• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.197-204
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• 2019

A tree-length harvesting system using the HAM300, which is mounted on a farm tractor prototype machine, have been recently introduced in South Korea for thinning old (>30 years) forests. However, no research has previously been conducted on the characteristics of residual stand damage associated with cable yarding systems on thinning treatment stands in South Korea. Therefore, there were assessed on the degree and quantity of residual stand damage caused by felling and yarding process to broaden the knowledge of residual stand damage on semi-mechanized skyline thinning operations. This study investigated scar size, direction, area, shape type and their distribution on the residual stand damage caused by felling and yarding operations. Damage to residual trees was generated for 7.4% and 6.9% of residual trees in felling and yarding operations, respectively. Damaged direction of scars was located in front-side (38.9%) and up-side (34.7%) for felling operations while the highest scar damage was found on down-side (44.6%) for yarding operations. Scar heights of felling damage were higher than those of yarding damage. In yarding operation, the most of the scars was located within l0m from the center of the skyline corridor. These results should be useful information for forest managers and landowners to reduce residual stand damages and retain valuable timber volume from thinning treatments.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.439-445
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• 2014

In this study, we developed a dynamic stand yield model to estimate the baseline carbon stock, which is essentially required for a forest carbon offset project based on forest management. For developing the yield model, the data was acquired from the databases of the $5^{th}$ National Forest Inventory. The model was validated by comparing its estimations with field measurements that were conducted from 4 study sites (14 plots with thinning treatments) located in Hong-chun, Hoeng-sung, Yang-yang Daechi and Yang-yang Jungja. The difference between the estimations and the field measurements was less than 5%. Using the dynamic stand yield model, we estimated the changes in stand yield volume and carbon stocks for each species according to the baseline scenarios. As the results, we found that baseline carbon stock was the highest at Quercus acutissima stand (83.01tC/ha), while the lowest at Pinus rigida stand (32.17tC/ha) and Pinus densiflora stand of central region (39.09tC/ha). Hence, a project provider could get more carbon emission credits from an improved forest management project when considering the project with Pinus rigida stand or Pinus densiflora stand (central region). The baseline carbon stock and the dynamic stand yield model developed from this study would be useful for designing carbon offset projects based on improved forest management.

• Journal of Korea Foresty Energy
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• v.24 no.2
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• pp.37-45
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• 2005

This study presents a method how to estimate the change of stand volume, the stand biomass and the carbon removals, using dynamic stand growth model according to whether the practices for forest management are implemented or not. As a result, it shows that the rate of stand change was significantly high if the practices were implemented. Consequently, the change of carbon removals was also high. The carbon removals at the stand where the practices were not implemented, was estimated about 0.27tC/ha. And the carbon removals at the stand where the practices were implemented, was estimated 166.02tC/ha(thinning from above) and 163.75tC/ha(thinning from below). It is confirmed that the thinning activities has a great influence on the change of carbon removals and there was little difference of the carbon removals between thinning types. From this result, it is proved that forest management like thinning activities is prerequisite condition to improve the carbon removals of stand.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.80-90
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• 2014

The objective of this research is to estimate the stand volume of Pinus koraiensis, by using the investigated volume and the information of remote sensing(RS), in the research forest of Kangwon National University. The average volume of the research forest per hectare was $307.7m^3/ha$ and standard deviation was $168.4m^3/ha$. Before and after carrying out 3 by 3 majority filtering on TM image, eleven indices were extracted each time. Independent variables needed for linear regression equation were selected using mean pixel values by indices. The number of indices were eleven: six Bands(except for thermal Band), NDVI, Band Ratio(BR1:Band4/Band3, BR2:Band5/Band4, BR3:Band7/Band4), Tasseled Cap-Greeness. As a result, NDVI and TC G were chosen as the most suitable indices for regression before and after filtering, and R-squared was high: 0.736 before filtering, 0.753 after filtering. As a result of error verification for an exact comparison, RMSE before and after filtering was about $69.1m^3/ha$, $67.5m^3/ha$, respectively, and bias was $-12.8m^3/ha$, $9.7m^3/ha$, respectively. Therefore, the regression conducted with filtering was selected as an appropriate model because of low RMSE and bias. The estimated stand volume applying the regression was $160,758m^3$, and the average volume was $314m^3/ha$. This estimation was 1.2 times higher than the actual stand volume of Pinus koraiensis.

• Journal of Forest and Environmental Science
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• v.3 no.1
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• pp.17-20
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• 1983

Through 7-year experiment in Korean pine stand since 1975, the followings are obtained as the results of investigation in several characters: 1. In total volume, the highest value after 1980 was shown in the control plot, which was the second one for 4 years, 1975 to 1979. 2. In the increment ratios of height, diameter at breast height(D. B. H.), and individual volume, the plot with the intermittent period of 3 years showed the higher values than any other plot.

• 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 Korean Society of Forest Science
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• v.105 no.1
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• pp.132-138
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• 2016

The objectives of this study were to infer the parameters of forest stand growth functions of STEMS for Cryptomeria japonica stands of Jeju Hannam Experimental Forest, Korea Forest Research Institute, and to investigate the effects of thinning regimes on the patterns of stand growth and carbon absorption. The forest stand growth functions for the potential diameter growth, modifier, crown ratio and mortality are the major ones composing the independent-tree/distance-free forest stand growth simulator, STEMS. The parameters were inferred using the sets of growth data obtained from stem analyses of 39 trees, chosen from 13 sample plots of the forest stands. The effects of thinning regimes on the patterns of stand growth and carbon absorption were investigated by simulating the stand growth patterns of the case study stand with 3 different thinning regimes: no-thinning, early thinning with low intensity and late thinning with high intensity using the simulator. According to the results of the analyses, the different thinning regimes cause significant effects on the growth patterns of average DBH, average height, diameter distribution and stand volume as well as the amount of carbon absorptions.

• Journal of Korean Society of Forest Science
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• v.90 no.5
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• pp.650-662
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• 2001

The growth and yield models for five different kinds of natural forest types were systemically developed in the natural Broadleaved-Korean pine Forests in Northeast China. The data were collected from 359 temporary plots and 58 permanent plots with area ranged from 0.06 ha to 1.0 ha, ranging in stand age from 43 to 364 years. The Site Class Index (SCI) was introduced to evaluate site quality and the Crown Competition Factor (CCF) was selected as a measure of stand density for the mixed natural forest. The Chapman-Richards function was adopted to develop SCI equation and height-diameter curve. The Schumacher growth function was selected as base model to develop the DBH, basal area, and stand volume growth models by using re-parameterized method. In modeling mean DBH and basal area growth, it was found that the asymptotic parameter A of Schumacher function was exponentially related to site quality (SCI) and stand density (CCF). The rate parameter k was related to stand density and it was independent of SCI. Several validation measures for predicted stand variables were evaluated in the growth and yield models using independent data sets. The results indicated that relative mean errors (RME) in predicted stand attributes were less than ${\pm}5%$ and the estimated precision values of the stand variables were all greater than 95%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2368-2374
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• 2013

Elevator power consists of power consumption in stand-by and in service. This paper designed a fuzzy controller saving stand-by power of elevators in a way that calculates the adequate number of elevators by the variable traffic volume of passenger and then powers off elevators being out of service. Also, the fuzzy controller was designed to minimize a increase of the average passenger's waiting time by the limited number of elevators in service. When the fuzzy controller designed in this paper was applied to the group elevator experimental device, The passenger's waiting time increased approximately 7.5%~9.5%, While the stand-by power saving is expected to be about 675KWh a day per unit and about 236.6KWh a year per unit.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.83-92
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• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.