• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.19-28
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• 2020

The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.

• Journal of Environmental Impact Assessment
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• v.32 no.3
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• pp.176-186
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• 2023

Urban Heat Island (UHI) is caused by an energy imbalance in urban areas, where building design and land cover contribute to its amplification. To mitigate UHI, increasing green space is one of the well known and the most effective approach. This study aims aimed to identify specific components of green spaces that lower temperatures and demonstrate the cooling effects based on their size and composition. Forests within green spaces have had a greater impact on temperature reduction due to shading and blocking solar radiation. Although lakes also contributed to temperature reduction, the effect to cooling intensity was not significant. The cooling distance does not depended on green space size or composition. The study emphasizes that initial temperature has a strongerinfluence on cooling intensity than green space size, highlighting the importance of vegetation type within green spaces to achieve a cooling effect. These findings provide valuable insights for urban planning and the design of green spaces to mitigate the effects of the urban heat island.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.225-236
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• 2022

Urbanization due to population growth and regional development can cause various environmental problems, such as the urban heat island phenomenon. A planned city is considered an appropriate study site to analyze changes in urban climate caused by rapid urbanization in a short-term period. In this study, changes in land cover and surface heat island phenomenon were analyzed according to the development plan in Sejong City from 2013 to 2020 using Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) satellite imagery. The surface temperature was calculated in consideration of the thermal infrared band value provided by the satellite image and the emissivity, and based on this the surface heat island effect intensity and Urban Thermal Field Variance Index (UTFVI) change analysis were performed. The level-2 land cover map provided by the Ministry of Environment was used to confirm the change in land cover as the development progressed and the difference in the surface heat island intensity by each land cover. As a result of the analysis, it was confirmed that the urbanized area increased by 15% and the vegetation decreased by more than 28%. Expansion and intensification of the heat island phenomenon due to urban development were observed, and it was confirmed that the ecological level of the area where the heat island phenomenon occurred was very low. Therefore, It can suggest the need for a policy to improve the residential environment according to the quantitative change of the thermal environment due to rapid urbanization.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.68-71
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• 2008

Our goal is to obtain a better scientific understanding how to define the nature and role of remotely sensed land surface parameters and energy fluxes in the heat island phenomena, and local and regional weather and climate. By using the MODIS visible and thermal imagery data and analyzing the surface energy flux images associated with the change of the landcover and landuse in study area, we will estimate and present how significant is the magnitude of the heat island heat effect and its relation with the surface parameters and the energy fluxes in Taiwan. To achieve our objective, we used the energy budget components such as net radiation, soil heat flux, sensible heat flux, and latent heat flux in the study area of interest derived form remotely sensed data to understand the island heat effect. The result shows that the water is the most important component to decrease the temperature, and the more the consumed net radiation to latent heat, the lower urban surface temperature.

• KIEAE Journal
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• v.13 no.4
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• pp.33-41
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• 2013

The impervious area on the surface of urban area has been increased as buildings and artificial land cover have continually been increased. Urban development has gradually decreased the green zone in downtown and alienated the city from the natural environment on outskirt area devastating the natural ecosystem. There arise the environmental problems to urban area including urban heat island phenomenon, urban flood, air pollution and urban desertification. As one of urban plans to solve such problems, green roof system is attracting attentions. The purpose of this study was to investigate flood discharge and heat reduction effect according to the green roof system and to quantify effect by analyzing through simulation water and heat cycle before and after green roof system. For the analysis, Distributed hydrologic model, WEP (Water and Energy transfer Processes) and WEP+ model were used. WEP was developed by Dr. Jia, the Public Works Research Institute in Japan (Jia et al., 2005), which can simulate water and heat cycle of an urban area with complex land uses including calculation of spatial and temporal distributions of water and heat cycle components. The WEP+ is a visualization and analysis system for the WEP model developed by Korea Institute of Construction Technology (KICT).

