• Journal of agriculture & life science
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• v.43 no.1
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• pp.17-23
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• 2009

This study was conducted to compare volumes estimated from two taper functions and observed volumes of Chamaecyparis obtusa trees to evaluate accuracy and precision of centroid method. Centroid volume estimates were also compared with volume estimates from existing Forest Resources Evaluation and Prediction Program. The results of this study showed that Gregoire's simple taper function produced unbiased volume estimates while the others were biased. Volume estimates from the Forest Resources Evaluation and Prediction Program were also biased when applied in the Jangseong National Forest regions. These results suggested that the centroid method could produce reliable stem volumes of trees when no other reliable stem volume equations exist.

• Journal of Korean Society of Forest Science
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• v.99 no.3
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• pp.285-291
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• 2010

Since 2006, the $5^{th}$ National Forest Inventory (NFI) has been implemented to provide forest resources statistics at the national level and at the county level as well. However, it needs a small-area estimator for estimating forest statistics at the county-level due to a small number of samples collected within a county. This study was conducted to evaluate the applicability of a geographical-based synthetic estimator for estimating forest growing stock volumes at the county level. The NFI-field plots surveyed were post-stratified into three forest cover types. In the synthetic estimator, field plots within a geographical-based super-county for each county were used to estimate stratum weights and stratum mean volumes. It was resulted that estimated stratum weights using the synthetic estimation were significantly differ from forest cover maps. The standard errors of estimated mean by the synthetic estimation that ranged from ${\pm}3.5\;m^3$/ha to ${\pm}7.7\;m^3$/ha were more smaller than those (${\pm}7.8\;m^3/ha{\sim}{\pm}24.7\;m^3/ha$) by the direct estimation. This means that the synthetic estimation is possible to provide more precise estimates of mean volumes.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.149-160
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• 2015

This study aims to estimate the forest volumes of the upper region of Nam-Han River in ecosystem zoning by forest types and age classes, and to suggest the optimal estimation method through the comparison of the standard errors according to the spatial unit. In the estimation of forest volumes, we used both of direct estimation, which uses sample plots of the target area only, and synthetic estimation, which includes sample plots of the expanded areas as well as those of the target area. As for the spatial expansion, we applied four standards for synthetic estimator: Mountainous zone, Neighbor ecosystem region, Gangwon province, and Buffer zone. The results show that average forest volume per ha, calculated by direct estimation, was $143.5m^3/ha$, while that by synthetic estimation with each standard, was estimated at $146.9m^3/ha$ by Gangwon province, $144.8m^3/ha$ by Buffer zone, $139.8m^3/ha$ by Neighbor ecosystem region, and $138.6m^3/ha$ by Mountainous zone, respectively. The standard errors of direct estimation was $1.79m^3/ha$, while those of synthetic estimation showed not a great difference among the errors. Meanwhile, considering the standard errors by forest type, the lowest was ${\pm}2.3m^3/ha$ of broad-leaved forest, followed by ${\pm}3.3m^3/ha$ of mixed forest, and ${\pm}4.8m^3/ha$ of coniferous forest.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.195-202
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• 2023

In this study, we sought to compare and evaluate the accuracy and predictive performance of machine learning algorithms for estimating the growth of individual Larix kaempferi trees in Gangwon Province, Korea. We employed linear regression, random forest, XGBoost, and LightGBM algorithms to predict tree growth using monitoring data organized based on different thinning intensities. Furthermore, we compared and evaluated the goodness-of-fit of these models using metrics such as the coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE). The results revealed that XGBoost provided the highest goodness-of-fit, with an R² value of 0.62 across all thinning intensities, while also yielding the lowest values for MAE and RMSE, thereby indicating the best model fit. When predicting the growth volume of individual trees after 3 years using the XGBoost model, the agreement was exceptionally high, reaching approximately 97% for all stand sites in accordance with the different thinning intensities. Notably, in non-thinned plots, the predicted volumes were approximately 2.1 m³ lower than the actual volumes; however, the agreement remained highly accurate at approximately 99.5%. These findings will contribute to the development of growth prediction models for individual trees using machine learning algorithms.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.140-148
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• 2016

This study aims to estimate the forest volumes of the economic forest in Gangwon Province of Republic of Korea (hereinafter referred to as Gangwon) through the synthetic estimation. To estimate the forest volume, Stratified systematic sampling method was used along with the forest type maps and the $5^{th}$ National Forest Inventory data. The synthetic estimation includes sample plots of the expanded areas as well as those of the target area, and the forest volume of economic forest in every city and county throughout Gangwon. Results show that the average forest volume calculated by synthetic estimation was $159.6m^3/ha$ in national economic forest and $129.6m^3/ha$ in private economic forest. The total forest volume of the national economic forest was approximately $59.45million\;m^3$, which was $20.18million\;m^3$ higher than that of the private economic forest. On the other hands, the standard error of the national economic forest was approximately ${\pm}2.21m^3/ha$, which was ${\pm}0.30m^3/ha$ lower than that of the private economic forest. The lowest standard errors was about ${\pm}3.12 m^3/ha$ in broad-leaved forest, followed by ${\pm}4.33m^3/ha$ of mixed forest, and ${\pm}5.78m^3/ha$ of coniferous forest.

