• Journal of Climate Change Research
• /
• v.8 no.4
• /
• pp.385-391
• /
• 2017

This study was conducted to estimate litter carbon stock change from the National Forest Inventory (NFI) data for national greenhouse gas inventory report. Litter carbon stocks were calculated from the NFI dataset in NFI5 (2008) and NFI6 (2013) in Gangwon province. Total carbon stock change of litter was $0.68{\pm}0.71\;t\;C/ha$ from NFI5 (2008) to NFI6 (2013), however, there was no significant difference between the both dataset at 2008 and 2013 year. Litter carbon stock of coniferous stands was higher than deciduous stands in NFI5 (2008) and NFI6 (2013) (P<0.05). This study was limited to pilot study, so we will assess litter carbon stock using more complete data from NFI systems. It can be used as data sources for national greenhouse gas inventory report on forest sector.

• Journal of Forest and Environmental Science
• /
• v.24 no.3
• /
• pp.159-164
• /
• 2008

Forest inventory is a commercial term meaning the preparation of detailed descriptive list of articles with number, quantity and value of each item included. Forest inventory deals with the measurement of trees and stands, the estimation of their volume, growth prediction, biomass, carbon stocks and the description tree characteristics, as well as the land upon which they are growing. National Forest Inventory Center (NFIC) in Korea conducts national forest inventory every 5 years to obtain accurate baseline data for national forest policy. The permanent sample plot data used in were collected by NFI. The objective of this study was to develop methods for quantifying forest resources at national scale based on $5^{th}$ National Forest Inventory (NFI) data in Korea. Forest land area decreased from 6.44 to 6.38 million ha between 1997 and 2007, continuing a slight downward trend in area beginning in the late 1990s. However forest resources of the Korea have continued improving in general condition and quality, as measured by increased average size and volume of trees. Growing-stock volume of the Korea increased from 17 to 123.79 cubic meter per ha between 1976 and 2007. The biomass in Korea was estimated to be 153.81 tons per hectare and carbon stocks in Korea was estimated to be 84.36 tons per hectare by NFI data. This information is important for government officials, public administration, the private business sector, and the researcher. Forest Inventory should be implemented in a way to be able to monitor and assess the forests continuously.

• Journal of Korean Society of Forest Science
• /
• v.106 no.2
• /
• pp.258-266
• /
• 2017

This study was conducted to develop a carbon storage distribution map of Pinus rigida stands in Muju-gun by using of the National Forest Inventory data and digital forest map. The relationships between the stand variables such as height, age, diameter at breast height (DBH), crown density and aboveground biomass of Pinus rigida were analyzed. The results showed that the crown density had the highest positive correlation with a value of 0.74 followed by the height variable with value of 0.61. The aboveground biomass regression models were developed to estimate biomass and carbon storage map. The results of this study showed that the average carbon storage was 58.2 ton C/ha while the total carbon stock of rigida pine forests in Muju area was estimated to be 430,963 C ton.

• Korean Journal of Environmental Biology
• /
• v.34 no.2
• /
• pp.73-78
• /
• 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 Climate Change Research
• /
• v.7 no.4
• /
• pp.499-506
• /
• 2016

This study was conducted to estimate carbon stock and uptake for Larix kaempferi Lamb., the single species, which is the most widely distributed one following Pinus densiflora, using data from 6th national forest inventory and forest type map of 1:5,000. Overall distribution area of Larix kaempferi in South Korea was shown as 272,800ha, in detail, Gangwon-do was the most widely distributed region with 39.6% (108,141 ha) of the whole forest area, and Gyeongsangbuk-do was 18.6%(50,839 ha), Chungcheongbuk-do was 15.1%(41,205ha) in order. As the results of analysis in carbon stock and uptake for each province, the values were high with Gyeonggi-do 109.0 tC/ha, $10.3tCO_2/ha/yr$, Gangwon-do 349.1 tC/ha, $9.7tCO_2/ha/yr$ in order, and Jeollabuk-do was the lowest with 78.3 tC/ha, $7.6tCO_2/ha/yr$. Also, the results of estimation in total carbon stocks and uptakes by year (1989~2015) were turned out that total carbon stocks and uptakes were 24,891 thousand tC, $2,428thousand\;tCO_2$ in 2015, increasing about 4.8 times and 3.8 times each compared with 5,238 thousand C/ha, $640thousand\;CO_2$ in 1989. Although forest area was decreased 26.6% with 371,884 ha in 1989 to 272,800 ha in 2015, carbon stocks and uptakes were increased in 2015 in that forest stock was increased 126% compared to 1989.

