• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.69-85
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• 2014

Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.554-568
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• 2021

Forests are the largest carbon (C) sinks in terrestrial ecosystems. Recently, as enhancing forest C sequestration capacity has been proposed as a basic direction of the Republic of Korea's "2050 Carbon Neutral Strategy," accurate estimation of forest C sequestration has been emphasized. According to the Intergovernmental Panel on Climate Change guidelines, sequestration quantity is calculated from changes in C stocks in forest C pools, such as biomass, deadwood, litter and soil layer, and harvested wood products. However, in Korea, only the overstory biomass increase is now considered the amount of sequestration quantity, so there can be a significant difference from the actual forest C sequestration. In this study, we quantified forest C exchange through C flux measurement using an eddy covariance system and an automated soil chamber system in a 57-year-old Korean pine plantation located in Mt. Taehwa, Gwangju-si, Gyeonggi-do. Then, the net amount of C sequestration was compared with the amount of the overstory biomass increase. We estimated the annual C stock change in the remaining C pools by comparing the net sequestration amount from the C flux measurement with the overstory biomass increase and C stock change in the litter layer. Therefore, the net C sequestration of the Korean pine plantation estimated from the flux measurement was 5.96 MgC ha^-1, which was about 2.2 times greater than 2.77 MgC ha^-1 of the overstory biomass increase. The annual C stock increase in the litter layer was estimated to be 0.75 MgC ha^-1, resulting in a total annual C stock increase of 2.45 MgC ha^-1 in the remaining C pools. Our results indicate that the domestic forest is a larger C sink than the current methods, implying that more accurate calculations of the C sequestration capacity are necessary to quantify C stock changes in C pools along with the C flux measurement.

• 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 Korean Society of Forest Science
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• v.96 no.6
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• pp.644-651
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• 2007

This study compared and estimated the changes in carbon stocks and emissions of harvested wood products (HWP) by applying FAO statistics and domestic statistics for Korean HWP production, import, and export volume, which is almost always supposed to be included in the carbon emissions and removals inventory by country in negotiations since the 2nd commitment period (2013~2017) of the Kyoto Protocol, for assessing the changes in carbon stocks and emissions of HWP. As a result, when applying FAO statistics to the changes in carbon stocks of HWP as of 2005, stock-change approach (SCA) was estimated at 1.434 Tg C, atmospheric-flow approach (AFA) -1.330 Tg C, and production approach (PA) 0.597 Tg C. When applying Korean statistics, SCA was estimated at 1.246 Tg C, AFA -11.520 Tg C, and PA 0.444 Tg C. When applying FAO statistics to $CO_2$ emissions and removals from HWP, SCA showed a decrease of $-5,258Gg\;CO_2$ (removals), AFA showed an increase of $4,877Gg\;CO_2$ (emissions), and PA showed a decrease of $-2,189Gg\;CO_2$ (removals). When applying Korean statistics, SCA showed a decrease of $-4,569Gg\;CO_2$ (removals), AFA showed an increase of $5,573Gg\;CO_2$ (emissions), and PA showed a decrease of $-1,628Gg\;CO_2$, (removals). Therefore, the application of FAO statistics was shown to be more beneficial for the estimation of both the changes in carbon stocks and emissions of HWP by all methods other than that of Korean statistics.

• 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 Korean Society of Forest Science
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• v.102 no.1
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• pp.82-89
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• 2013

Harvest is one of the major disturbances affecting the soil carbon (C) dynamics in forests. However, researches on the long-term impact of periodic harvest on the soil C dynamics are limited since they requires rigorous control of various factors. Therefore, we adopted a modeling approach to determine the long-term impacts of harvest interval, harvest intensity and post-harvest residue management on soil C dynamics by using the Korean Forest Soil Carbon model (KFSC model). The simulation was conducted on Pinus densiflora S. et Z. stands in central Korea, and twelve harvest scenarios were tested by altering harvest intervals (50, 80, and 100-year interval), intensities (partial-cut harvest: 30% and clear-cut harvest: 100% of stand volume), and the residue managements after harvest (collection: 0% and retention: 100% of aboveground residue). We simulated the soil carbon stock for 400 years for each scenario. As a result, the soil C stocks in depth of 30 cm after 400 years range from 50.3 to 55.8 Mg C $ha^{-1}$, corresponding to 98.1 to 108.9% of the C stock at present. The soil C stock under the scenarios with residue retention was 2.5-11.0% higher than that under scenarios with residue collection. However, there was no significant impact of harvest interval and intensity on the soil C stock. The soil C dynamics depended on the dead organic matter dynamics derived from the amount of dead organic matter and growth pattern after harvest.

