• 한국조경학회지
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• 제44권1호
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• pp.93-106
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• 2016

이 연구는 제안한 평균복사온도의 차감비교기법을 통해 도시림이 여름철 옥외 환경에 미치는 온열완화를 정량적으로 추정하고 평가는 것을 목적으로 한다. 항공 라이다 측량시스템 기반 3차원 점군자료로부터 도시림이 있는 모의 대상지와 도시림이 없는 모의 대상지 두 사례를 구축하여 SOLWEIG 기반에서 평균복사온도를 산출하고 두 값들을 비교 및 분석하였다. 연구를 통해 도시림 캐노피가 연구지역 전체 일평균 $T_{mrt}$를 약 $5^{\circ}C$ 정도 저감하며 태양의 위치와 지면 조건에 따라 시간평균 $T_{mrt}$가 $33^{\circ}C$까지 저감될 수 있음을 확인하였다. 결과들은 도시미기후 지표(풍속, 습도, 대기 온도 등) 및 생명기상(인지온도 등) 연구들을 향상시키고 더불어 삼림 기반 공공 녹색정책 개발에 활용될 수 있을 것이다.

• Journal of Forest and Environmental Science
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• 제35권4호
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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.

• 한국조경학회지
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• 제31권2호
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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.

• 농촌지도와개발
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• 제19권3호
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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.

• 한국환경복원기술학회지
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• 제22권3호
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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.

• 대한원격탐사학회지
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• 제38권6_2호
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• pp.1633-1641
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• 2022

도시의 인구 집중과 무분별한 개발은 대기오염, 열섬현상과 같은 다양한 환경 문제들을 유발하며, 자연재해로 인한 피해 상황을 악화시키는 등 인재의 원인이 되고 있다. 도심 수목은 이러한 도시 문제들의 해결방안으로 제시되어왔으며, 실제로 환경 개선 기능을 제공하는 등 중요한 역할들을 수행한다. 이에 따라 수목이 도시 환경에 미치는 영향을 파악하기 위해 도심 수목에서 개별목에 대한 정량적인 측정 및 분석이 요구된다. 그러나 도심 수목의 복잡성 및 다양성은 단일 수목 탐지 정확도를 낮추는 문제점이 존재한다. 따라서 본 연구는 수목 개체에 대해 효과적인 탐지가 가능한 고해상도 항공영상 및 object detection에서 뛰어난 성능을 발휘한 You Only Look Once Version 5 (YOLOv5) 모델을 사용하여 도심 수목을 효과적으로 탐지하는 연구를 진행하였다. 수목 AI 학습 데이터셋의 구축을 위한 라벨링 가이드라인을 생성하고 이를 기준으로 동작구 수목에 대해 box annotation을 수행하였다. 구축된 데이터셋으로부터 다양한 scale의 YOLOv5 모델들을 테스트하고 최적의 모델을 채택하여 효율적인 도심 수목 탐지를 수행한 결과, mean Average Precision (mAP) 0.663의 유의미한 결과를 도출하였다.

• KIEAE Journal
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• 제14권2호
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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.

• 대한공간정보학회지
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• 제5권2호
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• pp.45-54
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• 1997

도시녹지공간의 수목은 체계적이고, 신속한 관리를 함으로써 인간에게 더 많은 혜택을 부여한다. 현재 도시 녹지공간에 있어서의 수목관리의 방법론적인 방안을 고려해 볼 때 수목관리의 유지관리를 위한 자료의 수집과 처리, 첨단 System을 활용한 관리체계가 극히 미흡한 실정이다. 이를 위해서는 먼저 녹지자원 관리를 위한 효율적이고 체계적인 자료의 수집 및 처리와 합리적인 분석과정이 필요하며 그 다음으로 이러한 자료를 토대로 하여 적절한 도시녹지공간에 있어서의 수목관리를 효율적으로 처리할 수 있는 시스템과 그 활용이 필요하다. 이러한 시스템으로 본 연구에서는 최근 여러 분야에서 이용되고 있는 GIS을 이용하여 도시녹지관리모델을 제시하고 이를 통하여 그 효율성을 극대화하였다.

• 한국조경학회지
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• 제34권5호
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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: $$1nY=3.3233-0.0018X_1\;(r^2=0.99,\;p<0.0001)\;Y=27.5297-0.0019X_2\;(r^2=0.96,\;p=0.0007)$$

• 대한원격탐사학회지
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• 제21권5호
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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.