• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.41-50
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• 2010

Because mountain area covers a large proportion of entire country, the forest fire have been an important matter in disaster prevention in Korea. Estimation of damaged area after forest fire would be very important because it would be the basis to make budget or to calculate quantities in the restoration plan for the damaged area. In Korea, the damaged area from forest fire is generally surveyed using GPS. In practice, however, the estimation of damaged area from forest fire have been inaccurate in lots of case due to some problems. Korea Forest Service which is taking charge of prevention of forest fire in Korea is managing a large number of helicopters for forest service on the whole country. So, it would be possible to take snapshots of the damaged area after forest fire from the helicopter using a digital camera. This study aims to establish a suitable method to estimate damaged area after forest fire using snapshots which are taken in the air using a digital camera. So, several approaches were implemented and compared. In future, results of this study could be used in a development of a system for investigation of damages from forest fire using digital photographs.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.533-536
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• 2007

The LiDAR data structure has the potential for modeling in three dimensions because the LiDAR data can represent voxels with z value under certain defined conditions. Therefore, it is possible to classify the physical damaged degree of vegetation by forest fire as using the LiDAR data because the physical loss of canopy height and width by forest fire can be relative to an amount of points reached to the ground through the canopy of damaged forest. On the other hand, biological damage of vegetation by forest fire can be explained using the NDVI (Normalized Difference Vegetation Index) which show vegetation vitality. In this study, we graded the damaged degree of vegetation by forest fire in Yangyang-Gun of South Korea using the LiDAR data for physical grading and digital aerial photograph including Red, Green, Blue and Near Infra-Red bands for biological grading. The LiDAR data was classified into 2 classes, of which one was Serious Physical Damaged (SPD) and the other was Light Physical Damaged (LPD) area. The NDVI was also classified into 2 classes which are Serious Biological Damaged (SBD) and Light Biological Damaged (LBD) area respectively. With each 2 classes ofthe LiDAR data and NDVI, the damaged area by forest fire was graded into 4 degrees like damaged class 1,2,3 and 4 grade. As a result of this study, 1 graded area was the broadest and next was the 3 grade. With this result, we could know that the burned area by forest fire in Yangyang-Gun was damaged rather biologically because the NDVI in 1 and 3 grade appeared low value whereas the LiDAR data in 1 and 3 grade included light physical damage like the LPD.

• Fire Science and Engineering
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• v.20 no.2 s.62
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• pp.54-63
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• 2006

The number of forest fire under various conditions such as year, month, time, day of the week, region, damaged species, cause, and damaged area are checked, and the statistics of the forest fire causing materials in recent 14 years ('91-'04) are analyzed. The result shows that the year majority of forest fires had happened in last 14 year was 2001 and most of forest fire occurred in April, Sunday, around 14:00 to 15:00. The most damaged region is Gyeongsangbuk-Do, followed by Gangwon-Do, Jeollabuk-Do, and Gyeonggi-Do. The most damaged species is pine tree. The main causes of forest fires are accidental fire and incineration of a field boundary; however, recently, incendiarism is increased. The result of analysis on the damaged area shows that small fires under 5 ha occurred most frequently and large fires (over 30 ha) occurred mostly in Kangwon province (44.2%). The result also shows that the large forest fires (1,113 minutes) require 7.5 time more than the small forest fires (148 minutes). Especially, since average damaged area caused by large forest fire was about 470 ha per incident.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.718-719
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• 2003

It is very important to monitor change of a forest. We compare the different seasonal remote sensing data to detect forest damaged by typhoons and build a method to detect the area damaged by typhoons. Study site is located in western Oita prefecture. The multitemporal satellite dataset of this study were consisted of four Landsat TM scenes taken before and after the typhoons. As compared with non-damaged area, it was shown that the reflective characteristic of the damaged area becomes high by band 3, band 5, and band 7. These bands are effective in extracting the typhoon damaged area.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.1-8
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• 2009

