• 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.

• 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.

• Korean Journal of Environmental Biology
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• v.20 no.1
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• pp.10-19
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• 2002

In order to investigate relation between park scale and temperature decrease in and near parks, temperature distribution was observed and was analyzed in four parks of different scales. Relation between the temperature decrease and ratio of green coverage was also analyzed by using regression analysis. Lower temperature was observed in and near the parks and larger cooling effect was implicated near the larger parks. The result of regression analysis showed that the increase of green coverage ratio lends the decrease of the temperature in the parks. The degree of the temperature decrease varied according to the types of the coverage.

• 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 $0.122^{\circ}C$.

• Journal of Environmental Science International
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• v.19 no.9
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• pp.1137-1142
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• 2010

This study proposes a guideline of a green roof system suitable for the local environment by verifying the growth of Zoysia japonica in a shallow, extensive, green roof system under rainfed condition. The experimental soil substrates into which excellent drought tolerance and creeping Z. japonica was planted were made with different soil thicknesses(15cm, 25cm) and soil mixing ratios(SL, $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$, $P_4P_4L_2$). The plant height, green coverage ratio, fresh weight, dry weight and chlorophyll contents of Z. japonica were investigated. For the soil thickness of 15cm, the plant height of Z. japonica was significantly as affected by the soil mixing ratio and it was shown in the order SL= $P_4P_4L_2$ < $P_7P_1L_2$ = $P_5P_3L_2$ < $P_6P_2L_2$. For the soil thickness of 25cm, the plant height was increased in order to SL < $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$ < $P_4P_4L_2$. The green coverage ratio was not observed by soil the mixing ratio or soil thickness. However, the green coverage ratio was 86~90% with a good coverage rate overall. The chlorophyll contents of Z. japonica were not significantly affected by the soil mixing ratio in the soil thickness of 15cm, but were higher in the natural soil than in the artificial soil at 25cm soil thickness. The fresh weight and dry weight of Zoysia japonica were heavier in the 25cm thickness than in the 15cm thickness and in the artificial soil mixture than in the natural soil. The result indicated that the growth of Zoysia japonica was more effective in the 25cm soil thickness with artificial soil than in the 15cm soil thickness with natural soil in the green roof system under rainfed condition.

• 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.

• 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.

• 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.

• Korean Journal of Environmental Biology
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• v.22 no.2
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• pp.279-286
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• 2004

This study observed the temperature and humidity within the green zone to understand the effect that land coverage and the structure of forests have on the relief of micro-climate control. Based on this set of data, this study interpreted, through the regression analysis, the relevance of land coverage of the green zone with temperature and distribution of humidity, as well as the amount of green with the relief of microclimate control. The results of the study demonstrated that high temperature regions were formed in barren areas, and low temperature regions in forests or near the water. In particular, low temperature was found in areas covered with tall and small trees, the water surrounded by forests and areas enclosing small rivers. Furthermore, mechanisms causing low temperature were, among others, the ratio of land coverage (forest, grassland, water). In fact, the temperature reduction effect varied in accordance with the types and ratios of the land coverage. Humidity also showed a close correlation with the distribution of temperature high temperature areas had low humidity and low temperature areas had high humidity. Such a phenomenon.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.1
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• pp.117-123
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• 2011

This study aims to suggest a suitable soil thickness and soil mixture ratio of a green roof system by verifying the growth of Chrysanthemum zawadskii var. coreanum as affected by different green roof systems using rainwater. The experimental planting grounds were made with different soil thicknesses(15cm, 25cm) and soil mixing ratios (SL, $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$, $P_4P_4L_2$) and with excellent drought tolerance. Ornamental value Chrysanthemum zawadskii var. coreanum was planted. The change in plant height, green coverage ratio, chlorophyll content, fresh weight, dry weight, and dry T/R ratio of Chrysanthemum zawadskii var. coreanum were investigated from April to October 2009. For 15cm soil thickness, the plant height of Chrysanthemum zawadskii var. coreanum was not significantly different as affected by the soil mixing ratio. However, it was found to be higher in the amended soil mixture, $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$ and $P_4P_4L_2$ than in the sandy loam soil, as it was SL overall. For 25cm soil the plant height differences were in order to SL < $P_7P_1L_2$, $P_6P_2L_2$, $P_5P_3L_2$ < $P_4P_4L_2$. The green coverage ratio was observed not to be different by soil mixing ratio with soil thickness of 15cm, but, the lowest green coverage ratio in the SL. In the 25cm soil thickness, the green coverage ratio was 86-89% with a good coverage rate overall. The change in chlorophyll contents with 15cm soil thickness was found to be the highest in the SL treatment and the lowest in the $P_5P_3L_2$ treatment. For 25cm thickness, the highest value was in the $P_4P_4L_2$ and SL, and the lowest in the$P_7P_1L_2$. Fresh weight and dry weight were larger in soil with 25cm thickness. Therefore, the growth of Chrysanthemum zawadskii var. coreanum as affected by a different green roof system for using rainwater was higher in soil with 25cm thickness than 15cm, and in PPL amended soil than in sandy loam.