• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.204-212
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• 2010

This study was performed in 22 unthinned Larix olgensis plantations in northeast China. Data were collected on 95 sample trees of different canopy positions and the diameter at breast height ($d_{1.3}$) ranged from 5.7 cm to 40.2 cm. The individual tree models for the prediction of vertical distribution of live crown, branch and needle biomass were built. Our study showed that the crown, branch and needle biomass distributions were most in the location of 60% crown length. These results were also parallel to previous crown studies. The cumulative relative biomass of live crown, branch and needle were fitted by the sigmoid shape curve and the fitting results were quite well. Meanwhile, we developed the crown ratio and width models. Tree height was the most important predictor for crown ratio model. A negative competition factor, ccf and bas which reflected the effect of suppression on a tree, reduced the crown ratio estimates. The height-diameter ratio was a significant predictor. The higher the height-diameter ratio, the higher crown ratio is. Diameter at breast height is the strongest predictor in crown width model. The models can be used for the planning of harvesting operations, for the selection of feasible harvesting methods, and for the estimation of nutrient removals of different harvesting practices.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.149-152
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• 2003

• KCID journal
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• v.14 no.2
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• pp.255-260
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• 2007

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2001.04a
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• pp.58-61
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• 2001

• Journal of Korean Society of Forest Science
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• v.71 no.1
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• pp.74-81
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• 1985

Dimension analysis was used to estimate biomass and net primary production(NPP) in a 36-year-old Japanese red pine (Pines densiflora S. et Z.) natural forest in Kangwondo. Best estimation was made by the equation model of $Wt=aD^bH^c$ where Wt is weight in kg, D is DBH in cm, and H is total tree height in m. Total aboveground biomass was estimated at 198.82 t/ha. Organic matter was distributed in the Japanese red pine stand as follows ; bolewood 68.8%, live branches 16.5%, bolebark 5.4%, foliage 4.6%, dead branches 3.7%, and cones 0.6%. Net primary production was estimated at 15.87 t/㏊/yr and was distributed: bolewood 44.5%, live branches 30.9%, foliage 14.1%, current twig 7.1%, and bolebark 3.3%. Leaf efficiency was estimated at 1.876. The power equation for biomass and IVPP yielded similar results as the results for Pines densiflora in Japan.

• Korean Journal of Environmental Agriculture
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• v.30 no.3
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• pp.252-260
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• 2011

BACKGROUND: Currently, national biomass inventory are being established for efficient management of the potential energy sources. Among the various types of biomass, agricultural wastes are considered to take the biggest portion of the total annual biomass generated in Korea, implying its importance. However, the currently estimated amount is not reliable because the old reference data are still used to estimate total annual amount of agricultural wastes. METHODS AND RESULTS: Therefore, to provide reliable estimation data, a correct conversion factor obtained by taking into account the current situation is required. For this, the current study was conducted to provide the conversion factors for each representative 8 crop through a field cultivation study. Also conversion factors for 18 crops were calculated using the average amount of each crop produced during 2004 and 2008, subsequently; total amount of agricultural wastes generated in 2009 was estimated using these conversion factors. The total biomass of rice straw and rice husk generated in 2009 were 6.5 and 1.1 million tons, respectively, which consist 75% of the total agricultural based wastes, while the total biomass of pepper shoots and apple pruning twigs were 1.0 and 0.6 million tons, respectively. Despite the high amount of rice-based biomass, their applicability for bio-energy production is low due to conventional utilization of these materials for animal feeds and beds for animal husbandry. In addition to exact estimation of the total biomass, temporal variations in both generated amount and the type of agricultural biomass materials are also important for efficient utilization; fruit pruning twigs (January to March); barley-, been-, and mustard-related waste materials (April to June); rice-related waste (September to October). CONCLUSION(s): Such information provided in this study can be used to establish a master plan for efficient utilization of the agricultural wastes on purpose of bio-energy production.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.39-49
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• 2020

Rice paddy cultivation is one of the major sources in methane (CH₄) emission of which accurate assessment would be a prerequisite for agricultural greenhouse gas management. Biomass treatment in paddy fields is an important factor that affects CH₄ emissions and thus needs to be taken into account. The objectives of this study were to apply drone images to investigate organic matter practices and to incorporate into the estimation of CH₄ emissions from paddy fields. Three study areas were selected by one from each of the three different regions of Yeongnam, Honam and Jungbu, which are the most active region in paddy cultivation. The eBee drone was used to take images of the study sites twice a year; Jul mid-season for identifying rice cultivation area; Jan for investigating rice straw management and winter crop cultivation. Based on biomass management practices, different emissions factors were assigned on an individual paddy field and CH₄ emmisions were estimated by multiplying respective areas. The ratios of rice straw application and winter crop cultivation were 1.4% and 37.2% in Hapcheon, 1.3% and 19.8% in Gimje, and 0.0% and 0.5% in Dangjin, respectively. The CH₄ emissions estimates for respective sites were 0.40 ton CH₄/year/ha, 0.34 ton CH₄/year/ha, and 0.29 ton CH₄/year/ha. On average, estimated CH₄ emissions of this study were 28.5% less than the current Tier 2 CH₄ emission estimation method.

• 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 Korean Society of Forest Science
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• v.78 no.3
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• pp.323-330
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• 1989

Pinass densiflora natural forests of four local forms in Korea were studies to investigate effective biomass estimation method. Dimension analysis was used and three allometric regression models, such as logWt=A+BlogD, logWt=$A+B1ogD^2H$ and 1ogWt=A+BlogD+ClogH were applied to estimate biomass, The most accurate estimation was made by the regression model of logWt=A+BlogD+ClogH where Wt is dry weight, D is diameter at breast height, and H is tree height. However, dry weights of cones and dead branches were remotely related to tree size factor, such as D and H. In the interest of practical use. generalized allometric regressions for all samples trees of four stands were computed and analysis of covariance was used to compare the allometric regressions among the four stands. Based on the test criteria applied in this study, significant differences were found in terms of error variance and regression intercept, not in terms of regression slope. These trends suggest a generalized biomass regression is not valid for accurate estimation over a range of four local form stands.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.447-449
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• 2003

Remotely sensed data can be used to estimate biomass production using methodologies relating vegetation indices to light absorption or to leaf photosynthetic capacity. The considerations of both light absorption and photosynthetic capacity in remote sensing-based modeling to estimate biomass production or NPP was introduced based upon Monteith model NPP is one of a evaluation of land degradation. NPP was estimated from annual maximum NDVI by MODIS data. It was known that NPP of the grassland that except the forest and the farming ground was distributed between 50-200g /m2.