• Journal of Korean Society of Forest Science
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• v.99 no.3
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• pp.285-291
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• 2010

Since 2006, the $5^{th}$ National Forest Inventory (NFI) has been implemented to provide forest resources statistics at the national level and at the county level as well. However, it needs a small-area estimator for estimating forest statistics at the county-level due to a small number of samples collected within a county. This study was conducted to evaluate the applicability of a geographical-based synthetic estimator for estimating forest growing stock volumes at the county level. The NFI-field plots surveyed were post-stratified into three forest cover types. In the synthetic estimator, field plots within a geographical-based super-county for each county were used to estimate stratum weights and stratum mean volumes. It was resulted that estimated stratum weights using the synthetic estimation were significantly differ from forest cover maps. The standard errors of estimated mean by the synthetic estimation that ranged from ${\pm}3.5\;m^3$/ha to ${\pm}7.7\;m^3$/ha were more smaller than those (${\pm}7.8\;m^3/ha{\sim}{\pm}24.7\;m^3/ha$) by the direct estimation. This means that the synthetic estimation is possible to provide more precise estimates of mean volumes.

• Atmosphere
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• v.33 no.1
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• pp.61-72
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• 2023

Accurate estimation of forest carbon stocks is important in establishing greenhouse gas reduction plans. In this study, we estimate the spatial distribution of forest carbon stocks using machine learning techniques based on high-resolution remote sensing data and detailed field survey data. The high-resolution remote sensing data used in this study are Landsat indices (EVI, NDVI, NDII) for monitoring vegetation vitality and Shuttle Radar Topography Mission (SRTM) data for describing topography. We also used the forest growing stock data from the National Forest Inventory (NFI) for estimating forest biomass. Based on these data, we built a model based on machine learning methods and optimized for Korean forest types to calculate the forest carbon stocks per grid unit. With the newly developed estimation model, we created forest carbon stocks maps and estimated the forest carbon stocks in South Korea. As a result, forest carbon stock in South Korea was estimated to be 432,214,520 tC in 2020. Furthermore, we estimated the loss of forest carbon stocks due to the Donghae-Uljin forest fire in 2022 using the forest carbon stock map in this study. The surrounding forest destroyed around the fire area was estimated to be about 24,835 ha and the loss of forest carbon stocks was estimated to be 1,396,457 tC. Our model serves as a tool to estimate spatially distributed local forest carbon stocks and facilitates accounting of real-time changes in the carbon balance as well as managing the LULUCF part of greenhouse gas inventories.

• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.133-141
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• 2009

This study was conducted to support for determining an efficient sampling design for forest resources assessments in South Korea with respect to statistical efficiency. For this objective, different systematic sampling designs were simulated and compared based on an artificial forest population that had been built from field sample data and satellite data in Yang-Pyeong County, Korea. Using the k-NN technique, two thematic maps (growing stock and forest cover type per pixel unit) across the test area were generated; field data (n=191) and Landsat ETM+ were used as source data. Four sampling designs (systematic sampling, systematic sampling for post-stratification, systematic cluster sampling, and stratified systematic sampling) were employed as optimum sampling design candidates. In order to compute error variance, the Monte Carlo simulation was used (k=1,000). Then, sampling error and relative efficiency were compared. When the objective of an inventory was to obtain estimations for the entire population, systematic cluster sampling was superior to the other sampling designs. If its objective is to obtain estimations for each sub-population, post-stratification gave a better estimation. In order to successfully perform this procedure, it requires clear definitions of strata of interest per field observation unit for efficient stratification.

• KDI Journal of Economic Policy
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• v.44 no.4
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• pp.1-24
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• 2022

We investigate how reforestation contributed to stabilization of riverine water levels in South Korea. For the purpose, we estimate an equation capturing dynamic relationships among rainfall, upstream-area tree stock, and downstream water levels in three river systems of Hongcheon, Mangyeong, and Hyeongsan, using daily observations of precipitation and water levels for the period from 1985 to 2005. Simulation based on estimation results shows that increase in the tree stock in a river basin leads to a significantly suppressed peaking in riverine water levels in response to an abrupt and concentrated rain in the upstream area. For instance, an hour-long concentration of 100mm rain results in 0.7m rise in water level if the volume of growing stock is 1 million m³, whereas the rise in water level stays below 0.27m with 5 million m³ in the growing-stock volume.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.300-312
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• 2020