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.134-140
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• 2012

With rapid modernization and industrialization, many urban areas are becoming overcrowded at a rapid pace and such urban ecological problems as heat island effect are becoming serious due to the reduced green zones resulted from the indiscriminate development. To solve this problem, ecological park, constructed wetlands, and greening on the elevation, balcony, and roof of a building that have the structure and function very close to the state of nature are currently being promoted at the urban or regional level. Especially green roof will be able to not only provide the center of a city with a significant portion of green area but also help to relive heat island effect and improve micro climate by preventing concrete of a building from absorbing heat. According to a recent study, the temperature of green roof in the summer season shows a lower temperature than the outdoor temperature, but inversely the concrete surface shows a higher temperature. Accordingly, this study measured the surface temperature of buildings with green roof in Daejeon area in order to determine how the green roof system would have an impact on the distribution of surface temperature and did a comparative analysis of the distribution of the surface temperature of green roof vs non-green roof based on these theoretical considerations. As a result, it was found that the surface temperature of green roof was lower by $4{\sim}7^{\circ}C$ than that of non-green roof. This is expected to contribute to the mitigation of urban heat island effects.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.113-121
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• 2015

Remote sensing technology using a multi-spectral satellite imagery can be utilized for the analysis of urban heat island effect in large area. However, weather condition of Korea mostly has a lot of clouds and it makes periodical observation using time-series of satellite images difficult. For this reason, we proposed the analysis of urban heat island effect using time-series of Landsat TM images and ATC model. To analyze vegetation condition and urbanization, NDVI and NDBI were calculated from Landsat images. In addition, land surface temperature was calculated from thermal infrared images to estimate the parameters of ATC model. Furthermore, the parameters of ATC model were compared based on the land cover map created by Korean Ministry of Environment to analyze urban heat island effect relating to the pattern of land use and land cover. As a result of a correlation analysis between calculated spectral indices and parameters of ATC model, MAST had high correlation with NDVI and NDBI (-0.76 and 0.69, respectively) and YAST also had correlation with NDVI and NDBI (-0.53 and 0.42, respectively). By comparing the parameters of ATC model based on land cover map, urban area had higher MAST and YAST than agricultural land and grassland. In particular, residential areas, industrial areas, commercial areas and transportation facilities showed higher MAST than cultural facilities and public facilities. Moreover, residential areas, industrial areas and commercial areas had higher YAST than the other urban areas.

• Atmosphere
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• v.20 no.1
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• pp.13-26
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• 2010

The Urban Canopy Model (UCM) implemented in WRF model is applied to improve urban meteorological forecast for fine-scale (about 1-km horizontal grid spacing) simulations over the city of Seoul. The results of the surface air temperature and wind speed predicted by WRF-UCM model is compared with those of the standard WRF model. The 2-m air temperature and wind speed of the standard WRF are found to be lower than observation, while the nocturnal urban canopy temperature from the WRF-UCM is superior to the surface air temperature from the standard WRF. Although urban canopy temperature (TC) is found to be lower at industrial sites, TC in high-intensity residential areas compares better with surface observation than 2-m temperature. 10-m wind speed is overestimated in urban area, while urban canopy wind (UC) is weaker than observation by the drag effect of the building. The coupled WRF-UCM represents the increase of urban heat from urban effects such as anthropogenic heat and buildings, etc. The study indicates that the WRF-UCM contributes for the improvement of urban weather forecast such nocturnal heat island, especially when an accurate urban information dataset is provided.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.59-74
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• 2015

The purpose of this study is to analyze reasonable green area ratios for mitigating urban heat island considering various land use types. Land uses of 5 types such as single residential, multi residential, commercial area, public facility, and industrial area were considered. Green areas were extracted from the tree attribution of land cover. Effect of urban heat island was analysed by the surface temperature of ASTER thermal infrared radiance scanned daytime and nighttime. Mitigation effect of green area at daytime was higher than nighttime. Surface temperature of green area was low in single residential at daytime. But the difference of surface temperature by each land use type was small. The effect of surface temperature mitigation of green area was lower in industrial area. The results of reasonable green area ratios for mitigating urban heat island indicate that surface temperature was the lowest with green area ratio of 40~50% in single residential, multi residential, and commercial area at daytime. Surface temperature of nighttime was not changed much by green area ratios. Therefore, the results of this study will be suggested in urban development planning to construct effectively green area for mitigating urban heat island.