• Title/Summary/Keyword: Green Coverage Area

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A Study on the Calculation Methods on the Ratio of Green Coverage Using Satellite Images and Land Cover Maps (위성영상과 토지피복도를 활용한 녹피율 산정방법 연구)

  • Moon, Chang-Soon;Shim, Joon-Young;Kim, Sang-Bum;Lee, Shi-Young
    • Journal of Korean Society of Rural Planning
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    • v.16 no.4
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    • pp.53-60
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    • 2010
  • This study aims at suggesting the attributes and limitations of each methods through the evaluation of the verified analysis results, so that it will be possible to select an efficient method that may be applied to assess the green coverage ratio. Green coverage areas of each sites subject to this study were assessed utilizing the following four methods. First, assessment of green coverage area through direct planimetry of satellite images. Second, assessment of green coverage area using land cover map. Third, assessment of green coverage area utilizing the band value in satellite images. Forth, assessment of green coverage area using and land cover map and reference materials. For this study, four urban zones of the City of Seosan in Chungcheongnam-do. As a result, this study show that the best calculation method is the one that combines the merits of first and second methods. This method is expected to be suitable for application in research sites of middle size and above. It is also deemed that it will be possible to apply this method in researches of wide area, such as setting up master plans for parks and green zones established by each local self-government organizations.

Derivation of Green Coverage Ratio Based on Deep Learning Using MAV and UAV Aerial Images (유·무인 항공영상을 이용한 심층학습 기반 녹피율 산정)

  • Han, Seungyeon;Lee, Impyeong
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1757-1766
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    • 2021
  • The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

Comparative Study of Maximum Temperature Condition in Green Space (녹지 조건에 따른 최고기온의 비교연구)

  • 윤용한
    • Asian Journal of Turfgrass Science
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    • v.15 no.4
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    • pp.181-186
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    • 2001
  • In this study, we observed air temperature to make clear that land coverage condition and forest form has a certain relationship to air temperature in a day in various green space. And with revolution analysis, interpreted relationship of air temperature distribution in the green space, of land coverage rate and air temperature, of volume of tree and temperature. With this experimental result, propose green plan, taking into consideration lower effect of air temperature. In this result lower zone is formed in forest and water area, higher zone is done in paved surface and barren ground. And arbor+subarbor area, water area sur-rounded forest and small river is formed relative lower air temperature. In my opinion to promote efficiency lower air temperature area, it is need to make water area surrounded forest, to make forest form lower air temperature 2∼3 layer forest. Lower air temperature effect is in order of arbor, subarbor, shrub and is proportioned increasing of tree.

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Air Temperature Variation by Effect of Green Space Condition (녹지 조건에 따른 기온변화)

  • Yoon, Yong-Han
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.6 no.1
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    • pp.28-33
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    • 2003
  • In this study, we observed air temperature to make clear that land coverage condition and stand form has a certain relationship to air temperature during the night in various green space. And with revolution analysis, we interpreted relationship of air temperature distribution in the green space, The way of analysis is this land coverage rate and air temperature, of number of tree volume of tree air temperature. With this experimental result, we can propose green plan, which is taking into consideration lower effect of air temperature. In this result, lower zone is formed in forest and water area, higher zone is formed in paved surface and barren ground. but this gap is a little. arbor+subarbor area, in the point of water area surrounded stand is formed relative lower air temperature. As a result to make up efficiency lower air temperature area, it is needed to make water area which has surrounded forest, and it is needed to make stand form lower air temperature 2~3 layer forest. In order of arbor, subarbor, shrub, the lower air temperature is more effect.

Factors Affecting Temperature of Urban Parks (도시공원의 기온에 영향을 미치는 요인)

  • 윤용한;송태갑
    • Journal of the Korean Institute of Landscape Architecture
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    • v.28 no.2
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    • pp.39-48
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    • 2000
  • The purpose of this study is to investigate the factors affecting temperature of urban parks to grasp the relationship between the land coverage in open space as well as the forest condition and decreasing city temperature by difference of purposed are. Futhermore, this research interpreted the relationship between wind direction, air temperature, the land coverage of the green space, the number of tree, green volume, height of tree and the mitigation of city temperature with the revolution analysis. The result of this study is that cool air in open space move leeward and decreasing city temperature is influenced by the difference of the land coverage in open space. Specifically, in order of the arbo $r_{-a}$rbor in the forest zone, the increase of the number of trees was related with temperature surrounding significantly. This study found that the use possibility of the green volume was recognized as the index of the green volume relative to air temperature surrounding. Green space of the city control area is more effective decreasing temperature than that of housing zone.

