• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.496-503
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• 2021

Pinus densiflora is an essential tree species native to the Republic of Korea (ROK) and covers most of the total natural forest areas in the ROK. This study was conducted to understand the site characteristics and stand structure of P. densiflora forests distributed at sites where P. densiflora covered over 50% of the stand basal area during the 7th National Forest Inventory (NFI) period from 2016 to 2020. P. densiflora dominated 3,665 circular sample plots (400 m²). P. densiflora forests predominated at elevations less than 600 m above sea level (a.s.l). However, most P. densiflora forests were distributed at the slopes facing south and west over 800 m a.s.l. At altitudes below 800 m, they were distributed at all slopes but dominated at the southern and western slopes. P. densiflora grew mainly in the soils of sandy loam, loam, or silt loam with relative infertility. Dominant tree species distributed with P. densiflora were Quercus mongolica, Q. variabilis, Q. serrata, Prunus serrulata var. pubescens and Castanea crenata by the descending order. P. densiflora, P. thunbergii, and P. rigida were grown in large DBH classes, Quercus species and Fraxinus rhynchophylla in middle DBH classes, while Juniperus rigida and Styrax japonicus in small DBH classes. Dominant tree species distributed mainly at the lower layer of P. densiflora stands were Rhododendron mucronulatum, Q. serrata, Lindera obtusiloba, Fraxinus sieboldiana, Toxicodendron trichocarpum and Rhododendron schlippenbachii by the descending order.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.100-107
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• 2022

Quercus mongolica is an important deciduous tree species in the Republic of Korea; it covers most of the total natural deciduous forest area in the country. In this study, the site characteristics and stand structure of Q. mongolica forests were investigated at sites where Q. mongolica occupied >50% of the total basal area during the 7th National Forest Inventory period (2016-2020). The total number of circular sample plots (400 m²) of Q. mongolica forests was 1,421. These forests were mainly dominant at >800 m above sea level (a.s.l). However, they were also distributed on north-facing slopes at <600 m a.s.l. and gradually on southern slopes with ascending altitudes. Quercus mongolica forests were distributed in silt loam, loam, or sandy loam soils with relatively high fertility. Dominant species distributed with Q. mongolica included Pinus densiflora, Quercus variabilis, Acer pseudosieboldianum, Fraxinus rhynchophylla, and Quercus serrata. Pinus densiflora and Q. variabilis grew in large DBH classes, Q. serrata grew in middle DBH classes, and A. pseudosieboldianum and F. rhynchophylla grew in small DBH classes. The dominant species distributed at the lower layer of Q. mongolica forests were Sasa borealis, Lindera obtusiloba, Rhododendron mucronulatum, Rhododendron schlippenbachii, Q. mongolica, and Fraxinus sieboldiana.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.41-44
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• 2008

In this paper, major species of tree were discriminated in compartment by using LiDAR data and optic imagery. This is an important work in forest field. A current digital stock map has created the aerial photo and collecting survey data. Unlike high resolution imagery, LiDAR data is not influenced by topographic effects since it is an active sensory system. LiDAR system can measure three dimension information of individual tree. And the main methods of this study were to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for calculating tree crown 2D parameter. We should estimate the forest inventory for calculating parameter. 2D parameter has need of area, perimeter, diameter, height, crown shape, etc. Eventually, major species of tree were determined the tree parameters, compared a digital stock map.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.573-581
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• 2010

Natural ecosystem is an essential part to connect with the plan for biodiversity conservation in response strategy against climate change. For connecting biodiversity conservation with climate change strategy, Europe, America, Japan, and China are making an effort to discuss protection necessity through national biodiversity valuation but precedent studies lack in Korea. In this study, we made biodiversity maps representing biodiversity distribution range using species richness in National Forest Inventory (NFI) and Forest Description data. Using regression tree algorithm, we divided various classes by decision rule and constructed biodiversity maps, which has accuracy level of over 70%. Therefore, the biodiversity maps produced in this study can be used as base information for decision makers and plan for conservation of biodiversity & continuous management. Furthermore, this study can suggest a strategy for increasing efficiency of forest information in national level.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.140-148
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• 2016

This study aims to estimate the forest volumes of the economic forest in Gangwon Province of Republic of Korea (hereinafter referred to as Gangwon) through the synthetic estimation. To estimate the forest volume, Stratified systematic sampling method was used along with the forest type maps and the $5^{th}$ National Forest Inventory data. The synthetic estimation includes sample plots of the expanded areas as well as those of the target area, and the forest volume of economic forest in every city and county throughout Gangwon. Results show that the average forest volume calculated by synthetic estimation was $159.6m^3/ha$ in national economic forest and $129.6m^3/ha$ in private economic forest. The total forest volume of the national economic forest was approximately $59.45million\;m^3$, which was $20.18million\;m^3$ higher than that of the private economic forest. On the other hands, the standard error of the national economic forest was approximately ${\pm}2.21m^3/ha$, which was ${\pm}0.30m^3/ha$ lower than that of the private economic forest. The lowest standard errors was about ${\pm}3.12 m^3/ha$ in broad-leaved forest, followed by ${\pm}4.33m^3/ha$ of mixed forest, and ${\pm}5.78m^3/ha$ of coniferous forest.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.382-386
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• 1998

