• Journal of The Korean Society of Grassland and Forage Science
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• v.14 no.2
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• pp.120-124
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• 1994

Browse from oriental white oak(Quercus aliena Blume) was analysed for nutritive value and biomass estimation. The content of cmde protein was high on August and September. NDF, ADF and lignin contents were increased with progressing the seasons but IVDMD, TDN, DE and ME levels were not different from the variation of seasons. Tannin content was high on May and June. Basal stem diameter $\times$ height of tress was highly correlated with browse dry weights(r=0.80**) and the linear regression equation are the follows; Y = 8.23 + O.57X(Y = browse dry weight(g), X= basal stem diameter $\times$ height(cm)). Using the traditional cutting method, the amounts of browse was determined as 823 g dry weight per tree, while the new method by the above equation gave a similar results, i. e., 793 g dry weight per tree. The possibility of browse biomass estimation of oriental white oak by the basal stem diameter $\times$ height index was found.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.19-26
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• 2016

Biomass has been used for energy sources from the prehistoric age. Biomass are converted into solid, liquid or gaseous fuels and are used for heating, electricity generation or for transportation recently. Solid biofuels such as bio-chips or bio-pellet are used for heating or electricity generation. Liquid biofuels such as biodiesel and bioethanol from sugars or lignocellulosics are well known renewable transportation fuels. biogas produced from organic waste are also used for heating, generation and vehicles. Biomass resources for the production of above mentioned biofuels are classified under following 4 categories, such as forest biomass, agricultural residue biomass, livestock manure and municipal organic wastes. The energy potential of those biomass resources existing in Korea are estimated. The energy potential for dry biomass (forest, agricultural, municipal waste) were estimated from their heating value contained, whereas energy potential of wet biomass (livestock manure, food waste, waste sludge) is calculated from the biological methane potential of them on annual basis. Biomass resources potential of those 4 categories in Korea are estimated to be as follows. Forest biomass 355.602 million TOE, agricultural biomass 4.019 million TOE, livestock manure biomass 1.455 million TOE, and municipal organic waste 1.074 million TOE are available for biofuels production annually.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.19-20
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• 2013

The cofiring of renewable fuel in coal fired boilers is an attractive option to mitigate $CO_2$ emissions, since it is relatively low cost option for efficiently converting renewable fuel to electricity by adding biomass as partial substitute of coal. However, it would lead to reduce plant efficiency and flexibility in operation, and increase operation cost and capital cost associated with renewable fuels handling and firing equipment. The aim of this study is to investigate reduction of carbon dioxide at varying percentage of biomass in fuel blend to the boiler biomass, and estimate operation and capital cost. Wood pellet, PKS (palm kernel shell), EFB (empty fruit bunch) and sludge are considered as a renewable fuels for a cofiring with coal. Several approaches by the cofiring ratio are chosen from past plant demonstrations and commercial cofiring operation, and they are evaluated and discussed for CO2 reduction and cost estimation.

• Ocean and Polar Research
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• v.42 no.1
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• pp.21-31
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• 2020

Shorebirds migrating along the East Asian-Australasian Flyway (EAAF) have been drastically decreasing due to continuous area loss and quality degradation of intertidal mudflats in the Yellow Sea. Evaluating the current habitat quality by means of habitat carrying capacity estimation could be effective in predicting the magnitude of impacts caused by habitat loss and provide better understanding to improve management strategies. In this study, we estimated the total biomass of Macrophthalmus japonicus, a main prey item of curlews in the Korea peninsular as habitat carrying capacity of the southern intertidal mudflat of Ganghwa Island, one of the key stopover sites for curlews in the EAAF. The result of the estimation took into account spatial differences of prey biomass and the available foraging time by tide patterns. Accordingly, it was found that curlew populations account for 30.26% of the habitat carrying capacity. When we calculated the mean biomass of the area and extrapolated it to the whole area to calculate the total biomass, it was found that the curlews have consumed 10.92% of the total biomass. The results show that the habitat carrying capacity of the southern intertidal mudflat of Ganghwa Island has decreased by 7.8% compared to a study conducted twenty years ago employing the same method. This study shows that there can be considerable differences in the results of habitat carrying capacity estimation between different methods, indicating that various environmental factors that affect the estimation results of habitat carrying capacity must be considered to achieve a more precise analysis and assessment.

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2010.04a
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• pp.70-73
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• 2010

• 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.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.389-401
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• 2011

Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.

• Journal of Korea Foresty Energy
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• v.18 no.2
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• pp.92-99
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• 1999

This study was carried out to understand the primary production of biomass, vertical biomass distribution in the stand and the difference of biomass production for part of the trees by stand density for natural Pinus densiflora forest at Mt. Baekdoo located in northeastern China. The primary production of biomass was estimated by the layers of trees, shrubs, herbs for five density classes. For the biomass estimation of the Pinus densiflora trees in stern, stembark and the above-ground tree, the regression model of logW = a + blog(D$^2$H) + c(D$^2$H) was adapted for all of the density classes where W is dry weight, D$_1$ diameter at breast height, and H, tree height. For the biomass estimation in branch and needle, and the needle area, the regression model of logW=a+blogD+cD was adapted for all of the density classes. With increasing stand density the biomass of trees increased but that of shrubs and herbs decreased. Net primary production of biomass in parts of the tree also increased with increasing stand density. However the percentage of the needle biomass among the total biomass in the above-ground tree decreased with increasing stand density. Consequently, primary production rate of biomass in the above-ground tree increased. The primary production of biomass for each part of the trees in natural Pinus densiflora natural forests showed in descending order : stern, needle, branch, and stembark regardless of stand density.

• Journal of Korean Society of Forest Science
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• v.96 no.5
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• pp.602-608
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• 2007

Forest plantations become important strategy not merely for the financial aspect, but for carbon sequestration and ecosystem stability. Forest plantations increase the density of the forest biomass, which reduce the increase in atmospheric carbon dioxide. Biomass density is also a useful variable for comparing structural and functional attributes of forest ecosystems across a wide range of environmental conditions. In this study, carbon sequestration of teak (Tectona grandis Linn. f.) in the individual tree and plantation levels estimation was carried out Site-specific allometric equation for the estimation of teak tree biomass was developed based on the direct measurement of fifteen (15) harvested trees in the Oak-twin Township of the Bago Yoma Region, Myanmar. A regression equation of the diameter at breast height (DBH) and the aboveground biomass (carbon content) was constructed to estimate the carbon storage level of plantations, which averaged 79 ton/ha. The average carbon accumulation in the soil (up to 30 cm in depth) was estimated 38.89 ton/ha, The highest mean annual increment (MAI) of total carbon was found in the 6-yr-old teak plantation (12.10 ton/ha/yr) whereas the lowest MAI was in the 26-yr-old teak plantation (4.31 ton/ha/yr).