The growing stocks of young forests that are less than10 years of age have been excluded from the Korean forest resource statistics, despite the existence of standing trees; however, sustainable forest management and carbon removals in the forestry section require complete information regarding forest resources. This study developed a method to estimate the growing stocks for young forests from National Forest Inventory (NFI) data. After reviewing previous research on growth characteristics for young forests, we conducted stem analysis of major species, and examined stand characteristics by site index, based on real yield tables. Our statistical analysis results showed that there were few standing trees with diameters at breast height (DBH) above 6 cm in young stands, and that it would have taken 12 years, on average, to reach 6 cm DBH. This suggests that mean tree height by diameter should be assessed at the root, in order to assess growing stocks for young stands through the NFI. Moreover, the database system should be improved to differentiate tree species, since diverse shrubs, including trees, have been surveyed.

• Journal of Forest and Environmental Science
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• v.25 no.3
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• pp.167-175
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• 2009

An exploratory study was conducted in Juri Forest Range-2, a proposed biodiversity conservation area of Bangladesh to explore the present growing stock of tree, regeneration condition and status of non-timber forest products (NTFPs). This conservation area contains both natural and artificial plantation was selected by using multistage random sampling method. For determination of plot size and sampling methods, the quadrate size ($10m{\times}10m$) for tree stock measurement, ($2m{\times}2m$) for regeneration survey, ($20m{\times}20m$) for NTFPs survey was determined. Regarding tree stock survey, 14 species under eight families were found where Tectona grandis shows average number of stem/ha was 624 and basal area/ha was (10.36 $m^2/ha$) followed by Acacia auriculiformis (0.2 $m^2/ha$ and 637 stem/ha), Gmelina arborea (0.2 $m^2/ha$ and 600 stem/ha). In regeneration survey, 14 species were found belonging to 9 families where Alstonia scholaris shows highest (3,750) seedling per hectare. Regarding NTFPs, bamboo and cane are the most common resources. In last ten years, the total timber output was 1,28,596.14 cubic feet and total amount of revenue was 4,64,434 US$. The vacant area is 1,335.5 acre which contains 14% of total area. If this vacant area is planted with suitable species and take proper steps for appropriate management of this species it will be a good biologically diversified area.

• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.314-323
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• 2001

This study aimed to clarify the influencing factors of mesopore ratio on a pore geometry of surface soil in coniferous stands as an index of the water retention capacity. Twenty three factors including site conditions and soil properties were analyzed by spss/pc + for the data collected during March to October of 1993. The factors influencing the mesopore ratio(pF2.7) on the surface soil were as follows; macropore ratio(pF1.6), slope, crown-cover rates, thickness of F layer, organic matter contents, and the growing stock. And influencing factor on the ratio of mesopore in the soil surface was correlated with percentage of amount of clay, soil surface, A and B horizon soil hardness shows high negative significance. Also, multiple regression equations for mesopore ratios of surface soil and surface soil hardness, clear length, growing stock, B horizon of soil hardness, organic matter contents show high significance($R^2$; 0.80). In coniferous stands, it is effective in promoting development on the ratio of mesopore that forest practice for enhancing of the water resource retention capacity should be carried out when the crown-cover rates of stands are more than 80 percentages.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.192-197
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• 1998

This paper demonstrates that it is feasible to evaluate forest degradation and to detect deforestation in the 8156$km^2$ study area affected by expand farming using vegetation indices derived from Landsat TM data. The NDVI-growing stock relation was applied on th Landsat TM data and a 3 second grid DEM, whose coverages could improve the assessment of forest degradation and also estimate the rate of change of forest cover area depending on elevation intervals. The strength of the relationship between the ratio of the greenness and brightness indices and forest degradation conditions would have been more interesting in the deforested areas which were converted to crop farming land.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.702-707
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• 2002

Three periods of land-use maps of the Suomo Basin were drawn from topographic maps (1970a) and Landsat TM/ETM images (1986a and 1999a). The area of each kind of land use was calculated from the three maps. From 1970 to 1999, the area of forestland decreased 17%, the area of sparse forestland increased 8%, and the area of grassland increased 10%. The transferring trend of the land-use is that forestland turned into sparse forestland and brush land, and the brush land degenerated into grassland based on the transferring matrixes from 1970 to 1986, and from 1986 to 1999. According to the local government record and statistical data, forest cover rate had been increasing from 1970 to 1998, but the amount of growing stock had been declining. From 1957 to 1998, the amount of growing stock declined from 423m$^3$/ha to 177m$^3$/ha.

• 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.