• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.3
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• pp.207-216
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• 2010

Individual differences of ozone ($O_3$) resistance for seed production, seed germination and seedling development were examined in this study. Five in each healthy and damaged trees of Pinus thunbergii growing in air polluted area for 12 years were chosen based on visible foliar injury and growth. The cones of P. thunbergii, which were collected from healthy and damaged trees, were analyzed for physical characteristics and seeds from the cones were used to test germination percentage under $O_3$ treatment. The germinated seeds were continuously exposed to $O_3$ treatment and the lipid peroxidation and activities of antioxidative enzymes were determined for both seeds and seedlings. The $O_3$ treatment for seed germination and seedling development were conducted at three conditions: control, 150 ppb and 300 ppb of $O_3$. The non-treated seeds from the damaged trees showed 21.6% lower germination than those from the healthy ones. On the $O_3$ treatment of 300 ppb, seed germination decreased approximately 10% for the healthy trees and 19% for the damaged trees compared to that on the control. The seeds from the healthy trees showed significantly higher activities of superoxide dismutase (SOD), glutathione reductase (GR), and catalase (CAT) than those from the damaged trees. The activities of GR, ascorbate peroxidase (APX), and CAT decreased along with the increasing $O_3$ concentration in two tree grades. Malondialdehyde (MDA) content of seeds was not influenced by $O_3$ treatment for two tree grades. In seedling development, there were no significant differences for length and biomass of needle and root of two tree grades at both the control and 150 ppb of $O_3$. At 300 ppb of $O_3$ treatment, however, the length and biomass of needle and stem decreased for two tree grades but no significant differences was detected in root. The seedlings from the damaged trees were more sensitive to the $O_3$ treatment, showing higher activities of SOD, APX, and CAT and content of MDA compared to those from the healthy tree seedlings. Our results indicate that seed germination and seedling development are vulnerable to increasing $O_3$ concentrations and that attention must be paid to the individual selection of tree species for reforestation.

• Genomics & Informatics
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• v.2 no.3
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• pp.147-148
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• 2004

Recently completed mitochondrial genome databses from public resources provide us with a better understanding of individual mitochondrial genomes for population genomics. By determining the substitution rate of the genomic sequences, it is plausible to derive dates on the phylogenetic tree and build a chronology of events in the evolution of human species. MitGEN is specially designed as a mitochondrial genome browser for analyzing, comparing and visualizing single nucleotide polymorphism for human mitochondrial genomes between human races for comparative genomics. It is a standalone application and is available free for non-commercial work.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1139-1149
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• 2017

Measuring tree's volume is very important input data of various environmental analysis modeling However, It's difficult to use economical and equipment to measure a fragmented small green space in the city. In addition, Trees are sensitive to seasons, so we need new and easier equipment and quantification methods for measuring trees than lidar for high frequency monitoring. In particular, the tree's size in a city affect management costs, ecosystem services, safety, and so need to be managed and informed on the individual tree-based. In this study, we aim to acquire image data with UAV(Unmanned Aerial Vehicle), which can be operated at low cost and frequently, and quickly and easily quantify a single tree using SfM-MVS(Structure from Motion-Multi View Stereo), and we evaluate the impact of reducing number of images on the point density of point clouds generated from SfM-MVS and the quantification of single trees. Also, We used the Watertight model to estimate the volume of a single tree and to shape it into a 3D structure and compare it with the quantification results of 3 different type of 3D models. The results of the analysis show that UAV, SfM-MVS and solid model can quantify and shape a single tree with low cost and high time resolution easily. This study is only for a single tree, Therefore, in order to apply it to a larger scale, it is necessary to follow up research to develop it, such as convergence with various spatial information data, improvement of quantification technique and flight plan for enlarging green space.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.1
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• pp.41-49
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• 2014

This study spatially assesses the impact of trees on residential rooftop solar energy potential using urban three-dimensional models derived from Light Detection and Ranging(LiDAR) data in San Francisco, California. In recent years on-site solar energy generation in cities has become an essential agenda in municipal climate action plans. However, it can be limited by neighboring environments such as shade from topography, buildings and trees. Of all these effects, the impact of trees on rooftop photovoltaics(PVs) requires careful attention because improper situation of solar panels without considering trees can result in inefficient solar energy generation, tree removal, and/or increasing building energy demand and urban heat island effect. Using ArcMap 9.3.1, we calculated the incoming annual solar radiation on individual rooftops in San Francisco and the reduced insolation affected by trees. Furthermore, we performed a multiple regression analysis to see what attributes of trees in a neighborhood(tree density, tree heights, and the variance of tree heights) affect rooftop insolation. The result shows that annual total residential rooftops insolation in San Francisco is 18,326,671 MWh and annual total light-loss reduction caused by trees is 326,406 MWh, which is about 1.78%. The annual insolation shows a wide range of values from $34.4kWh/m^2/year$ to $1,348.4kWh/m^2/year$. The result spatially maps the locations that show the various levels of impact from trees. The result from multiple regression shows that tree density, average tree heights and the variation of tree heights in a neighborhood have statistically significant effects on the rooftop solar potential. The results can be linked to municipal energy planning in order to manage potential conflicts as cities with low to medium population density begin implementing on-site solar energy generation. Rooftop solar energy generation makes the best contribution towards achieving sustainability when PVs are optimally located while pursuing the preservation of urban trees.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.167-176
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• 2011

