• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.599-605
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• 2012

The purpose of this study is to estimate diameter distribution, volume per hectare, and carbon stock for Quercus variabilis stand. 354 Quercus variabilis stands were selected on the basis of age and structure, the data and samples for these stands are collected. For the prediction of diameter distribution, Weibull model was applied and for the estimation of the parameters, a simplified method-of-moments was applied. To verify the accuracy of estimates, models were developed using 80% of the total data and validation was done on the remaining 20%. For the verification of the model, the fitness index, the root mean square error, and Kolmogorov-Smirnov statistics were used. The fitness index of the site index, height, and volume equation estimated from verification procedure were 0.967, 0.727, and 0.988 respectively and the root mean square error were 2.763, 1.817, and 0.007 respectively. The Kolmogorov-Smirnov test applied to Weibull function resulted in 75%. From the models developed in this research, the estimated volume and above-ground carbon stock were derived as $188.69m^3/ha$, 90.30 tC/ha when site index and stem number of 50-years-old Quercus variabilis stand show 14 and 697 respectively. The results obtained from this study may provide useful information about the growth of broad-leaf species and prediction of carbon stock for Quercus variabilis stand.

• Korean Journal of Environmental Biology
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• v.34 no.1
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• pp.1-7
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• 2016

As the deforestation in North Korea gets severed, the interest for REDD+ is also increasing. This study analyzed historical land cover changes of the study area which is 10,000 ha in Hwanghaebukdo of North Korea for assessing change in landcover and carbon storage. The result showed that the forest area had decreased from 7,035 ha to 4,293 ha which is approximately 39% of total forest area between 1989 and 2013. The deforestation caused that forest carbon storage had decreased approximately $284,399tCO_2$. Set the baseline and analysed the potential reduction amount of carbon emission, it was estimated that REDD+ project could store approximately $364,704tCO_2$ for next 30 years. This study still has limitations such as lacking in direct field survey and the data of stand volume of each tree species which was replaced with the data of stand volume in South Korea. But, study can be applied for future REDD+ projects in North Korea.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.283-292
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• 2015

The total global emission of $CO_2$ from soils is recognized as one of the largest fluxes in the global carbon cycle. Especially it is necessary to quantify the amount of $CO_2$ emitted by the organic material decomposition processes of microorganisms in the soil, because it becomes one of a factor for determining the carbon stocks in the soil. This study was conducted to estimate the impact of the Korean water deer(Hydropotes inermis)' feces to the soil organic matter. Also, effects of Korean water deer' feces on $CO_2$ emissions of soil and land use pattern dependent $CO_2$ flux quantification are studied. The organic materials in the Korean water deer' feces significantly changed organic matter content of soil and influenced the activity of soil microorganisms, both changing of respiration of the soil and physical chemical components in soil. In particular, C/N ratio and the $CO_2$ flux of soil of four regions (Rice paddy, Fallow ground, Salix koreensis community, Phragmites australis community) showed a statistically highly significant correlation (P<0.01) with the presence or absence of feces. $CO_2$ flux of soil affected by the feces was 2-20 times higher than the soil unaffected by the feces. This study has great significance to quantify the extent of the material circulation and its impact to the terrestrial ecosystem and soil zone throughout Korean water deer' feces. Feces of wildlife can affect soil and soil material circulation.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.87-96
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• 2011

Carbon emissions and storages that are strongly related to global warming has have emerged as one of the important issues while many governments and researchers have been interested in climate change and pollution. In this regards, forest biomass estimation is quite importance since forest biomass works as an important medium of the global carbon cycle between the atmosphere and soil. Forest biomass estimation through field survey needs lots of time and labors, and has accessibility issues. Hence, many researchers have focused on the forest biomass approaches based on remotely sensed data. This research comprehensively reviewed forty one international studies using remote sensing data according to five different categories (i.e., location of study area, size of study area, biome, used remote sensing data, and estimation technology). It would be expected that the results of this study can be used for suggesting domestic research directions; domestic research in this field is at the beginning stage in terms of level of technologies and useful materials. As results, 39% out of the reviewed studies used the areas located in North America. 59% out of the researches dealt with small size of the study areas (less than 3,600km2). In case of biome, around 30% of the studies focused on the boreal/taiga areas. Moreover, 35% and 16% of the studies were carried out using Landsat series and Lidar data, respectively. Finally, regression analysis method was most frequently used for forest biomass estimation by 71% out of 41 studies.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.1
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• pp.5-11
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• 2022

