• 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 Ecology and Environment
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• v.43 no.1
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• pp.43-60
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• 2019

Background: Tropical montane forests played an important role in the provision of ecosystem services. The intense degradation and deforestation for the need of agricultural land expansion result in a significant decline of forest cover. However, the expansion of agricultural land did not completely destruct natural forests. There remain forests inaccessible for agricultural and grazing purpose. Studies on these forests remained scant, motivating to investigate biomass and soil carbon stocks. Data of biomass and soils were collected in 80 quadrats ($400m^2$) systematically in 5 forests. Biomass and disturbance gradients were determined using allometric equation and disturbance index, respectively. The regression modeling is employed to explore the spatial distribution of carbon stock along disturbance and environmental gradients. Correlation analysis is also employed to identify the relation between site factors and carbon stocks. Results: The result revealed that a total of 1655 individuals with a diameter of ${\geq}5cm$, representing 38 species, were measured in 5 forests. The mean aboveground biomass carbon stocks (AGB CS) and soil organic carbon (SOC) stocks at 5 forests were $191.6{\pm}19.7$ and $149.32{\pm}6.8Mg\;C\;ha^{-1}$, respectively. The AGB CS exhibited significant (P < 0.05) positive correlation with SOC and total nitrogen (TN) stocks, reflecting that biomass seems to be a general predictor of SOCs. AGB CS between highly and least-disturbed forests was significantly different (P < 0.05). This disturbance level equates to a decrease in AGB CS of 36.8% in the highly disturbed compared with the least-disturbed forest. In all forests, dominant species sequestrated more than 58% of carbon. The AGB CS in response to elevation and disturbance index and SOC stocks in response to soil pH attained unimodal pattern. The stand structures, such as canopy cover and basal area, had significant positive relation with AGB CS. Conclusions: Study results confirmed that carbon stocks of studied forests were comparable to carbon stocks of protected forests. The biotic, edaphic, topographic, and disturbance factors played a significant variation in carbon stocks of forests. Further study should be conducted to quantify carbon stocks of herbaceous, litter, and soil microbes to account the role of the whole forest ecosystem.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.365-373
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• 2022

We compared carbon stocks in tree biomass and soils of Quercus acutissima, Q. mongolica, Q. serrata, and Q. variabilis stands. A total of 531 plots (Q. acutissima: 110 plots, Q. mongolica: 177 plots, Q. serrata: 96 plots, Q. variabilis: 148 plots) were examined between 2016 and 2021 to determine the tree biomass and soil carbon stocks throughout the country. The carbon stocks of tree biomass were significantly higher in Q. mongolica (mean stand age, 57 years, 144.9 Mg C ha^-1) than in Q. variabilis (mean stand age, 43 years, 123.7 Mg C ha^-1), Q. serrata (mean stand age, 43 years, 120.1 Mg C ha^-1), and Q. acutissima (mean stand age, 36 years, 113.2 Mg C ha^-1) stands. The soil carbon concentration was significantly higher in Q. mongolica (A: 43.1 mg C g-1) than in Q. serrata (31.0 mg C g-1), Q. variabilis (25.31 mg C g-1), and Q. acutissima (24.4 mg C g-1) stands. The soil carbon stocks were significantly higher in Q. mongolica (116.8 Mg C ha^-1) than in Q. acutissima (49.3 Mg C ha^-1) stands. Total carbon stocks of tree biomass and soil were highest in Q. mongolica (262 Mg C ha^-1), followed by Q. serrata (218 Mg C ha^-1), Q. variabilis (211 Mg C ha^-1), and Q. acutissima (163 Mg C ha^-1) stands. Multiple linear regressions were performed to estimate the total carbon stocks of the four Quercus spp., and results showed that total carbon stocks increased with increasing elevation, mean diameter at breast height, and basal areas. Basal area and elevation of Quercus spp. stands were important explanatory variables based on multiple linear regressions for estimating carbon stocks.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.330-338
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• 2023

To investigate the impact of forestry projects on the carbon stocks of forests, we estimated the carbon stock change of above-ground and soil before and after forestry projects using forest type maps, forestry project information, and soil information. First, we selected six map sheet with large areas and declining age class based on forest type map information. Then, we collected data such as forest type maps, growth coefficients, soil organic matter content, and soil bulk density of the estimated areas to calculate forest carbon storage. As a result, forest carbon stocks decreased by about 34.1~70.0% after forestry projects at all sites. In addition, compared to reference studies, domestic forest soils store less carbon than the above-ground, so it is judged that domestic forest soils have great potential to store more carbon and strategies to increase carbon storage are needed. It was estimated that the amount of carbon stored before forestry projects is about 1.5 times more than after forestry projects. The study estimated that it takes about 27 years for forests to recover to their pre-thinning carbon stocks following forestry projects. Since it takes a long time for forests to recover to their original carbon stocks once their carbon stocks are reduced by physical damage, it is necessary to plan to preserve them as much as possible, especially for highly conservative forests, so that they can maintain their carbon storage function.