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Application of Multi-satellite Sensors to Estimate the Green-tide Area (황해 부유 녹조 면적 산출을 위한 멀티 위성센서 활용)

  • Kim, Keunyong;Shin, Jisun;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.34 no.2_2
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    • pp.339-349
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    • 2018
  • The massive green tide occurred every summer in the Yellow Sea since 2008, and many studies are being actively conducted to estimate the coverage of green tide through analysis of satellite imagery. However, there is no satellite images selection criterion for accurate coverage calculation of green tide. Therefore, this study aimed to find a suitable satellite image from for the comparison of the green tide coverage according to the spatial resolution of satellite image. In this study, Landsat ETM+, MODIS and GOCI images were used to coverage estimation and its spatial resolution is 30, 250 and 500 m, respectively. Green tide pixels were classified based on the NDVI algorithm, the difference of the green tide coverage was compared with threshold value. In addition, we estimate the proportion of the green tide in one pixel through the Linear Spectral Unmixing (LSU) method, and the effect of the difference of green tide ratio on the coverage calculation were evaluated. The result of green tide coverage from the calculation of the NDVI value, coverage of green tide usually overestimate with decreasing spatial resolution, maximum difference shows 1.5 times. In addition, most of the pixels were included in the group with less than 0.1 (10%) LSU value, and above 0.5 (50%) LSU value accounted for about 2% in all of three images. Even though classified as green tide from the NDVI result, it is considered to be overestimated because it is regarded as the same coverage even if green tide is not 100% filled in one pixel. Mixed-pixel problem seems to be more severe with spatial resolution decreases.

A Study on Temperature Change Profiles by Land Use and Land Cover Changes of Paddy Fields in Metropolitan Areas (대도시 외곽지역 논경작지의 토지이용 및 피복변화에 따른 온도 변화모형 연구)

  • Ki, Kyong-Seok;Lee, Kyong-Jae
    • Journal of the Korean Institute of Landscape Architecture
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    • v.37 no.1
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    • pp.18-27
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    • 2009
  • The purpose of this study is to understand the scale of temperature change following large-scale urban developments in paddy fields to present possible measures to preserve suburban area paddy fields and to lower the scale of temperature increase after developing paddy fields in urban areas. The study was conducted in Bupyeong and Bucheon of Incheon Metropolitan City. The satellite image($1989{\sim}2000$) before and after the development of old paddy fields were used to analyze the land surface temperature changes according to the land use types. Building coverage, green coverage, non-permeable pavement coverage, and floor area ratio(FAR) were selected as the factors that influence urban temperature changes and the temperature estimation model was constructed by using correlation and regression analyses. The before and after satellite images of Bupyeong and Bucheon were classified into forests, greens and plantations, paddy fields, unused lands, and urban areas. The results indicate that most of the paddy fields that existed in the center of Bupyeong and Bucheon were converted into unused lands which were undergoing construction to become new urban areas. The difference between the surface temperatures of May 17th, 1989 and May 7th, 2000 was analyzed to reveal that most land converted from paddy fields to unused lands or urban areas saw an increase in surface temperature. Han River was used as a comparison to analyze the average surface temperature changes($1989{\sim}2000$) in former paddy fields. The scale of temperature changes were: $+1.6697^{\circ}C$ in urban parks; $+2.5503^{\circ}C$ in residential zones; $+2.9479^{\circ}C$ on public lands, $+3.0385^{\circ}C$ in commercial zones, and $+3.1803^{\circ}C$ in educational zones. The correlation between building coverage, green coverage, non-permeable pavement coverage, or floor area ratio(FAR) and surface temperature increases was also analyzed. The green coverage to temperature increases, but building coverage, non-permeable pavement coverage, and floor area ratio(FAR) had no statistically significant temperature increases. The factors that influence urban temperature changes were set up as independent variables and the surface temperature changes as dependent variables to construct a surface temperature change model for the land use types of former paddy fields. As a result of regression analysis, green coverage was selected as the most significant independent variable. According to regression analysis, if farmland is converted into an urban area, a temperature increase of $+3.889^{\circ}C$ is anticipated with 0% green coverage. The temperature saw a decrease of $-0.43^{\circ}C$ with every 10% increase of green coverage.

