• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.93-106
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• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of Forest and Environmental Science
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• v.35 no.4
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• pp.240-247
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• 2019

This study quantified carbon reduction services through direct harvesting of Ilex rotunda and Machilus thunbergii, which are the typical urban landscape tree species in southern Korea. A total of 20 open-grown tree specimens (10 specimens for each species) were selected reflecting various sizes of stem diameter at breast height of 1.2 m (DBH) at a regular interval. The study measured biomass for each part of the tree specimens including roots to compute total carbon storage per tree. Annual carbon uptake per tree was also calculated analyzing the DBH growth rate of stem disk specimens. Quantitative models were developed using DBH as an independent variable to easily estimate storage and annual uptake of carbon by tree growth for each species. All the models had a high goodness-of-fit with R²=0.95-0.99. The difference in carbon reduction services between DBH sizes increased with increasing DBH. The storage and annual uptake of carbon from a tree with DBH of 10 cm were 13.5 kg and 2.4 kg/yr for I. rotunda, and 19.1 kg and 3.6 kg/yr for M. thunbergii, respectively. The tree of this size stored the amount of carbon equivalent to that emitted from a gasoline use of approximately 24 L for I. rotunda and 34 L for M. thunbergii, respectively. The study provides actual measurement data to quantify carbon reduction services of urban open-grown landscape trees for the warm-temperate species that have been little known until now.

• Journal of the Korean Institute of Landscape Architecture
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• v.31 no.2
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• pp.48-57
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• 2003

The objective of this study is to review and verify whether the functions and effect of roadside trees generally hewn in theory are actually realized in urban roads and how well they are performed if the function and effect are realized. The study was conducted with a focus on 3 functions and effects including roadside tree's urban landscape improvement function (green area visibility ratio), effect of introducing green area within a city, and urban green network building function. The major study results are as follows: First, the average green area visibility ratio of 41 study areas is currently about 25.90%. The green area visibility ratio of commercial area within downtown was lowest among 5 road types. It showed that it is possible to raise the average green area visibility ratio up to 32.49% through roadside tree management and additional plantation. Second, in a section between Paldal Mountain and Suwon City Hall where there is no forest fragments and parks at all, a green area of 4,826 roadside trees represented 2.4% of total area and served as the only linear green area. Third, an analysis of 15 cities in Kyonggi province showed that urban forests are concentrated in outskirts. The suey showed that because forest fragments and parks exist in a form of points in urban areas, roadside trees are the only green areas that link each other and build a network.

• Journal of Agricultural Extension & Community Development
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• v.19 no.3
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• pp.617-647
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• 2012

The purpose of this study was to identify the predictors of suicidal ideation of rural residents. This study was based on predictors of suicidal ideation of urban residents. The participants were adolescents, adults, and seniors sampled from 10 provinces all over the country, from May to Aug, 2010. The data for the study were analysed as decision tree analysis. The major results of the study were as follows. First, a main predictor of suicidal ideation for rural residents was high depression. Unlike rural residents, urban residents reporting high depression and influence of mass media showed high suicidal ideation. Second, interaction of depression and family solidarity was important predictor of suicide ideation both rural and urban residents, but a condition that effects the situation differed between rural and urban residents. Rural residents reporting high depression and high family solidarity showed high suicidal ideation, urban residents reporting low depression and high family solidarity showed low suicidal ideation. Stress was also operate differently. Rural residents reporting moderate depression, low family solidarity and high stress showed high suicidal ideation, but stress of urban resident was not a important predictors of suicidal ideation. And rural residents reporting low depression and low stress showed the lowest level of suicidal ideation, urban residents reporting low family solidarity and low depression showed the lowest level of suicidal ideation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.3
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• pp.55-71
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• 2019

The purpose of this study is to propose an evaluation method to assess green environments of streetscapes to improve urban street green spaces in Jeonju City. Through a rapid assessment of urban street green spaces, we suggest an objective basis for expanding street green space as well as for adopting sustainable maintenance and improvement measures. We choose 12 sections of streetscapes (roads and sidewalks) to investigate existing street conditions which have more than four lanes and function as major road axes. Six large roads and six medium roads of Jeonju City center area are investigated as pilot assessment study sites. Site inventory checklists consist of environmental characteristics of streetscape, street tree status, and planting condition evaluation. Environmental characteristics of streetscapes are composed of physical and neighborhood factors. For instance, items for physical factors are types and width of road/sidewalks, paving materials, tree protection materials, and green strip. And surrounding landuse is a neighborhood factor. Assessment items for street tree status are street plant names (tree/shrubs/ground cover), size, and planting intervals. Planting condition evaluation items are tree shape, damage, canopy density, and planting types with existence of adjacent green space. Evaluation results are classified into three levels such as A(maintain or repair), B(greening enhancement), and C(structural improvement). In case of grade A, streetscapes have enough sidewalk width for maintaining green strip and a multi-layered planting(in large road only) with fairly good growing conditions of street trees. For grade B and C, streetscapes have a moderate level of sidewalk width with a single street tree planting. In addition, street tree growing conditions are appeared poor so that green enhancement or maintenance measures are needed. For median, only grade B and C are found as its planting growing foundations are very limited in space. As a result, acquiring enough sidewalk space is essential to enhance ecological quality of urban street green. Especially, it is necessary to have green strip with reasonable widths for plant growing conditions in sidewalks. In addition, we need to consider native species with multi-layer plant compositions while designing street green.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1633-1641
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• 2022

