study aims to classify forest fire-affected areas, identify forest types by the intensity of forest fire damage using multi-time Landsat-satellite images before and after forest fires and to analyze the effects of artificial restoration sites and natural restoration sites. The difference in the values of the Normalized Burned Ratio(NBR) before and after forest fire damage not only maximized the identification of forest fire affected and unaffected areas, but also quantified the intensity of forest fire damage. The index was also used to confirm that the higher the intensity of forest fire damage in all forest fire-affected areas, the higher the proportion of coniferous forests, relatively. Monitoring was conducted after forest fires through Normalized Difference Vegetation Index(NDVI), an index suitable for the analysis of effects by restoration type and the NDVI values for artificial restoration sites were found to no longer be higher after recovering the average NDVI prior to the forest fire. On the other hand, the natural restoration site witnessed that the average NDVI value gradually became higher than before the forest fires. The study result confirms the natural resilience of forests and these results can serve as a basis for decision-making for future restoration plans for the forest fire affected areas. Further analysis with various conditions is required to improve accuracy and utilization for the policies, in particular, spatial analysis through forest maps as well as review through site checks before and immediately after forest fires. More precise analysis on the effects of restoration will be available based on a long term monitoring.

• Journal of Integrative Natural Science
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• v.13 no.1
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• pp.34-40
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• 2020

This study aims to create a model for predicting the number of extinguishment manpower to put out forest fires by taking into account the climate, the situation, and the extent of the damage at the time of the forest fires. Past research has been approached to determine the cause of the forest fire or to predict the occurrence of a forest fire. How to deal with forest fires is also a very important part of how to deal with them, so predicting the number of extinguishment manpower is important. Therefore predicting the number of extinguishment manpower that have been put into the forest fire is something that can be presented as a new perspective. This study presents a model for predicting the number of extinguishment manpower inputs considering the scale of the damage with forest fire on a scale bigger than 0.1 ha as data based on the forest fire annual report(Korea Forest Service; KFS) from 2015 to 2018 using the moderated multiple regression analysis. As a result, weather factors and extinguished time considering the damage show that affect forest fire extinguishment manpower.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.463-472
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• 2023

The amount of damage and the area of damage to forest fires are increasing globally, and the effectiveness analysis of the restoration method after the damage is performed insufficient. This study calculated the area of forest fire damage was calculated using Sentinel-2B satellite images and stack map and the intensity of forest fire damage is analyzed according to the forest type. In addition, the vegetation index was calculated using various wavelength bands. Based on the results, the vegetation resilience by the restoration method was quantitatively. As results, areas with a high proportion of coniferous forests suffered high intensity forest fire damage, and areas with a relatively high ratio of mixed and broad-leaved forests tended to have low forest fire damage. Also, artificial forests showed a recovery of about 92.7% compared to before forest fires and natural forests showed a recovery of about 99.6% from the result of analyzing vegetation resilience in artificial and natural forests after forest fires. Accordingly, it was confirmed that natural forests after forest fire damage had superior vegetation resilience compared to artificial forests. It can be proposed that this study is meaningful in providing important information for efficiently restoring the affected target site and the selection criteria for trees to reduce forest fire damage through the evaluation of vegetation resilience by the intensity of forest fire damage and restoration methods.

• Fire Science and Engineering
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• v.25 no.5
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• pp.39-46
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• 2011

In order to consider the prevention countermeasure to the occurrence of forest fires, analysing characteristic of the past forest fire data is needed. This research analyzed distribution and characteristics of forest fires damage over 30 ha based on statistics data of forest fires in Korea between 1975 and 2010. As a result, the number of forest fires damage over 30 ha as 23 was most occurred in 1978. Forest fires show an upward tendency from 1970 to 2000. Forest fires of 30 ha~50 ha damaged area was most occurred. Forest fire in Gangwon province was occurred as the number of total 66 (37.0 %). Gangwon province was superior in point density analysis. The number of forest fire occurrence over 30 ha was most high to 114 (63.0 %) in April and to 44 (24.3 %) in Sunday. The occurrence number of forest fire and damage caused by forest fire is increasing more and more since 1975, appropriate authorities can use effectively in devising policy for forest fire prevention from this result.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.153-156
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• 2008

Comparative analysis of forest fire danger rating on the forest characteristics of thinning area and non-thinning area on forest fire burnt area was studied in this work. To investigate the effect of thinning slash in forest fire, Gangneung-si Wangsan-myeon, Ulgin-gun Wonnam-Myeon, Samchok-si Gagok-Myeon, in which forest fire broke out, were selected. As a result that investigated forest fire danger ratio between thinning slash and non-thinning slash, leeward scorching ratio(36%), crown damage ratio(29%), mortality of branch at the former are higher than those at the latter, leeward scorching ratio of tree, where thinning slash is around, is 10%-20% higher than that of independent tree. So I estimate that thinning slash has a some effect on the intensity of forest fire. And the result to investigate damage of forest fire according to tree species shows that leeward scorching ratio of conifer is 5% higher than that of non-conifer, and mortality of branch of the former is 19% higher than that of the latter. It is considered that forest fire may affect directly to a tree trunk if it diffuse to piled thinning tree because there was no space between thinning trees and trees. Furthermore, it was found that re-ignition had a chance to occur due to lots of piled thinning trees.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.89-94
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• 2006

Forest damage is a worldwide issue and specially, a forest fire involves damage to itself and causes secondary damage such as a flood etc. However, actually, clear analysis on forest fire damage can be hardly conducted due to difficulty in approaching a forest fire and quite a long period of time for analysis. To overcome such difficulty, recently, forest fire damage has been actively investigated with satellite image data, but it is also difficult to obtain satellite image data fitted to the time a forest fire occurred. In addition, it is burdensome to verify accuracy of the obtained image. Therefore, this study was attempted to look into the damaged districts from forest fires by reference to spectroradiometric characteristics of the obtained vegetation with a spectroradiometer as preliminary work to use satellite image data. To begin with, the researcher analyzed the field survey data each measured 3 months and 6 months after occurrence of a forest fire by judging the extent of the damage through visual observation and using a spectroradiometer in order to investigate any potential errors arising out of one-time visual observation. Besides, in this study, groups showing possibilities that trees might be restored to life and wither to death could be classified on the sampling points where forest fire damage is minor.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.301-306
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• 2020

In this study, analyzed national forest fire statistics by cause, year, region, and damage scale based on the National Fire Data System. as a result, the main cause of forest fires was the most frequent human error. forest fires occurred in areas with high population density. and it was confirmed that the Widest area of forest damage was Gang-Won province, which is rich in forestry resources. by season, it occurred a lot in spring because of the warm temperature and strong wind and low humidity. such disasters directly damage forest facilities such as house and cultural properties as well as destruction of natural resources. therefore in this study, made a suggestion plan for prevention from forest fire with forest fire prevention comprehensive plan of MFOA.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.211-214
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• 2007

After the forest fire, as access is not easy, forest damage degree are determined with Landsat TM image rather than visual inspection. Therefore in this study, damaged areas are extracted with factor analysis and cluster analysis. Second factor analysis was performed for areas suspicious as forest fire damage areas to evaluate accuracy after separating into strong, medium and light forest fire areas.