This study's purpose is to analyse factors of determination about detouring for makinga standard model in regard of unfavorableness and uncertainty when unspecified individual recipients make a decision at the time of course detour. In order to achieve this, we surveyed SP investigation whether making a detour or not for drivers as a target who take a high way and National highway. Based on this result, we analysed detour determination factors of drivers, establishing a combination model of Decision Tree and Neural Network model. The result demonstrates the effected factors on drivers' detour determination are in ordering of the recognition of alternative routevs, reliable and frequency of using traffic information, frequency of transition routes and age. Moreover, from the outcome in comparison with an existing model and prediction through undistributed data, the rate of combination model 8.7% illustrates the most predictable way in contrast with logit model 12.8%, and Individual Model of Decision Tree 13.8% which are existed. This reveals that the analysis of drivers' detour determination factors is valid to apply. Hence, overall study considers as a practical foundation to make effective detour strategies for increasing the utility of route networking and dispersion in the volume of traffic from now on.

• Journal of Korean Society of Forest Science
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• v.104 no.4
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• pp.536-542
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• 2015

This study was examined for the growth response of tree diameter and volume to thinning treatments from different thinning intensities using three long-term thinning trials for Japanese Evergreen Oak (Quercus acuta Thunb.) stands in Wando island, Korea. After thinning in 1999, annual tree growth of diameter and volume was highest in heavy thinned stands for individual tree and this growth pattern of thinning response showed similar tendency to the individual tree growth response in light thinned stands. By increasing diameter growth, the value of H/D ratio (HDR) as an indicator of stem form was properly decreased and improved up to 80%. Although there is significant growth response of basal area in both heavily and lightly thinned stands, the growth potential both of heavily and lightly thinned stands in total stand volume is not likely to reach at the level of unthinned stands because of basal area growth loss associated with both light and heavy thinnings.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.431-440
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• 2005

Location, height and clear-length of individual tree can be measured directly by LiDAR Remote Sensing, and dbh(diameter at breast height) can be estimated indirectly by tree height measured by LiDAR. In addition, stand volume and stand biomass are computed from estimated growth factors. In this study, each estimated growth factor was compared to the field measurements to validate accuracy. The coefficient of determination of total tree heights was 0.66 for total trees, 0.68 for Pinus koraiensis, 0.66 for Larix leptolepis and 0.60 for Quercus spp. The coefficient of determination of clear-length was 0.79 for total trees, 0.73 for Pinus koraiensis, 0.79 for Larix leptolepis, 0.68 for Quercus spp. The coefficient of determination of dbh predicted was 0.73 for Pinus koraiensis, 0.73 for Larix leptolepis and 0.85 for Quercus spp. Moreover The coefficient of determination of basal area was 0.82 for Pinus koraiensis, 0.92 for Larix leptolepis and 0.95 for Quercus spp. Biomass per ha computed by growth factor using LiDAR was 40,306 dm/ha for Pinus koraiensis, 94,150 tdm/ha for Larix leptolepis and 94,481 tdm/ha for Quercus spp. by species.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.63-69
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• 2018

This study is to examine the determinants of the elderly poverty by using the Decision-tree analysis. In line with this perspective, this study includes individual characteristics, family characteristics, working characteristics, and periodic income characteristics after retirement as determinants for senior poverty. The study uses data from the Korean Retirement and Income Study based on panel survey and employs the Decision-tree analysis to explain the causes of the elderly poverty. As the result of analysis, earned wage has the greatest effect on the elderly poverty. Depending on status of the earned wage, there are 2 different variable groups. One with no earned wage includes public pension, education, and residence, paid employee and gender in the other with earned wage. Based on the analytical results, the study suggests measures to address the elderly poverty.

• Journal of Korean Society of Forest Science
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• v.71 no.1
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• pp.27-32
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• 1985

Individual tree growth in a given stand is considerably affected by its neighbouring trees or surrounding density. This trend is appeared more clearly in the unthinned stand. Relationship between growth of individual trees and density around them was analyzed by the use of the angle-summation method(AS method), and then multiple regression equation including variables of center trees and measures of surrounding density by the AS method was given for estimating diameter increment for the last five years and the next few years of center trees.

• 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.