The purpose of this study is to find a way to improve damaged forest in rural area in terms of both landscape . quality and regulation. Mountain and forest cover 65% of total land in Korea, and the shortage of areas for developing housing, road and facilities made us to use forest area for above purposes. This led various types of damages on the sensitive rural landscape visually and ecologically. There are rules and regulations for decreasing damaging effect by constructions on forest area, but it was not so effective because theses rules focused on quantitative issues only. This study will consist of three phases, 1. analyse landscape damage types by development tendencies in forest area 2. find diminution plan on each damage types 3. set improvement on rules and regulations both qualitatively and quantitatively. This study will meet the goal of improving and managing rural and forest landscape by providing objective standards, rational procedure and amelioration plan.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.75-83
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• 2004

In Korea the number of forest fire occurrence and its damaged area have increased drastically and the plans for afforestation such as sound erosion control restoration and forestation have performed to restore for forest fire damaged area. In this study fire resistant forest was developed by selecting fire resistance tree species and applying GIS analysis, considering the characteristic of forest fire and location environment in forest fire damaged area along the east coast. Moreover, it showed the possibility of how spatial information technology such as virtual GIS could be applied during restoring forest fire damaged area and approaching landscape ecology researches. Especially the fire resistant forest was established by using GIS analysis against large scaled forest fires then the best forest arrangement was performed through this fire resistant forest species and 3D modeling in study area. In addition, the forest landscape was established through site index on passing years and then 3D topography and tracking simulation, which is very similar to real world, were constructed by using virtual GIS.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.240-249
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• 2006

Recently, dispersion of damaged forest by pine wilt disease has been regarded as a serious social issue. Damages by pine wilt disease have been spreaded by natural area expansion of the vectors in the damaged area, while the national wide damage spread has induced by human-involved carrying infected trees out of damaged area. In this study, damaged trees were detected and located on the digital map by aerial photograph and terrestrial surveys. The spatial distribution pattern of damaged trees, and the relationship of spatial distribution of damaged trees and some geomorphological factors were geostatistically analysed. Finally, we maked natural spread pattern map of pine wilt disease using geostatistical CART(Classification and Regression Trees) model. This study verified that geostatistical analysis and CART model are useful tools for understanding spatial distribution and natural spread pattern of pine wilt diseases.

• 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%.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.29-39
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• 2020

Forest fire is a critical disaster that causes massive destruction of forest ecosystem and economic loss. Hence, accurate estimation of the burned area is important for evaluation of the degree of damage and for preparing baseline data for recovery. Since most of the area size damaged by wildfires in Korea is less than 1 ha, it is necessary to use satellite or drone images with a resolution of less than 10m for detecting the damage area. This paper aims to detect wildfire-damaged area from a Kompsat-3 image using the indices such as NDVI (normalized difference vegetation index) and FBI (fire burn index) and to examine the classification characteristics according to the methods such as Otsu thresholding and ISODATA(iterative self-organizing data analysis technique). To mitigate the salt-and-pepper phenomenon of the pixel-based classification, a gaussian filter was applied to the images of NDVI and FBI. Otsu thresholding and ISODATA could distinguish the burned forest from normal forest appropriately, and the salt-and-pepper phenomenon at the boundaries of burned forest was reduced by the gaussian filter. The result from ISODATA with gaussian filter using NDVI was closest to the official record of damage area (56.9 ha) published by the Korea Forest Service. Unlike Otsu thresholding for binary classification,since the ISODATA categorizes the images into multiple classes such as(1)severely burned area, (2) moderately burned area, (3) mixture of burned and unburned areas, and (4) unburned area, the characteristics of the boundaries consisting of burned and normal forests can be better expressed. It is expected that our approach can be utilized for the high-resolution images obtained from other satellites and drones.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.687-690
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• 2005

Recently there have been a lot of kinds of damages in forest area such as forest fires, forest pest, landslide so that the efficient methods to mange those information and the way to face them are deadly needed. In this study, there were preparing the various vegetation index map and comparing them with the field surveying the tried to figure out which vegetation index algorism is the best proper to present forest fire damaged area. These all were based on Landsat ETM+ satellite image (2000.10.16). The result of this study is to select the high correlation algorism among the various vegetation indexes and then construct the forest fire disaster map, the case of forest fires damaged area.