• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.398-406
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• 2013

Afforestation/reforestation (A/R) clean development mechanism (CDM) is the only forestry-based activities allowed under the Kyoto protocol. This study was conducted to develop a methodology to estimate greenhouse gas (GHG) removals of a small scale A/R CDM pilot project in Goseong, Gangwon Province, Korea. AR-AMS0001 was applied as a methodology and selected tree species were Pinus koraiensis, Larix kaempferi, and Betula platyphylla for total area of 75.0 ha. To improve the accuracy on the GHG removals estimation, selection of the baseline scenario and carbon pools and stratification of the project site were conducted. Based on the developed methodology, net anthropogenic GHG removals were estimated as actual net GHG removals, subtracted by baseline net greenhouse gas removals and leakage. As a result, anthropogenic GHG removals of the project were 12,415 ton $CO_2-e$ and 165.5 ton $CO_2-e/ha$. This project is the first A/R CDM in domestic site and could enhance the technical accuracy of the GHG removals estimation by using countryspecific data reflecting the site condition.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.27-42
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• 2016

Forest accounts for almost 64 percents of total land cover in South Korea. For inventorying, monitoring, and managing such large area of forest, application of remote sensing and geographic information system (RS/GIS) technology is essential. On the basis of spectral characteristics of satellite imagery, forest cover and tree species can be classified, and forest cover map can be prepared. Using three dimensional data of LiDAR(Light Detection and Ranging), tree location and tree height can be measured, and biomass and carbon stocks can be also estimated. In addition, many indices can be extracted using reflection characteristics of land cover. For example, the level of vegetation vitality and forest degradation can be analyzed with VI (vegetation Index) and TGSI (Top Grain Soil Index), respectively. Also, pine wilt disease and o ak w ilt d isease c an b e e arly detected and controled through understanding of change in vegetation indices. RS and GIS take an important role in assessing carbon storage in climate change related projects such as A/R CDM, REDD+ as well. In the field of climate change adaptation, impact and vulnerability can be spatio-temporally assessed for national and local level with the help of spatio-temporal data of GIS. Forest growth, tree mortality, land slide, forest fire can be spatio-temporally estimated using the models in which spatio-temporal data of GIS are added as influence variables.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.356-364
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• 2012

This study was to estimate the biomass of Mt. Changbai mountain area using the IKONOS imagery and field survey data. Then, we prepared the regression function using the vegetation index derived from the IKONOS and biomass estimated from field measured data of previous studies, respectively. The five vegetation index which used in the regression model was SAVI, NDVI, SR, ARVI, and EVI. As a result, the rank of the R-square from coefficient of correlation was as follow, SAVI(0.84), NDVI(0.73), SR(0.59), ARVI(0.0036), EVI(0.0026). Finally, we estimated the biomass of non-measured area using the Soil Adjusted Vegetation Index (SAVI). This study can be used as reference methodology for the estimation of carbon sinks of primary forest.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.52-65
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• 2012

The net biomass accumulation (or net primary production, NPP) and gross primary production (GPP) have closely related with carbon accumulations(or carbon exchange) in vegetation. There are many approaches to estimate biomass using remote sensing techniques. The vegetation indices (VIs) can be a methodology to estimate biomass which assumes total chlorophyll contents. Various VIs were characterized with difference development conditions as vegetation species, input datasets. The hyperspectral data have also different spatial/spectral resolutions for aerial surveying. Additionally they need particular spectral bands selection difficulty to calculate the VIs. The objective of this study is to evaluate the correlations with airborne hyperspectral data (compact airborne spectrographic imager, CASI) and spectral unmixing model (or spectral mixture analysis, SMA) to characterize vegetation indices in forest area. The spectral mixture analysis was used to model the spectral purity of each pixel as an endmember. The endmembers are the fraction components derived from hyperspectral data through the SMA. In this study, we choose three endmembers represented vegetation pixels in the hyperspectral data. These endmembers were compared with 9 VIs by the Pearson's correlation coefficient. The results show MTVI1 and TVI have same correlation coefficient with 0.877. The MCARI, especially has very high relationship with vegetation endmembers as 0.9061 at less vegetation and soil distributed site. The MTVI1 and TVI have high correlations with the vegetation endmembers as 0.757 in whole test sites.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.914-921
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• 2010

This study analyzed the above-and belowground biomass, net primary production, stem density, and biomass expansion factors for Pinus densiflora stands of Cheongyang and Boryeong regions in Chungnam. The total dry weights in Cheongyang and Boryeong regions were 122.36 kg/tree and 137.68 kg/tree while the aboveground biomass for these two regions were 72.23 Mg/ha and 143.27 Mg/ha, respectively. Total(above-and belowground) biomass were 91.77 Mg/ha and 178.98 Mg/ha, respectively. Net primary production of above-and belowground biomass in Cheongyang and Boryeong regions were 8.69 Mg/ha, 10.03 Mg/ha, 16.00 Mg/ha and 18.66 Mg/ha, respectively. Stem density (g/$cm^3$) was 0.457 and 0.421 while the above and total biomass expansion factors were 1.394~1.662 and 1.324~1.639, respectively. These results suggested that stand density and site quality could be influenced on the biomass and net primary production of the two regions. In addition, the results of this study could be very useful to calculate carbon sequestrations by applying stem density values and biomass expansion factors for Pinus densiflora in these two regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.108-118
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• 2012

To investigate the responses of yellow poplar (Liriodendron tulipifera L.) seedlings to the interactive effects of the elevated atmospheric $CO_2$ level and nitrogen addition, we measured biomass, photosynthetic pigments, photosynthesis, and the contents of nitrogen (N) and carbon (C) from the seedlings after 16 weeks of the treatments. Yellow poplar seedlings were grown under the ambient ($400{\mu}mol\;mol^{-1}$) and the elevated (560 and $720{\mu}mol\;mol^{-1}$) CO2 concentratoins with three different N addition levels (1.2, 2.4, and $3.6g\;kg^{-1}$) in the Open Top Chambers (OTC). The dry weight of the seedlings enhanced with the increased N levels under the elevated $CO_2$ concentrations and the increment of the dry weight differed among the different N levels. Photosynthetic pigment content of the yellow poplar leaves also increased with the increase of the $CO_2$ concentration levels. The effects of the N levels on the photosynthetic pigment content, however, were significantly different among the $CO_2$ levels. Photosynthetic rates were affected by the levels of $CO_2$ and N concentrations. Stomatal conductance and transpiration rates increased with increasing $CO_2$ concentration. The carboxylation efficiency of the seedlings without N addition increased under the higher $CO_2$ concentrations whereas that with N addition decreased under the elevated $CO_2$ concentrations. Nitrogen and carbon uptake in leaf, stem, and root increased with the elevated $CO_2$ concentration level and N addition. In conclusion, under the elevated $CO_2$ concentrations, physiological characteristics and carbon uptake of the yellow poplar seedling were improved and increased with N addition.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.