• ETRI Journal
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• v.36 no.3
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• pp.450-459
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• 2014

In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree-growing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self-similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.

• Journal of Forest and Environmental Science
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• v.13 no.1
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• pp.66-80
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• 1997

Pinus koraiensis is one of the major speciese which have been recently planted for ten years and consists of 31% of total plantation. Presently young stand less than 30 years consists of 87% of total forest, but tending thinning of it is hardly carried out and the desirable direction for the thinning is not established yet. The objective of the study is to introduce the optimum thinning plan and thinning method through the long-run experiment of tending thinning for the Pinus koraiensis stand. The experiments carry out to interprete its growth model on the subject of two thinning experimental plots and yield table of Pinus koraiensis. As the basic step for understanding the thinning process, a theoretical growth model which is suitable to express the growth process is required. For that purpose, three growth functions (Mitscherlich, 4 parameter Richards, 3 parameter Richards) are applied to the diameter growth of the sample trees which are taken in the two plots. The results show that 3 parameter Richards is the most suitable. It is also verified that the diameter growth, the height growth, and the decrease in the number of stocks can be estimated by this function. To estimate the growth change of single tree, growth model including parameter h which is related to the occupation area of single tree are introduced. The parameter h can be estimated by using the data of the diameter growth obtained from the established experimental plots. Therefore, if both verification and modification of the usefulness of the model suggested is made, equations which tell about the thinning effects could be drived by estimating the growth process of single tree in advance.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.1-17
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• 2024

Forest management is known to beneficially influence stand structure and wood production, yet quantitative understanding as well as an illustrative depiction of the effects of different management approaches on tree growth and stand dynamics are still scarce. Long-term management of beech forests must balance public interests with ecological aspects. Efficient forest management requires the reliable prediction of tree growth change. We aimed to develop a novel hybrid simulation approach, which realistically simulates short- as well as long-term effects of different forest management regimes commonly applied, but not limited, to German low mountain ranges, including near-natural forest management based on single-tree selection harvesting. The model basically consists of three modules for (a) natural seedling regeneration, (b) mortality adjustment, and (c) tree growth simulation. In our approach, an existing validated growth model was used to calculate single year tree growth, and expanded on by including in a newly developed simulation process using calibrated modules based on practical experience in forest management and advice from the local forest. We included the following different beech forest-management scenarios that are representative for German low mountain ranges to our simulation tool: (1) plantation, (2) continuous cover forestry, and (3) reserved forest. The simulation results show a robust consistency with expert knowledge as well as a great comparability with mid-term monitoring data, indicating a strong model performance. We successfully developed a hybrid simulation that realistically reflects different management strategies and tree growth in low mountain range. This study represents a basis for a new model calibration method, which has translational potential for further studies to develop reliable tailor-made models adjusted to local situations in beech forest management.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.539-551
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• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.

• Journal of Korean Society of Forest Science
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• v.94 no.5 s.162
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• pp.321-329
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• 2005

Based on the data representing four typical Korean pine forest types, the age structure, DBH distribution, species composition, and forking rule were systemically analyzed for old-growth Korean pine forest in Liangshui Nature Reserve, northeast China. The age structure of Korean pine trees was strongly uneven-aged with one dominated peak following normal distribution, and age of trees varied from 100 to 180 years within a stand. The DBH and height differences in same age class (20 years) varied from 28 cm~64 cm and 5 to 20 m, respectively. Many conifer and hard wood species, such as spruce, fir, costata birch, basswood, oak, and elm, were mixed with dominated trees of Korean pine. The canopy of the old-growth Korean pine forest can be divided into two layers, and differences of mean age and height between Layer I and Layer II were ranged 80~150 years and 7~13 m, respectively. The Weibull function was used to model the diameter distribution and performed well to describe size-class distribution either with a single peak in over-story canopy and inverse J-shape in under-story canopy for old-growth Korean pine stands. The forking height of Korean pine trees ranged from 16m to 24 m (mean 19.4 m) and tree age about 120 to 160 years old. The results will provide a scientific basis to protect and recover the ecosystem of natural old-growth Korean pine and also provide the model in management of Korean pine plantation.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.143-149
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• 2008

