• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

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

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

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.415-424
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• 2017

This study was conducted to estimate carbon stocks of Pinus densiflora with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree age, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010) and Statistical yearbook of forest (2016), and method provided in IPCC GPG was applied to estimate carbon stock and uptake. Performance in predicting stem diameter at a specific point along a stem in Pinus densiflora by applying Kozak's model, $d=a_{1}DBH^{a_2}a_3^{DBH}X^{b_{1}Z^2+b_2ln(Z+0.001)+b_3\sqrt{Z}+b_4e^z+b_5(\frac{DBH}{H})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume table of P. densiflora was derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.445t/m^3$, BEF = 1.445, R = 0.255) of P. densiflora. As the results of analysis in carbon uptake for each province, the values were high with Gangwon-do $9.4tCO_2/ha/yr$, Gyeongsandnam-do and Gyeonggi-do $8.7tCO_2/ha/yr$, Chungcheongnam-do $7.9tCO_2/ha/yr$ and Gyeongsangbuk-do $7.8tCO_2/ha/yr$ in order, and Jeju-do was the lowest with $6.8tC/ha/yr$. Total carbon stocks of P. densiflora were 127,677 thousands tC which is 25.5% compared with total percentage of forest and carbon stock per hectare (ha) was $84.5tC/ha/yr$ and $7.8tCO_2/ha/yr$, respectively.

• Journal of the Korean Wood Science and Technology
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• v.46 no.2
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• pp.202-210
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• 2018

This study was carried out to quantify degree of contribution of harvested wood product (HWP) on mitigation of climate change by valuation of public benefits, environmentally and economically. The potential carbon dioxide emission reduction of HWP was estimated by accounting carbon storage effect and substitution effect. Based on 2014 statistics of Korea Forest Service, domestic HWPs were sorted by two categories, such as wood products produced domestically from domestic and imported roundwood. The wood products were divided into seven items; sawnwood, plywood, particle board, fiberboard (MDF), paper (including pulp), biomass (wood pellet) and other products. The carbon stock of wood products and substitution effects during manufacturing process was evaluated by items. Based on the relevant carbon emission factor and life cycle analysis, the amount of carbon dioxide emission per unit volume on HWP was quantified. The amounts of carbon stock of HWP produced from domestic and from imported roundwood were 3.8 million $tCO_{2eq}$., and 2.6 million $tCO_{2eq}$., respectively. Also, each reduction of carbon emission by substitution effect of HWP produced from domestic and imported roundwood was 3.1 million $tCO_{2eq}$. and 2.1 million $tCO_{2eq}$., respectively. The results of this study, the amount of carbon emission reduction of HWP, can be effectively used as a basic data for promotion of wood utilization to revise and establish new wood utilization promotion policy such as 'forest carbon offset scheme', and 'carbon storage labeling system of HWP'.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.77-93
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• 2013

Global warming accelerates both carbon (C) input through increased forest productivity and heterotrophic C emission in forest soils, and a future trend in soil C dynamics is uncertain. In this study, the Korean forest soil carbon model (KFSC model) was applied to 1,467,458 ha of Pinus densiflora forests in Korea to predict future C dynamics under RCP 8.5 climate change scenario (RCP scenario). Korea was divided into 16 administrative regions, and P. densiflora forests in each region were classified into six classes by their stand ages : 1 to 10 (I), 11 to 20 (II), 21 to 30 (III), 31 to 40 (IV), 41 to 50 (V), and 51 to 80-year-old (VI+). The forest of each stand age class in a region was treated as a simulation unit, then future net primary production (NPP), soil respiration (SR) and forest soil C stock of each simulation unit were predicted from the 2012 to 2100 under RCP scenario and constant temperature scenario (CT scenario). As a result, NPP decreased in the initial stage of simulation then increased while SR increased in the initial stage of simulation then decreased in both scenarios. The mean NPP and SR under RCP scenario was 20.2% and 20.0% higher than that under CT scenario, respectively. When the initial age class was I, IV, V or VI+, predicted soil C stock under CT scenario was higher than that under RCP scenario, however, the countertrend was observed when the initial age class was II or III. Also, forests having a lower site index showed a lower soil C stock. It suggested that the impact of temperature on NPP was higher when the forests grow faster. Soil C stock under RCP scenario decreased at the end of simulation, and it might be derived from exponentially increased SR under the higher temperature condition. Thus, the difference in soil C stock under two scenarios will be much larger in the further future.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.239-245
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• 2017

This study aimed to suggest priority for developing emission factor (EF) and to develop the methodology of quantitative assessment of EF in the forestry sector. Based on the stock-difference method, 17 kinds of EFs (27 EFs based on forest types) were required to calculate the carbon emission in the forestry sector. Priority for developing EFs followed the standards, which is a development plan by the government agency, importance of carbon stock for greenhouse gas, and EFs by the species. Currently, the most urgent development of EFs was carbon fraction in biomass and carbon stock in dead wood. Meanwhile, the quantitative assessment of EF consisted of 7 categories (5 categories of compulsory and 2 categories of quality evaluation) and 12 verification factors. Category in compulsory verification consisted of administrative document, determination methodology of emission factors, emission characteristic, accuracy of measurement and analysis, and data representative. Category in quality evaluation consisted of data management and uncertainty estimates. Based on the importance of factors in the verification process, each factor was scored separately, however, the score needs to be coordinated by the government agency. These results would help build a reliable and accurate greenhouse gas inventory report of Korea.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.357-366
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• 2015

This study was conducted to estimate carbon stocks of Quercus serrata with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010), and method provided in IPCC GPG was applied to estimate carbon storage and removals. Performance in predicting stem diameter at a specific point along a stem in Quercus serrata by applying Kozak's model,$d=a_1DBH^{a_2}a_3^{DBH}X^{b_1Z^2+b_2ln(Z+0.001)+b_3{\sqrt{Z}}+b_4e^Z+b_5({\frac{DBH}{H}})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume tables of Quercus serrata were derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.65t/m^3$, BEF=1.55, R=0.43) of Quercus serrata. As a result of carbon stock analysis by age class in Quercus serrata, carbon stocks of IV age class (11,358 ha, 36.5%) and V age class (10,432; 33.5%) which take up the largest area in distribution of age class were 957,000 tC and 1,312,000 tC. Total carbon stocks of Quercus serrata were 3,191,000 tC which is 3% compared with total percentage of broad-leaved forest and carbon sequestration per hectare(ha) was 3.8 tC/ha/yr, $13.9tCO_2/ha/yr$, respectively.