• Journal of Environmental Science International
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• v.28 no.8
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• Journal of Korean Society of Forest Science
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• v.94 no.2 s.159
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• pp.121-126
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• 2005

This study was carried out to construct a single diameter and a single height model that could localize Chamaecyparis obtusa stand grown in 3 Southern regions of Korea. Dummy variables, which convert qualitative information such as geographical regions into quantitative information by means of a coding scheme (0 or 1), were used to localize growth models. In results, modified form of Gompertz equation, $Y_2={\exp}({\ln}(Y_1){\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))+({\alpha}+{\alpha}_1Al+{\beta}_1k_1+{\beta}_2k_2)(1-{\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))$, for diameter and height was successfully disaggregated to provide different projection equation for each of the 3 regions individually. The use of dummy variables on a single equation, therefore, provides potential capabilities for testing the justification of having different models for different sub-populations, where a number of site variables such as altitude, annual rainfall and soil type can be considered as possible variables to explain growth variation across regions.

• Journal of Forest and Environmental Science
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• v.27 no.1
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• pp.47-54
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• 2011

Allometry and basal area equations were developed with various tree measurement variables for the major species; Quercus variabilis, Quercus mongolica, Pinus koraiensis and Larix leptolepis in Korea. For allometry models, the relationships between total height-DBH, crown width-DBH, height to the widest portion of the crown-total height, and height to base of crown-total height were investigated. Multiple regression methods were used to relate annual basal area growth to tree variables of initial size (DBH, total height, and crown width), relative size (relative diameter and relative height) as well as competition measures (competition index, crown class, and live crown ratio).

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.373-379
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• 2019

Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.

• Journal of Forest and Environmental Science
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• v.28 no.2
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• pp.63-67
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• 2012

Crown ratio is the ratio of live crown length to tree height. It is often used as an important predictor variable for tree growth equation. It indicates tree vigor and is a useful parameter in forest health assessment. The objective of the study was to develop crown ratio prediction models for Tectona grandis. Based on the data set from the temporary sample plots, several non linear equations including logistics, Chapman Richard and exponential functions were tested. These functions were evaluated in terms of coefficient of determination ($R^2$) and standard error of the estimate (SEE). The significance of the estimated parameters was also verified. Plot of residuals against estimated crown ratios were observed. Although the logistic model had the highest $R^2$ and the least SEE, Chapman-Richard and Exponential functions were observed to be more consistent in their predictive ability; and were therefore recommended for predicting crown ratio in the stand.

• The Korean Journal of Quaternary Research
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• v.14 no.1
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• pp.57-63
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• 2000

A simulation model was used to examine the effects of climate variation on the tree-ring structure of Larix leptolepis trees growing at a plantation plot in Worak National Park in central Korea. The model uses mathematical equations to simulate processes affecting cell(tracheid) size variations for individual rings using daily precipitation and temperature measurements. Limiting conditions are estimated from temperature, day length and a calculated water balance. The results indicate that the seasonal growth is mostly limited by the soil moisture content and precipitation income during April and May. The April-May temperature also inversely influences the growth by increasing water losses from soil. The global climate-change scenario which includes regional warming(increasing temperature in spring-summer periods) appears to decrease the duration of optimal growths. Consequently, the model estimated that Larix leptolepis would lose the total production of xylem by 25%.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.351-356
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• 2009

This study purposed to judge potential possibility of building highly precise empirical model using environmental variables. Environmental variables such as altitude, mean annual rainfall, mean annual temperature and organic matter ratio of soil were added to height and diameter model for Chamaecyparis obtusa, and examined accuracy and residuals of prediction model. Improvement in precision was found for the Gompertz polymorphic height model by including mean temperature and altitude as independent variables, while the Gompertz diameter model with annual rainfall and altitude was showed improvement of precision and accuracy. Comparing the improvement of precision between the model before adding environmental variables and the model after adding them, an improvement or some ratio was obtained though it is not obvious. Therefore, there is enough proof that adding environmental variables, which can be easily acquired relatively when considering the difficulties of measurement and budget, into the model as independent variables would improve the accuracy and precision of growth models.

• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.9-15
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• 2010

This study was conducted to develop a stand growth model and a stand yield table for Eucalyptus pellita and Acacia mangium plantations in Kalimantan, Indonesia. To develop a stand growth model, Weibull robability density function, a diameter class model, was applied in this study. In the development of stand growth model by site index and stand age, a hierarchy is generally required - estimation, recovery and prediction of the diameter class model. A number of grow equations were also involved in each process to estimate diameter, height, basal area, minimum or maximum diameter. To examine whether the grow equations are adequate for Eucalyptus pellita or Acacia mangium plantations, a fitness index was analyzed for each equation. The results showed that fitness indices were ranged from 65 to 89% for Eucalyptus pellita plantations and from 72 to 95% for Acacia mangium plantations. As being highly adequate for the plantations, a stand yield table was developed based on the resulted growth model, and applied to estimate the stand growth with midium site index for 10-year period. The highest annual stand growth of Eucalyptus pellita plantations was estimated to be 21.25 $m^3$/ha, while that of Acacia mangium plantations was 27.5 $m^3$/ha. In terms of annual stand growth, Acacia mangium plantations appeared to be more beneficial than Eucalyptus pellita plantations. Also, to estimate commercial timber volume available from the plantations, an assumption that a log would be cut by 2.7 m in length and the rest of the log would be cut by 1.5m was involved. The commercial timber volume available from Eucalyptus pellita plantations was 68.0 $m^3$/ha, 33% from the total stand volume, 203.2 $m^3$/ha. Also 96.7 $m^3$/ha of commercial timbers were available from Acacia mangium plantations, which was 42% from the 232.9 $m^3$/ha in total. Presenting a good information about the stand growth in Eucalyptus pellita and Acacia mangium plantations, this study might be useful for whom proceeds or considers an abroad plantation for merchantable timber production or carbon credit in tropical regions.

• Journal of Korean Society of Forest Science
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• v.57 no.1
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• pp.1-7
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• 1982

The simple logistic growth model on the logistic curve, being originally a kind of population growth curve has also been sometimes utilized to describe growth curves in herbaceous plants such as duckweed and sun-flowers. It has already been recognized that the agreement between the theoretical calculations and the empirical observations is quite satisfactory form a practical point of view. It remains, however, still doubtful whether the logistic curve could be applied to the growth or ordinary woody plants which is quite different in its character from that of herbaceous plants. In this study, the simple logistic model, being a basic tool of stand density management, is applied to yield data from pine stands in order to test the adequacy of the model An attempt of testing the significance of the fit is made by applying the Chi-square test.

• 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.