• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.1
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• pp.121-133
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• 2016

It was required to evaluate ecological restorations in a comprehensive way in order to systematically manage conservation areas such as DMZ and national parks in South Korea. In this research we developed a new approach to evaluating ecological restorations with more various indexes than vegetation covering-related indexes. By analyzing damaged areas in the vicinity of DMZ, major damaged types were identified as six classes: landform modification, surface loss, soil pollution, soil physio-chemical modification, vegetation decline and vegetation damaged. From literature review, 39 indexes were selected and were grouped into four divisions: soil property, vegetation growth & structure, habitat property and landscape structure & functions. By conducting a survey with the selected indexes targeting relevant experts, data on relative importance among the divisions and indexes by damaged type were collected. As a result, it was found that the orders and values of weighted values of the divisions were different by damaged type: for example, soil property (0.402), vegetation growth & structure (0.209), habitat property (0.225), landscape structure & function (0.163) for "landform modification"; but soil property (0.171), vegetation growth & structure (0.401), habitat property (0.270), landscape structure & function (0.158) for "vegetation decline". Similarly, evaluation indexes showed different orders and values of relative importance, easiness in field measurement and representativeness for the division by damaged type, and the values were used for calculating importance factor for each index. In the evaluation table, score1 and score2 were made by the importance factors of indexes multiplied by distribution values which present grades and by the weighted values of divisions. In conclusion, while dealing with the damaged type was considered significant for evaluating and managing restorations, further tests on this table with a range of cases were needed to improve its quality.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.908-910
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• 2003

In this paper the extraction method for the best suitable green vegetation area in urban area, Daegu, Korea, was developed using satellite images (1994, 1999, Landsat TM). For this, the GIS overlay analysis of GVI (Green Vegetation Index), SBI (Soil Brightness index), NWI (None-Such wetness Index) was performed to estimate the best suitable green vegetation area. Also, the statistical documents, algorithm and Tasseled-Cap index were used to recognize the change of land cover such as cultivation area, urban area, and damaged area. Through the result of this study, it is possible to monitor the large sized reclamation of land by drainage or damaged area by forest fires. Moreover, information with the change of green vegetation and the status of cultivation by GVI, but also moisture content by percentage by NWI and surface class by SBI can be obtained.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.13-21
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• 2004

The usefulness of the multi-temporal satellite image to monitoring the vegetation recovery process after forest fire was tested. Using multi-temporal Landsat TM and ETM＋data, NDVI and NBR changes over times were analyzed. Both NDVI and NBR values were rapidly decreased after the fire and gradually increased for all forest type and damage class. However, NBR curve showed much clearer tendency of vegetation recovery than NDVI. Both indices yielded the lowest values in severely damaged red pine forest. The results show the vegetation recovery process after forest fire can detect and monitor using multi-temporal Landsat image. NBR was proved to be useful to examine the recovering and development process of the vegetation after fire. In the not damaged forest, however the NDVI shows more potential capability to discriminate the forest types than NBR..

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.1
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• pp.71-79
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• 2008

To find out the effect of the vegetation recovery and the problems of forest land, the researches of the mortality in pine stand and vegetation recovery have been carried out from the burned site. In area which is damaged by fire scar on crown and stem, rate of dead is higher. Where stand growing stocks were totally damaged by crown forest fire, most of vegetation was recovered by sprouts and planted seeds. Vegetation recovery power were depending on the condition of soil depth condition. For the artificial recovery, the damage happened by insects in the planted birches plantation. Rate of growth was somewhat different between Pinus densiflora and Pinus thunbergii in the plantation, because of individual growth rate.

• The Korean Journal of Ecology
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• v.4 no.3_4
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• pp.109-113
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• 1981

The area damaged by the fire effect, most serious artificial damage of forest, was measured to analysis vegetation structures and changes of microclimate at the region of the Pal-gong mountain. Vegetation of whole investigated area was Querceto-Pinetum with rich differetial species. But at the areas fire damaged and undamaged, few differential were noted. The two communites appear physiognomical different of temperature according to height an ddepth at the area of damaged was 11:00 a.m. and 13:00 p.m. at undamaged area. On the whole, high temperature distribution at the damaged area and sensitive reaction by the changes of solar radiation were noticed. Changes of humidity according to height were few, but the saturating deficient at 13:00 p.m. at the whole investigated area extremely high and sensitive at the damaged area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.15-28
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• 2020

Urbanization and industrialization have caused increasing damage to national lands, and ecological restoration has proceeded without any specific assessment of this damage. The purpose of this study is to select indices to assess damaged areas through literature review and panel discussions, and to derive the importance of damaged area assessment indices by analyzing them through the Analytic Hierarchy Process (AHP). This study has derived, via literature review, six types of damage and a total of 18 related assessment indices. A total of 51 responses were collected from surveys and given to experts, and an AHP analysis conducted. As a result of the analysis, "Landform change (0.268)" was of the highest importance, with associated damage types as follows: "Soil contamination (0.193)", "Vegetation damaged (0.149)", "Surface soil loss (0.143)", "Change in soil physiochemical property (0.125)", and "Vegetation decline (0.122)". The analysis determined that the item of the highest importance in the overall assessment of damage was "Slope occurred area (0.100)", and that "Conductivity (0.022)" was of the lowest importance. This study can be presented as a criterion in determining the type and degree of damage in setting priorities for future ecological restoration projects.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.1
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• pp.1-14
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• 2020

In this study, we 1) identified the damaged areas along the south limit line (SLL) of the demilitarized zone (DMZ) by the military's 'DMZ barren land campaign', and 2) categorized the identified damaged areas into a few ecological types. Using high-resolution satellite images, we delineated the total damaged areas to be 1,183.2 ha, which accounted for 50.1% of the 100-m northern buffer regions from the SLL. Of the total damaged areas, 16% were severely damaged, i.e., they had been damaged until recently and so remained barren without vegetation cover. In other areas, the levels of damage were either moderate (59.9%) or slight (24.1%), due to natural succession that turned those areas to grassland or forest. Using satellite image-derived land cover maps and climatic and topographic data, we categorized the damaged areas into seven types: lowland grassland (19.8%), western lowland forest (21.4%), low-altitude forest (25.5%), mid-altitude forest (18.4%), high-altitude forest (6.8%), vicinity in east coast (7.9%), and waterbody (0.2%). These types can be used to identify proper measures to restore ecosystems in the DMZ for now and after Korean reunification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.211-221
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• 2021

The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.