• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.119-129
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• 2010

The joint use of remotely sensed data and field measurements has been widely used to estimate aboveground carbon stock in many countries. Recently, Korea Forest Research Institute has developed new carbon emission factors for kind of tree, thus more accurate estimate is possible. In this study, the aboveground carbon stock of Danyang area in South Korea was estimated using k-Nearest Neighbor(kNN) algorithm with the 5th National Forest Inventory(NFI) data. Considering the spectral response of forested area under the climate condition in Korea peninsular which has 4 distinct seasons, Landsat TM seasonal satellite images were collected. As a result, the estimated total carbon stock of Danyang area was ranged from 3542768.49tonC to 3329037.51tonC but seasonal trends were not found.

• 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 Ecology and Environment
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• v.44 no.1
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• pp.8-25
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• 2020

Background: Species of the genera Eucalyptus, Cupressus, and Pinus are the most widely planted tree species in the country in general and in Chilimo dry Afromontane forest in particular. Eucalyptus covers 90% of the total planted forest area in the country. However, only limited information exists in the country regarding aboveground biomass (AGB), belowground biomass (BGB), growth, and yield. This study was conducted to assess the variables on 25 and 30 years of age for three planted species: Cupressus lusitanica, Eucalyptus saligna, and Pinus patula in Chilimo plantation forest, in the Central Highlands of Ethiopia. A two-times inventory was conducted in 2012 and 2017. A total of nine square sampled plots of 400 ㎡ each, three plots under Cupressus lusitanica, 3 Eucalyptus saligna, and 3 Pinus patula were used for data collection. Data on height, diameter, soil, and tree stumps were collected. Percent C, % N, and bulk density was performed following chemical procedure. Results: The aboveground biomass ranged from 125.76 to 228.67 t C ha^-1 and the basal area and number of stems from 3.76 to 25.50 ㎡ ha^-1 and 483 to 1175 N ha^-1, respectively. The mean annual basal area and volume increment were between 0.97 and 1.20 ㎡ ha^-1 year^-1 and 10.79 and 16.22 ㎥ ha^-1 year^-1. Both carbon and nitrogen stock of the planted forest was non-significant among the tree species. Conclusion: The aboveground biomass, growth, and yield significantly varied among the species. Cupressus lusitanica had the highest aboveground biomass, volume, and basal area, while Eucalyptus saligna had the lowest value. To a depth of 1 m, total carbon stored ranged from 130.13 to 234.26 t C ha^-1. The total annual carbon sequestration potential was 12,575.18 t CO₂ eq. Eucalyptus has the highest carbon stock density and growth rate than other species.

• Journal of Forest and Environmental Science
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• v.37 no.3
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• pp.193-205
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• 2021

The importance of forests and trees in climate change mitigation and soil nutrient cycling cannot be overemphasized. This study assessed the above-ground carbon stock of two exotic and two indigenous tree species - Gmelina arborea, Tectona grandis, Khaya grandifoliola and Nauclea diderrichii and their litter impact on soil nutrient content of an arboretum within the University of Port Harcourt, Nigeria. Data were collected from equal sample plots from the four species' compartments. Tree growth variables including total height, diameter at breast height, crown height, crown diameter and merchantable height were measured for the estimation of above-ground carbon stock. Soil samples were collected from a depth of 0-30 cm from each compartment and analyzed for particle size distribution, organic carbon, total nitrogen, available phosphorus, exchangeable bases, exchangeable acidity, cation exchange capacity, base saturation, pH, Manganese, Iron, Copper and Zinc. Analysis of Variance (ANOVA) was used to test for significant difference (p<0.05) in the carbon contents of the four species and the soil nutrient contents of the different species' compartments. Pearson correlation was used to assess the relationships between the carbon contents, growth parameters and soil parameters. The highest and lowest carbon stock per hectare was observed for G. arborea (151.52 t.ha^-1) and K. grandifoliola (45.45 t.ha^-1) respectively. Cation exchange capacity and base saturation were highest and lowest for soil under G. arborea and K. grandifoliola respectively. The pH was highest and lowest for soil under G. arborea and T. grandis respectively. Carbon stock correlated positively with dbh, crown diameter, merchantable height and Zn and negatively with base saturation. The study revealed that G. arborea and N. diderrichii can effectively be used for reforestation and afforestation programmes aimed at climate change mitigation across Nigeria. Therefore, policies to encourage and enhance their planting should be encouraged.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.569-576
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• 2021

This study developed an estimation model for litterfall input using the stand parameters (basal area, stand density, mean DBH, and carbon stocks of the aboveground tree biomass) collected from the Korean red pine (Pinus densiflora S. et Z.) stands of seven regions in Gyeongsangnam-do. The mean annual litterfall was 2,779 kg ha^-1 year^-1 for needles, 883 kg ha^-1 year^-1 for miscellaneous, 611 kg ha^-1 year^-1 for broadleaved, 513 kg ha^-1 year^-1 for branches, and 340 kg ha^-1 year^-1 for bark litter. The mean annual total litterfall was 5,051 kg ha^-1 year^-1. Litterfall components were significantly correlated with stand parameters, except for broadleaved litter. A stronger correlation was observed between the carbon stock of the aboveground tree biomass and all the litterfall components compared with the other stand variables. The allometric equations for all the litterfall components were significant (P < 0.05), with the stand parameters accounting for 5%-43% and 8%-42% of the variation in the needle litter and total litterfall, respectively. The results indicated that the annual litterfall inputs of the Korean red pine stands on a regional scale can be effectively estimated by allometric equations using the basal area and carbon stocks of the aboveground tree biomass.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.33-46
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• 2023