Urban population concentration and indiscriminate development are causing various environmental problems such as air pollution and heat island phenomena, and causing human resources to deteriorate the damage caused by natural disasters. Urban trees have been proposed as a solution to these urban problems, and actually play an important role, such as providing environmental improvement functions. Accordingly, quantitative measurement and analysis of individual trees in urban trees are required to understand the effect of trees on the urban environment. However, the complexity and diversity of urban trees have a problem of lowering the accuracy of single tree detection. Therefore, we conducted a study to effectively detect trees in Dongjak-gu using high-resolution aerial images that enable effective detection of tree objects and You Only Look Once Version 5 (YOLOv5), which showed excellent performance in object detection. Labeling guidelines for the construction of tree AI learning datasets were generated, and box annotation was performed on Dongjak-gu trees based on this. We tested various scale YOLOv5 models from the constructed dataset and adopted the optimal model to perform more efficient urban tree detection, resulting in significant results of mean Average Precision (mAP) 0.663.

• KIEAE Journal
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• v.14 no.2
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• pp.87-98
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• 2014

This study is to identify quantitatively the function of carbon dioxide emissions reduction due to temperature and energy reduction according to direct carbon dioxide storage, shade provision, and evaportanspiration of urban park. According to the result of study, landscape tree indicated high carbon dioxide storage effect compare to bush, in which broadleaf tree indicated higher storage function than coniferous tree. It is believed to be the storage of carbon dioxide can be increased by increasing the composition rate of forest plants in the urban park. According to the direct estimation result of carbon dioxide storage in terms of example area, storage of carbon dioxide is estimated to be "seoul a zone" $476,818.8kg{\cdot}CO_2/m^2yr$, "anyang b zone" $186,435.7{\cdot}CO_2/m^2yr$, "daejeon c zone" $262,826{\cdot}CO_2/m^2yr$, "kwangju d zone" $231,657.8{\cdot}CO_2/m^2yr$. The carbon dioxide storage per unit area estimated to be "seoul a zone" $3.4{\cdot}CO_2/m^2yr$, "anyang b zone" $5.0{\cdot}CO_2/m^2yr$, "daejeon c zone" $2.6{\cdot}CO_2/m^2yr$, "kwangju d zone" $5.6{\cdot}CO_2/m^2yr$. The result of indirect carbon dioxide reduction effect estimated to be "seoul a zone" $291,603.4{\cdot}CO_2/m^2yr$, "anyang b zone" $165,462.4{\cdot}CO_2/m^2yr$, "daejeon c zone" $141,719.2{\cdot}CO_2/m^2yr$, "kwangju d zone" $154,803.4{\cdot}CO_2/m^2yr$. Carbon dioxide reduction potential amount through the urban park was increased to 1.6 times to 1.8 times when calculated to the indirect effect.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.45-54
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• 1997

A mathodology to manage effectively urban open space using GIS(Geographic Information System) was developed to explore the methology of efficient urban open space management focusing on landscaped trees. Cartographic modeling technique was used for practical use of GIS as a case study of the Childeren's park in Kwangju city. First, spatial and attribute information for efficient landscaped tree management was acqired through the development of a tree management cartographic model. Second the information of location and the attribute of individual trees can be applied as a means of decision making in tree management. Thira optimal path of tree management and priority of management in work process of the selected urban open space could be determined according to the objective of park management.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.5 s.118
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• pp.70-75
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• 2006

The purpose of this study is to explore the effects of difference in urban tree plantings on microclimate amelioration, and to suggest essential information for quantifying urban energy budgets and energy savings. This study was focused on measuring and analyzing air temperature and relative humidity in summer. Daytime air temperatures at places with 8%, 24%, 44%, 79%, and 100% cover of woody plants were, respectively, $0.6^{\circ}C,\;1.3^{\circ}C,\;2.4^{\circ}C,\;3.5^{\circ}C,\;and\;4.8^{\circ}C$ cooler, compared to a place with 0% cover. A 10% increase of woody plant cover was estimated to reduce the temperature by approximately $0.55^{\circ}C$. The temperature reduction effects were relatively greater between places with lower cover of woody plants than between those with higher cover. Woody plant cover and crown volume were the appropriate indicators which quantified the effects of tree plantings on air temperatures, based on the correlation analysis. Regression equations to estimate temperature change ($Y:^{\circ}C$) using woody plant cover ($X_1:%$) or crown volume ($X_2:m^3$) as independent variables are as follows: $$1nY=3.3233-0.0018X_1\;(r^2=0.99,\;p<0.0001)\;Y=27.5297-0.0019X_2\;(r^2=0.96,\;p=0.0007)$$

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.