The objectives of this study are to reveal relationship between tree physiology and spectral reflectance on effects of artificial acid rain and to obtain basic data on optimal wave length for forest of LRC sensor on KOMPSAT-2. Three pH levels of artificial acid rain - control, pH4.5 and pH3.0 - were applied to Pinus and Quercus species. Three types of the acid rain were spraied at the amount of 500m1 in every two days. Spectral reflectance data was collected once in a month by using GER 1500 (350~2500nm) or Ll 1800(300~1100nm) Spectroradiometer. The data was measured three times in a pH level. The results of this study are as follows; in April, the spectral reflectance of Pinus species was high in order at the level of pH3.0, control and pH4.5; in May, control, pH3.0 and pH4.5; in June, control, pH4.5 and pH3.0. That of Quercus species was high in the order of control, pH4.5 and pH3.0 in May; in June, control, pH3.0 and pH4.5, especially, within infrared wave length range, control, pH4.5 and ph3.0.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.827-835
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• 2010

Reliable forest statistics provides important information to meet the UNFCCC. In this respect, the national forest inventory has played a crucial role to provide the reliable forest statistics for several decades. However, the previous forest statistics calculated by administrative district has not provided spatial information in a small scale. Thus, this study focused on developing models to estimate an explicit spatial distribution of forest growing stock. For this, first, stand volume model by stand types was developed using National Forest Inventory(NFI) data. Second, forest type map was integrated with this model. NFI data were used to calculate plot-level stand volume and basal area. The stand types of NFI plot including the species composition, age class, DBH class and crown density class are very crucial data to be connected with forest type map. Finally, polygonlevel stand volume map was developed with spatial uncertainty map. Average stand volume was estimated at 85.7 $m^3$/ha in the study area, and at 95% significance interval it was ranged from 79.7 $m^3$/ha to 91.8 $m^3$/ha.

• Korean Journal of Environmental Biology
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• v.34 no.2
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• pp.73-78
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• 2016

Bhutanese forests have been well preserved and can sequester the atmospheric carbon (C). In spite of its importance, understanding Bhutanese forest C dynamics was very limited due to the lack of available data. However, forest C model can simulate forest C dynamics with comparatively limited data and references. In this study, we aimed to simulate Bhutanese forest C dynamics at 6 plots with the Forest Biomass and Dead organic matter Carbon (FBDC) model, which can simulate forest C cycles with small amount of input data. The total forest C stock ($Mg\;C\;ha^{-1}$) ranged from 118.35 to 200.04 with an average of 168.41. The C stocks ($Mg\;C\;ha^{-1}$) in biomass, litter, dead wood, and mineral soil were 3.40-88.13, 4.24-24.95, 1.99-20.31, 91.45-97.90, respectively. On average, the biomass, litter, dead wood, and mineral soil accounted for 36.0, 5.5, 2.5, and 56.0% of the total C stocks, respectively. Although our modeling approach was applied at a small pilot scale, it exhibited a potential to report Bhutanese forest C inventory with reliable methodology. In order to report the national forest C inventory, field work for major tree species and forest types in Bhutan are required.

• Journal of Korean Society of Forest Science
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• v.104 no.2
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• pp.239-247
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• 2015

Since 2006, new national forest inventory in Korea has been restructured to assess current status and and monitor the changes in forest resources based on permanent sample plots. The objective of estimate this study is to assess changes in forest resources such as land use/cover categories and forest stand variables. For this study, permanent plot data were collected between 2006-2008 and 2011-2013 in Chungcheongbuk-do, respectively. In order to produce land use/cover change matrix which plays an important role as an activity data for estimating GreenHouse Gas inventory, permanent plots were classified into six land use/cover categories. Additionally, matrixes for assessing the changes in age class and dominant tree species can provide more detailed information. For forest stand variables(tree density, basal area, growing stock, mean diameter at breath height, and mean height), their growth and change were assessed. The periodic annual growth ratios for tree density and basal area were slightly declined whereas that of growing stock was estimated to be about 3.7%. The uncertainty of changes in forest stand variables is less than 5%, except for tree density (RSE: 58%). The variation of tree density is relatively high compared to the other variables.

• Proceedings of the KSRS Conference
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• v.2
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• pp.590-593
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• 2006

Timber inventory management includes to measure and update forest attributes, which is crucial information for private companies and public organizations in property assessment and environment monitoring. Field measurement would be accurate, but time-consuming and inefficient. For the reason, remote sensing technology has been an alternative to field measurement from an economic perspective. Among several sensors, LiDAR and Radar interferometry are known for their efficiency for forest monitoring because they are less influenced by weather and light conditions, and provide reasonably accurate vertical/horizontal measurement for a large area in a short period. For example, Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED) in the U.S. can provide tree height information and DSM. On the other hand, LiDAR DSM (the first return) and DEM (the last return) can also present tree height estimation. With respect to project site of loblolly pine plantation in Louisiana in the U.S., the accuracy of SRTM C-Band approach estimating tree height was assessed by the LiDAR approaches. In addition, SRTM X-Band and NED were also compared with the results. Plantation year in inventory GIS, which is directly related to forest age, is high correlated with the difference between SRTM C-Band and NED. As a byproduct, several stands of age mismatch could be recognized using an outlier detection algorithm, and optical satellite image (ETM+) were used to verify the mismatch. The findings of this study were (1) the confirmation of usefulness of the SRTM DSM for forest monitoring and (2) Multi-sensors- Radar, LiDAR, ETM+, MODIS can be used for accuracy improvement of forest inventory GIS altogether.