In this study, carbon storage in the aboveground biomass, litter layer, and soil layer was calculated for abandoned mining restoration areas to determine the level of carbon storage after the restoration project through comparison with the ecological reference. Five survey sites were selected for each abandoned mining restoration area in Boryeong-si, Chungcheongnam-do, and the ecological reference that can be a goal and model for the restoration project. The carbon storage in the restoration area was 0~21.3Mg C ha^-1, the deciduous layer 3.3~6.0Mg C ha^-1, and the soil layer(0-30cm) 8.3~35.1Mg C ha^-1, showing a significant difference in carbon storage by target site. The total carbon storage was between 6.1 and 35.3% of the ecological reference, with restoration area ranging from 14.0 to 62.4 Mg C ha^-1. The total carbon storage in the restoration area and the ecological reference differed the most in the aboveground biomass and was less than 12%. Based on these results, forest restoration area need to improve the carbon storage of forests through continuous management and monitoring so trees can grow and restore productivity in the early stages of the restoration project. The results of this study can be used as primary data for preparing future forest restoration indicators by identifying the storage of abandoned mining restoration areas.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.161-182
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• 2019

Quantifying the amount of carbon pools in forest ecosystems enables to understand about various carbon pools in the forest ecosystem. Therefore, this study was conducted in the Chilimo dry afromontane forest to estimate the amount of carbon stored. The natural forest was stratified into three forest patches based on species composition, diversity, and structure. A total of 50 permanent sample plots of 20 m × 20 m (400 ㎡ ) each were established, laid out on transects of altitudinal gradients with a distance of 100 m between plots. The plots were measured twice in 2012 and 2017. Tree, deadwood, mineral soil, forest floor, and stump data were collected in the main plots, while shrubs, saplings, herbaceous plants, and seedling data were sampled inside subplots. Soil organic carbon (SOC %) was analyzed following Walkely, while Black's procedure and bulk density were estimated following the procedure of Blake (Methods of soil analysis, 1965). Aboveground biomass was calculated using the equation of Chave et al. (Glob Chang Biol_20:3177-3190, 2014). Data analysis was made using RStudio software. To analyze equality of means, we used ANOVA for multiple comparisons among elevation classes at α = 0.05. The aboveground carbon of the natural forest ranged from 148.30 ± 115.02 for high altitude to 100.14 ± 39.93 for middle altitude, was highest at 151.35 ± 108.98 t C ha^-1 for gentle slope, and was lowest at 88.01 ± 49.72 t C ha^-1 for middle slope. The mean stump carbon density 2.33 ± 1.64 t C ha^-1 was the highest for the middle slope, and 1.68 ± 1.21 t C ha^-1 was the lowest for the steep slope range. The highest 1.44 ± 2.21 t C ha^-1 deadwood carbon density was found under the middle slope range, and the lowest 0.21 ± 0.20 t C ha^-1 was found under the lowest slope range. The SOCD up to 1 m depth was highest at 295.96 ± 80.45 t C ha^-1 under the middle altitudinal gradient; however, it was lowest at 206.40 ± 65.59 t C ha^-1 under the lower altitudinal gradient. The mean ecosystem carbon stock density of the sampled plots in natural forests ranged from 221.89 to 819.44 t C ha^-1. There was a temporal variation in carbon pools along environmental and social factors. The highest carbon pool was contributed by SOC. We recommend forest carbon-related awareness creation for local people, and promotion of the local knowledge can be regarded as a possible option for sustainable forest management.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.16-33
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• 2012

The aim of this study is to estimate aboveground biomass carbon stocks using ordinary kriging(OK) which is the most commonly used type of kriging and regression kriging(RK) that combines a regression of the auxiliary variables with simple kriging. The analysis results shows that the forest carbon stock in Danyang is estimated at 3,459,902 tonC with OK and 3,384,581 tonC with RK in which the R-square value of the regression model is 0.1033. The result of RK conducted with sample plots stratified by forest type(deciduous, conifer and mixed) shows the lowest estimated value of 3,336,206 tonC and R-square value(0.35 and 0.18 respectively) is higher than that of when all sample plots used. The result of leave-one-out cross validation of each method indicates that RK with all sample plots reached the smallest root mean square error(RMSE) value(22.32 ton/ha) but the difference between the methods(0.23 ton/ha) is not significant.

• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.258-266
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• 2017

This study was conducted to develop a carbon storage distribution map of Pinus rigida stands in Muju-gun by using of the National Forest Inventory data and digital forest map. The relationships between the stand variables such as height, age, diameter at breast height (DBH), crown density and aboveground biomass of Pinus rigida were analyzed. The results showed that the crown density had the highest positive correlation with a value of 0.74 followed by the height variable with value of 0.61. The aboveground biomass regression models were developed to estimate biomass and carbon storage map. The results of this study showed that the average carbon storage was 58.2 ton C/ha while the total carbon stock of rigida pine forests in Muju area was estimated to be 430,963 C ton.