We conduct economic analysis of the snow damage on sugi (Cryptomeria japonica) forest stands in Toyama Prefecture, Japan. We utilize a single tree and distant independent growth simulator called "Silv-Forest." With this growth simulator, we developed an optimization model by dynamic programming, called DP-Silv (Dynamic Programming Silv-Forest). The MS-PATH (multiple stage projection alternative technique) algorithm was embedded as a searching algorithm of dynamic programming. The height / DBH ratio was used to constrain the thinning regime for snow damage protection. The optimal rotation age turned out to be 65 years for the non-restricted case, while it was 50 years for the restricted case. The difference in NPV of these two cases as the induced costs ranged from 179,867 to 1,910,713yen/ha over the rotation age of 20 to 75 years. Under the optimal rotation of 65 years, the cost became 914,226 yen/ha. The estimated annual payment based on the difference in NPV, was from 9,869 yen/ha/yr to 85,900 yen/ha/yr. All in all, 10,000 yen/ha/yr to 20,000 yen/ha/yr seems to cover the payment from the rotation age of 35 to 75 years.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Journal of Forest and Environmental Science
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• v.27 no.3
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• pp.135-141
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• 2011

The present study was carried out from September 2007 to February 2008 in Umfakarin natural forest reserve, South Kordofan, Sudan. The objective was to analyze the effect of different management strategies on yield of gum talha from Acacia seyal. A total of 493 single target trees were selected, based on their diameters, and assigned to tapping treatments in three different stand densities (making a total of nine treatments per stand density). The treatments are as follows: tapping date with three levels (first of October, 15 October and first of November) and two levels of local tapping tools (sonki, and makmak). Untapped trees were used as control. The first picking of gum was started fifteen days after tapping while the subsequent pickings were done in intervals of fifteen days. Yield per tree throughout the season was obtained by summing up the gum yield from all pickings. Yield throughout the season (from first to the last picking) were analyzed. General linear model (GLM) was used to test the effect of different tapping treatments on the yield of gum talha. Post hoc test after analysis of variance (ANOVA) based on Scheffe test was performed to examine the differences in gum yield as a result of different management strategies. The results showed that tapping has a significant influence on gum yield. Analysis of pick-to-pick yield indicated that only three treatments in dense stand density showed a decreasing pattern while the rest of treatments either have constant or unclear patterns. The results of the present study were based on a single season data and that may underscore the real effect of Acacia seyal stands' management strategies on gum talha yield. Conducting gum yield experiments in permanent trial plots are highly recommended in order to analyze gum yield of seasonal time series.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.6
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• pp.16-24
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• 2015

This study quantified storage and annual uptake of carbon for riparian greenspaces established in watersheds of four major rivers in South Korea and explored desirable strategies to improve carbon reduction effects of riparian greenspaces. Greenspace structure and planting technique in the 40 study sites sampled were represented by single-layered planting of small trees in low density, with stem diameter at breast height of $6.9{\pm}0.2cm$ and planting density of $10.4{\pm}0.8trees/100m^2$ on average. Storage and annual uptake of carbon per unit area by planted trees averaged $8.2{\pm}0.5t/ha$ and $1.7{\pm}0.1t/ha/yr$, respectively, increasing as planting density got higher. Mean organic matter and carbon storage in soils were $1.4{\pm}0.1%$ and $26.4{\pm}1.5t/ha$, respectively. Planted trees and soils per ha stored the amount of carbon emitted from gasoline consumption of about 61 kL, and the trees per ha annually offset carbon emissions from gasoline use of about 3 kL. These carbon reduction effects are associated with tree growth over five years to fewer than 10 years after planting, and predicted to become much greater as the planted trees grow. This study simulated changes in annual carbon uptake by tree growth over future 30 years for typical planting models selected as different from the planting technique in the study sites. The simulation revealed that cumulative annual carbon uptake for a multilayered and grouped ecological planting model with both larger tree size and higher planting density was approximately 1.9 times greater 10 years after planting and 1.5 times greater 30 years after than that in the study sites. Strategies to improve carbon reduction effects of riparian greenspaces suggest multilayered and grouped planting mixed with relatively large trees, middle/high density planting of native species mixed with fast-growing trees, and securing the soil environment favorable for normal growth of planting tree species. The research findings are expected to be useful as practical guidelines to improve the role of a carbon uptake source, in addition to water quality conservation and wildlife inhabitation, in implementing riparian greenspace projects under the beginning stage.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.