• Journal of the Korean association of regional geographers
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• v.20 no.2
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• pp.206-216
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• 2014

In this study, forest types in Chungheongnam-do were analyzed using Landsat satellite images and digital forest type map as a means to estimate forest carbon stocks. NDVI and Tasseled Cap, ISODATA, and supervised classification among others were used to analyze the forest types. The forest carbon stocks of Chungcheongnam-do were estimated utilizing forest statistical data derived from the classified results. The results indicate that the analysis of forest types through supervised classification yielded the highest overall accuracy in analyzing forest types using satellite images. Coniferous forests(49.3%) accounted for the highest proportion in all the forest types of Chungcheongnam-do, followed by deciduous forests(28.0%) and mixed forests(22.7%). The results of a comparative analysis between forest carbon stocks estimates made using the modified digital forest type map and other estimation methods showed that the method using Tasseled Cap and unsupervised classification yielded the most similar forest carbon stock estimates. The most significant difference, though, was made when only the digital forest type map was used. It is expected that if carbon stocks are estimated by integrating satellite images and digital forest type maps in the future, more accurate results can be derived in estimating forest carbon stocks at a national level.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.708-714
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• 2011

Wood store carbon that the forest absorbed until burned or decomposed over a long period. Such materials are most used in houses except in paper and pulp, and the use of wood in houses play an important role in reducing green-house gases. Therefore, we estimated the amount of carbon stocks in Korean houses, and analyzed how much contribution such stocks offers to green-house gas reduction. As the result, the carbon stocks amount of the wood products in Korean houses was 28.4 million $tCO_2$, which is 4.6% of the total annual green-house gas emission in Korea (620 million $tCO_2$ e), and 77.4% of forest sinks (LULUCF). Even though few wooden houses which use most wood in housing exist in Korea, the carbon stocks of wood products in houses in 2010 increased to 4.1 times that in 1975 (21.4 million $tCO_2$) because the carbon stocks increased due to apartment construction, which hit its stride from the last 1980's.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.233-243
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• 2021

Considering worldwide efforts to mitigate repercussions of climate change, the South Korean government has declared to reach net zero by 2050 to achieve a carbon-neutral sustainable society. For full implementation of NDCs, the government has actively reflected its forestry sector into these strategies. Since coarse woody debris (CWD) in forests represents an enduring carbon storage, it is of particular significance to determine characteristics of changes in carbon stocks of CWD by utilizing data on dead trees monitored in permanent sample plots within national forest inventories (NFIs). In this study, therefore, both occurrence and carbon stocks of CWD were estimated in such plots using data on CWD from the 5^th, 6^th, and 7^th NFIs. Subsequently, characteristics of changes in carbon stocks over time were analyzed. Based on the analysis of 2,021 plots available for monitoring in each NFI of Gangwon Province, the volume of CWD (m³ ha^-1) was found to be 4.71 in the 5^th NFI and 4.09 in the 6^th NFI. However, the volume of CWD declined to 3.09 in the 7^th NFI. Moreover, the annual carbon stocks of CWD (ton C ha^-1) were estimated to be 0.67 in 2009, 0.64 in 2014, and 0.41 in 2019, showing a downward trend over time. This study provides a basis for future research to investigate long-term changes and estimate carbon stocks of CWD in South Korea forests.

• Journal of Korean Society of Forest Science
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• v.104 no.4
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• pp.527-535
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• 2015

With results from previous Korean studies on forest thinning, we conducted a meta-analysis on the effect of thinning on diameter at breast height (DBH) growth and carbon (C) stocks (tree, litter layer, coarse woody debris (CWD), and soils) in Korean forests. Thinning increased the DBH growth and the C stocks in soils by 39.2% and 12.8%, respectively, while it decreased the C stocks in tree by 30.9%. In contrast, thinning had no significant effect on the C stocks in litter layer and CWD. The DBH growth and the C stocks in tree showed significant correlations with thinning intensity and recovery time. The C stocks in litter layer correlated with recovery time while those in CWD and soils did not show significant correlation neither with thinning intensity nor with recovery time. Regression models of the DBH growth and the C stocks in tree were developed to quantify the effect of thinning intensity and recovery time. An integration of the regression model of the tree C stock into forest carbon models is expected to be essential to quantify the effect of thinning on the C stocks in litter layer, CWD, and soils. We also suggested expansion of study species, long-term and frequent monitoring, and investigation on understory vegetation in order to elucidate changes in Korean forests following thinning practices.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.81-99
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• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• 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.