• Journal of Climate Change Research
• /
• v.8 no.4
• /
• pp.393-399
• /
• 2017

According to the United Nations Framework Convention on Climate Change (UNFCCC), all parties have to submit the national GHG inventory report. Estimating carbon stocks and changes in Land Use, Land-Use Changes and Forestry (LULUCF) needs an activity data and emission factors. So this study was conducted to develop carbon emission factor for Robinia pseudoacacia L., Betula platyphylla var. japonica, and Liriodendron tulipifera. As a result, the basic wood density ($g/cm_3$) was 0.64 for R. pseudoacacia, 0.55 for B. platyphylla, and 0.46 for L. tulipifera. Biomass expansion factor was 1.47 for R. pseudoacacia, 1.30 for B. platyphylla, and 1.24 for L. tulipifera. Root to shoot ratio was 0.48 for R. pseudoacacia, 0.29 for B. platyphylla, and 0.23 for L. tulipifera. Uncertainty of estimated emission factors on three species ranged from 3.39% to 27.43% within recommended value (30%) by IPCC. We calculated carbon stock and change using these emission factors. Three species stored carbon in forest and net $CO_2$ removal was $1,255,398\;t\;CO_2/yr$ during 5 years. So we concluded that our result could be used as emission factors for national GHG inventory report on forest sector.

• Journal of Climate Change Research
• /
• v.6 no.4
• /
• pp.303-310
• /
• 2015

This study was conducted to estimate of carbon stock and greenhouse gas (GHGs) removals by tree species and forest type at Gangwon province. We used a point sampling data with permanent sample plots in national forest inventory and national emission factors. GHGs emissions was caclulated using the stock change method related to K-MRV and IPCC guidance. Total carbon stock and greenhouse gas removals were high in deciduous forest and species than in coniferous. The range of annual net greenhouse gas emissions in other deciduous species was from $-11,564.83Gg\;CO_2\;yr^{-1}$ to $-13,500.60Gg\;CO_2\;yr^{-1}$ during 3 years (2011~2013). On the other hand, coniferous forest was temporally converted to source due to reducing of growing stock in 2012. It was that growing stocks and forest area were likely to reduce by the deforestation and clear cutting. This study did not consider other carbon pools (soil and dead organic matter) due to the lack of data. This study needs to complement the activity data and emission factors, and then will find the way to calculate the greenhouse gas emissions and removals in the near future.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.18 no.5
• /
• pp.61-72
• /
• 2015

This study was reviewed the national greenhouse gas inventory report (NIR) of Annex I countries and estimated national greenhouse gas inventory on wetlands in Korea. Annex I countries submitted National Inventory Report which are focused on land converted to wetlands category and wetland remaining wetland (mainly peat lands) because IPCC did not suggest a formal methodology on flooded land. So we conducted a study on estimating of national greenhouse gas inventory in wetland (flooded land). The total annual $CO_2-eq.$ emission of wetland remaining wetland (flooded land) was ranged from 99.9 Gg $CO_2-eq.$ to 237.1 Gg $CO_2-eq.$ from 1990 to 2012. The $CO_2-eq.$ emissions was declined after peaking in 1995, however, it slightly increasing in recently years. The latest total $CO_2-eq.$ emission from flooded land was 117.7 Gg $CO_2-eq.$ in 2012 which was covered only 0.00002% of national GHG inventory. This means that flooded land is not key-category in Korea. We will consider an improvement for emissions of flooded land, if IPCC suggest formal or complementary methodology.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.2
• /
• pp.39-48
• /
• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

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