This research evaluated the long-term application effects of different soil amendments on yield, dissolved organic carbon, nitrogen and soil organic carbon stock in rice paddy. The experiment consisted of four different fertilizations; Inorganic fertilization (NPK), NPK+Lime (NPKL), NPK+Silicate (NPKS), NPK+Compost (NPKC). There was no significant difference in rice yield between the treatment groups in 1995, but the rice yields in the NPKL and NPKC treatments in 2019 increased by 4.3% and 14.3% compared to NPK. In terms of soil properties, the pH of NPKS(6.7) and NPKL(6.4) in 2019 increased the most compared to the soil pH before experiment(5.2). The organic matter(OM) content from NPKC treatment increased upto 34 and 27 g kg^-1 in year of 1995 and 2019, respectively, compared to before the test. In NPKS and NPKL treatment, labile carbon and nitrogen content, used as a soil quality indicator, increased by 1.1-1.9 times over the control. From these result, it is suggested that type and application rate of soil amendment should be determined based on the soil analysis before cultivation for sustainable agricultural environment and productivity.

• Journal of Korean Society of Forest Science
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• v.103 no.4
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• pp.593-598
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• 2014

In this study, we developed the carbon emission factors for 4 major species of warm-temperate region in Korea, and tried to provide their carbon emissions and removals estimates using these carbon emission factors. We selected Castanopsis cuspidata, Camellia japonica, Quercus acuta and Quercus glauca as target species and derived their carbon emission factors. The basic wood density that serve as one of the carbon emission factors were 0.583 for Castanopsis cuspidata, 0.657 for Camellia japonica, 0.833 for Quercus acuta and 0.763 for Quercus glauca and their uncertainties ranged from 5.3 to 17.9%. Biomass expansion factors were calculated as well: 1.386 for Castanopsis cuspidata, 2.621 for Camellia japonica, 1.701 for Quercus acuta and 2.123 for Quercus glauca and associated uncertainties varied from 14.7 to 30.5%. Lastly root-shoot ratios for each species were also determined: 0.454 for Castanopsis cuspidata, 0.356 for Camellia japonica, 0.191 for Quercus acuta and 0.299 for Quercus glauca with the uncertainties lying within a range from 19.8 to 35.7%. These three carbon emission factors including basic wood density had the uncertainties of less than 40% recommended by FAO. Therefore the application of country-specific emission factors seemed to provide quite accurate estimates of carbon emissions and removals. The estimation of the carbon stored in the 4 species were also conducted which amounted to $186.10tCO_2/ha$ for Castanopsis cuspidata, $280.63tCO_2/ha$ for Camellia japonica, $344.04tCO_2/ha$ for Quercus acuta and $278.91tCO_2/ha$ for Quercus glauca and their annual carbon removals were $6.65tCO_2/ha/yr$, $6.25tCO_2/ha/yr$, $11.70tCO_2/ha/yr$ and $12.29tCO_2/ha/yr$, respectively. This systematic assessment of forest resources can be a reliable source of information for managing evergreen broadleaved forest in warm temperate regions and thus serve as useful data for effective decision-making to address vegetation zone shifts due to climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.95-106
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• 2010