• Forest Science and Technology
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• v.14 no.4
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• pp.181-191
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• 2018

This study was carried out in the teaching and research forest of the University of Dschang in Belabo, with the aim of analysing land-cover and land-use changes as well as carbon stocks dynamic. The databases used are composed of three Landsat satellite images (5TM of 1984, 7ETM + of 2000 and 8OLI of 2016), enhanced by field missions. Satellite images were processed using ENVI and ArcGIS software. Interview, focus group discussion methods and participatory mapping were used to identify the activities carried out by the local population. An inventory design consisting of four transects was used to measure dendrometric parameters and to identify land-use types. An estimation of carbon stocks in aboveground and underground woody biomass was made using allometric models based on non-destructive method. Dynamic of land-cover showed that the average annual rate of deforestation is 0.48%. The main activities at the base of this change are agriculture, house built-up and logging. Seven types of land-use were identified; adult secondary forests (64.10%), young secondary forests (7.54%), wetlands (7.39%), fallows (3.63%), savannahs (9.59%), cocoa farms (4.28%) and mixed crop farms (3.47%). Adult secondary forests had the highest amount of carbon ($250.75\;t\;C\;ha^{-1}$). This value has decreased by more than 60% for mixed crop farms ($94.67\;t\;C\;ha^{-1}$), showing the impact of agricultural activities on both forest cover and carbon stocks. Agroforestry systems that allow conservation and introduction of woody species should be encouraged as part of a participatory management strategy of this forest.

• 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.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.2
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• pp.167-172
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• 2011

A three-dimensional ecological model (EMT-3D) was applied to Tokyo Bay to simulate 4,4'-bis (2-sulfostyryl)biphenyl (DSBP). The simulated results were in good agreement with the observed values, with a correlation coefficient of R=0.8431 and a coefficient of determination of $R^2$=0.7108. The sensitivity analysis indicated that the photolysis rate is the most important factor. Therefore, the parameters must be considered carefully in modeling. The mass balance results showed that the standing stock of DSBP in water and in particulate organic carbon was 621.2 and 19.5 kg, respectively, and the effluent flux to the open sea was 2.63 and 0.055 kg/day, respectively.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.417-425
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• 2023

As climate change gets severe, the ecosystem acts as an important carbon sink, therefore efforts are being made to utilize these functions to mitigate climate change. In this study, we inventoried and analyzed the previous studies related to carbon storage and flux by ecosystem type (forest, cropland, wetland, grassland, and settlement) and carbon pool (aboveground and belowground biomass, dead wood, Litter, soil organic carbon, and ecosystem) in Korean ecosystems. We also collected the results of previous studies and calculated the average value of carbon storage and flux for each ecosystem type and carbon pool. As a result, we found that most (66%) of Korea's carbon storage and fluxes studies were conducted in forests. Based on the results of forest studies, we estimated the storage by carbon stock. We found that much carbon is stored in vegetation (aboveground: 4,018.32 gC m^-2 and belowground biomass: 4,095.63 gC m^-2) and soil (4,159.43 gC m^-2). In particular, a large amount of carbon is stored in the forest understory. For other ecosystem types, it was impossible to determine each carbon pool's storage and flux due to data limitations. However, in the case of soil organic carbon storage, the data for forests and grasslands were comparable, showing that both ecosystems store relatively similar amounts of carbon (4,159.43 gC m^-2, 4,023.23 gC m^-2, respectively). This study confirms the need to study carbon in rather diverse ecosystem types.