• Journal of Forest and Environmental Science
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• v.31 no.1
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• pp.47-54
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• 2015

The study was performed to analyze the growth of the red pine (Pinus densiflora) in the Eastern Region of Korea. Stem profile data from a total of 8 dominant trees of which each tree represents its site were collected and used for the analysis. The stem volumes were calculated using Smalian's formula and much higher than the ones by Korea Forest Research Institute in larger than dbh 40 cm. The total bark volumes were more proportionally related to dbh and stem volume than to height and age. The bark thickness and volume decreased as relative height increases but increased as relative dbh increased. The average PAI of dbh and height reached the highest at 0.8 cm/yr (age 15) and at 0.45 m/yr (age 30) respectively, while the average PAI of volume steadily tended to increase up to age 80. The growth percentages of dbh, height and volume tended to decrease with age and volume growth percentage was higher than dbh and height.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.35-42
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• 2024

The Japanese larch (Larix kaempferi [Lamb.] Carriere) is a major timber species in Korea. However, studies on bucking rates and merchantable logs of this species are insufficient in South Korea. To bridge these gaps, in this study, the bucking rate of Japanese larch (Larix kaempferi [Lamb.] Carriere) was computed and the number of long logs and merchantable log volumes were analyzed. Sample trees were bucked according to the log grade for trading, and collected from a forest field in Gangwon Province. The bucking rate of all Japanese larch logs was >89%. The highly profitable 2-4 logs of 3.6 m length from trees with ≤30 cm diameter at breast height (DBH) and 5-6 logs with ≥34 cm DBH were produced. The bucking rate of long logs was >84%; thus, Japanese larch was found to be suitable for the supply of high-grade timber. Additionally, to follow reasonable wood supply plans, merchantable volume tables were offered based on 3.6 m-long number of logs and small-end diameter classes. Understanding the proportion of merchantable log volumes, bucking rates, and the number of long and short logs has large-scale applications in practical forestry.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.504-511
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• 2020

This study estimated planned felling volumes to set targets for management planning of nationwide country-owned forests. Estimates were made using timber harvest prediction methods that use probability density functions, including area weighting (AW), area ratio weighting (ARW), and sample area change ratio weighting (SCRW). Country-owned forest areas in 2010 and 2015 were used to estimate planned felling volumes, as shown in basic forest statistics, and calculations were made assuming that the felling areas were the changes in the forest area over the 5-year period. For the age classes of V-VI, the average felling ages for AW, ARW, and SCRW were 5.41, 5.56, and 5.37, respectively, and the felling areas were 594,462, 586,704, and 580,852 ha, respectively, with ARW reaching closest to the actual changes. The actual changes in the areas and chi-squared test results were most stable with the SCRW method. This study showed that SCRW was more adequate than AW and ARW as a method to predict timber harvests for forest management planning.

• Journal of Korean Society of Forest Science
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• v.94 no.1 s.158
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• pp.45-49
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• 2005

Although the forest accounts in Korea have been constructed partly as the research projects since the mid-1990s, the framework of the accounts has not yet been established. The objective of this study is to provide the physical asset accounts of forested land and forest stock based on the system of integrated environmental economic accounts(SEEA) by utilizing the restructured 2004 statistical yearbook of forestry in Korea. In 2004 yearbook, new variables such as logging area and volumes are added. The logging area and volumes play important roles in constructing forest accounts because the basic structure of the physical asset accounts are composed of the opening stock, closing stock, and the changes between the two. The changes between the opening and closing stock are largely explained by the harvest. In forest accounts, in general, the main elements for the increase in stock are afforestation and reforestation while the main cause for the decrease is logging. In this study we separate the logging into natural or man-made causes. In addition, other useful information for the status of forest is recorded in an annex even if it is not necessary element in the account table. According to the forested land asset accounts generated with 2003 data, the logging area is larger than the reforestation area, and the total forested land is decreased. The logging volume is 0.4% of the total stock volume, and the planed logging volume is more than 3 times larger than the damaged logging volume. The damaged logging volumes by man-made causes is about $300,000m^3$, and it is much than that of natural causes, which is about $55,000m^3$.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.216-224
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• 2021

Aim of this research was to classify forest types at Wando in Jeonnam Province and develop warm temperate forest management system with application of Remote Sensing and GIS. Another emphasis was given to the analysis of satellite images to compare forest type changes over 10 year periods from 2009 to 2019. We have accomplished this study by using ArcGIS Pro and ENVI. For this research, Landsat satellite images were obtained by means of terrestrial, airborne and satellite imagery. Based on the field survey data, all land uses and forest types were divided into 5 forest classes; Evergreen broad-leaved forest, Evergreen Coniferous forest, Deciduous broad-leaved forest, Mixed fores, and others. Supervised classification was carried out with a random forest classifier based on manually collected training polygons in ROI. Accuracy assessment of the different forest types and land-cover classifications was calculated based on the reference polygons. Comparison of forest changes over 10 year periods resulted in different vegetation biomass volumes, producing the loss of deciduous forests in 2019 probably due to the expansion of residential areas and rapid deforestation.