A Study of Factors Influencing of Temperature according to the Land Cover and Planting Structure in the City Park - A Case Study of Central Park in Bundang-gu, Seongnam - (도시공원의 토지피복 및 식재구조에 따른 온도 영향요인 규명 연구 - 성남시 분당구 중앙공원을 사례로 -)

  • Ki, Kyong-Seok;Han, Bong-Ho;Hur, Ji-Yeon
    • Korean Journal of Environment and Ecology
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    • v.26 no.5
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    • pp.801-811
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    • 2012
  • The purpose of this study is to find out how land cover and planting of an urban park influence temperature. Field research on the land cover and planting status was conducted for Bundang Central Park in Sungnam-si. 30 study plots in the site were selected to closely analyze land cover type and planting structure. The temperature was measured 10 times for each plot. Land coverage type, planting type, planting layer structure and green space area (the ratio of green coverage, GVZ) were chosen as factors impacting temperature and statistics were analyzed for the actual temperature measured. Analysis on how the land coverage type influences temperature showed that planting site had a low temperature and that grassland and paved land had a high temperature. When it comes to planting type, the temperature at the land planted with conifers and broad-leaved trees was low, while the temperature at grassland and paved land was high. With regard to planting layer structure, canopy and canopy-underplanting type showed low temperature, while grassland and paved land showed high temperature. An analysis on the relation between green space area and temperature found out that both ratio of green coverage and GVZ had a high level of negative correlation with the temperature measured. According to regression model of green space area and the temperature measured, for every 1% increase in the ratio of green coverage, temperature is expected to lower by $0.002^{\circ}C$. Also, for every $1m^3/m^2$ increase in GVZ, temperature is expected to go down by $0.122^{\circ}C$.

Humidity Variation by Green Space Calculation Method (녹지의 산출방법이 습도변화에 미치는 영향)

  • Yoon, Yong-Han;Park, Heon
    • Asian Journal of Turfgrass Science
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    • v.16 no.1
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    • pp.41-47
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    • 2002
  • For this study grasp quantitative humidity variation with planting stratification to various green space of calculation method, observed humidity distribution in the green space. with this data, coverage condition and humidity distribution, planting calculation method and humidity, planting stratification calculation method and humidity, analyzed by revolution analysis. In this result, as well as coverage condition, planting stratification effect humidity variation. increasing planting ratio (area) and planting volume (capacity) effect higher humidity. especially, if we compared between planting stratification calculation method and higher humidity, effect by a revolution coefficient and a correlation coefficient, effect relatively planting volume (capacity) higher than stratification ratio (area). today, in the index of higher humidity, planting calculation propose application of capacity method.

Forest Stratification Effect of Air Temperature and Humidity in the Green Space (수림의 계층구조가 녹지내의 기온 및 습도에 미치는 영향)

  • Yoon, Yong-Han
    • Korean Journal of Environmental Biology
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    • v.21 no.2
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    • pp.120-125
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    • 2003
  • For this study grasp coverage condition and forest stratification to various green space, observed air temperature and relative humidity. With this data, coverage condition and air temperature, relative humidity distribution, analyzed relationship of forest rate and air temperature or relative humidity, tree numbers and green volume and humidity by revolution analysis. In this result, higher none is formed artificiality and barren area, lower zone did fores and water area. Relative humidity have corresponding type of air temperature distribution. lower Tone was higher humidity. Different of Idlest type or water area, surround of forest showed relatively higher humidity. Increasing tree numbers or green volume effect higher humidity and this efficiency order of an arbor, subarbor, shrub.