The performance of Community Land Model version 3.5 - Dynamic Global Vegetation Model (CLM-DGVM) was evaluated through a comparison with the observation over temperate deciduous forest in Gwangneung, Korea. Influence of plant phenology, composition of plant functional type, and climate variability on carbon exchanges was also examined through sensitivity test. To get equilibrium carbon storage, the model was run for 400 years driven by the observed atmospheric data at the deciduous forest of the year 2006. We run the model for 2006 with the equilibrium carbon storage at Gwangneung forest and compared the model output with the observation. A comparison of leaf area index (LAI) between the model and observation indicated that the simulated phenology poorly represented the timing of budburst, leaf-fall, and evolution of LAI. Senescence of the phenology was delayed about four weeks and the simulated maximum LAI (of 5.8 $m^2$ $m^{-2}$) was greater than the observed value (of 4.5 $m^2$ $m^{-2}$). The overestimated LAI contributed to overestimation of both gross primary productivity (GPP) and ecosystem respiration $(R_e)$ through increased photosynthesis and foliar autotropic respiration $(R_a)$, respectively. Despite the discrepancy between the simulated and observed LAI, the simulated tree carbon storage amounts were comparable with the reported values at the site. Change in plant phenology from the simulated to the observed reduced more than six weeks of the plant growth period, resulting in the decreased amount of GPP and $R_e$. These values, however, were still higher (~10% of GPP and 40% of $R_e$) than the observed values. The effect of change in plant functional type composition (from dominant temperate deciduous forest to the coexistence of temperate deciduous and needle leaf forests) on the estimated amount of GPP and $R_e$ was marginal. The influence of climate variability on carbon storage amounts was not significant. The simulated inter-annual variation of GPP and $R_e$ from 1994 to 2003 depended on annual mean air temperature and total radiation but not on precipitation. Other deficiencies of CLM3.5-DGVM have been discussed.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.1-14
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• 2019

Carbon storage is one of the regulating ecosystem services provided by urban street trees. It is important that evaluating the economic value of ecosystem services accurately. The carbon storage of street trees was calculated by measuring the morphological parameter on the field. As the method is labor-intensive and time-consuming for the macro-scale research, remote sensing has been more widely used. The airborne Light Detection And Ranging (LiDAR) is used in obtaining the point clouds data of a densely planted area and extracting individual trees for the carbon storage estimation. However, the LiDAR has limitations such as high cost and complicated operations. In addition, trees change over time they need to be frequently. Therefore, Structure from Motion (SfM) photogrammetry with unmanned Aerial Vehicle (UAV) is a more suitable method for obtaining point clouds data. In this paper, a UAV loaded with a digital camera was employed to take oblique aerial images for generating point cloud of street trees. We extracted the diameter of breast height (DBH) from generated point cloud data to calculate the carbon storage. We compared DBH calculated from UAV data and measured data from the field in the selected area. The calculated DBH was used to estimate the carbon storage of street trees in the study area using a regression model. The results demonstrate the feasibility and effectiveness of applying UAV imagery and SfM technique to the carbon storage estimation of street trees. The technique can contribute to efficiently building inventories of the carbon storage of street trees in urban areas.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.757-765
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• 2012

The purpose of this study was to estimate the spatial-temporal NPP(Net Primary Productivity) and SCS(Soil Carbon Storage) of forest ecosystem under climate change in the capital area of South Korea using Mapss-Century1 (MC1), one of Dynamic Global Vegetation Models (DGVMs). The characteristics of the NPP and SCS changes were simulated based on a biogeochemical module in this model. As results of the simulation, the NPP varies from 2.02 to 7.43 tC $ha^{-1}\;yr^{-1}$ and the SCS varies from 34.55 to 84.81 tC $ha^{-1}$ during 1971~2000 respectively. Spatial mean NPP showed a little decreasing tendency in near future (2021~2050) and then increased in far future (2071~2100) under the condition of increasing air temperature and precipitation which were simulated by the A1B climate change scenario of Intergovernmental Panel on Climate Change (IPCC). But it was estimated that the temporal change of spatial mean NPP indicates 4.62% increasing tendency in which elevation is over 150m in this area. However, spatial mean SCS was decreased in the two future periods under same climate condition.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.