• 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.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.821-834
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• 2017

The increase in the rate of industrialization due to urbanization has caused the Urban Heat Island phenomenon where the temperature of the city is higher than the surrounding area, and its intensity is increasing with climate change. Among the cities where heat island phenomenon occurs, Seoul city has different degree of urbanization, green area ratio, energy consumption, and population density in each administrative district, and as a result, the strength of heat island is also different. So It is necessary to analyze the difference of Urban Heat Island Intensity by administrative district and the cause. In this study, the UHI intensity of the administrative gu and the administrative dong were extracted from the Seoul metropolitan area and the differences among the administrative districts were examined. and linear regression analysis were conducted with The variables included in the three categories(weather condition, anthropogenic heat generation, and land use characteristics) to investigate the cause of the difference in heat UHI intensity in each administrative district. As a result of analysis, UHI Intensity was found to be different according to the characteristics of administrative gu, administrative dong, and surrounding environment. The difference in administrative dong was larger than gu unit, and the UHI Intensity of gu and the UHI Intensity distribution of dongs belonging to the gu were also different. Linear regression analysis showed that there was a difference in heat island development intensity according to the average wind speed, development degree, Soil Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI) value. Among them, the SAVI and NDBI showed a difference in value up to the dong unit and The creation of a wind route environment for the mitigation of the heat island phenomenon is necessary for the administrative dong unit level. Therefore, it is considered that projects for mitigating heat island phenomenon such as land cover improvement plan, wind route improvement plan, and green wall surface plan for development area need to consider administrative dongs belonging to the gu rather than just considering the difference of administrative gu units. The results of this study are expected to provide the directions for urban thermal environment design and policy development in the future by deriving the necessity of analysis unit and the factors to be considered for the administrative city unit to mitigate the urban heat island phenomenon.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2006.10a
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• pp.70-72
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• 2006

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.1-16
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• 2022

Areas developed through land reclamation projects have huge economic advantages in terms of supplying lands that can be used for farmlands, urban areas and etc., however have relatively small areas of grasslands and densely located buildings compared to inland cities. Hence, an urban heat island is occurring in these areas due to this characteristic, and in particular, the urban heat island in Cheongna International City is getting serious. In this study, the urban heat island in Cheongna International City was evaluated and analyzed by classified into the three periods after the reclamation project: farmland(2001-2008), development(2009-2013) and artificial grassland(2014-2020). The land cover map and Landsat time-series imagery were utilized for measuring the differences of the land surface temperatures between the urbanized areas and the grassland/forest areas in Cheongna International City. The statistical results showed that the differences in the land surface temperature between these areas were calculated to be at most 0℃ during the period of farmland, at most 3.60℃ during the period of development, and at most 2.51℃ during the period of grassland. This study proved that the urban heat island phenomenon increased when the urbanized areas increased, and the urban heat island phenomenon decreased when the artificial grassland areas increased in Cheongna International City where the reclamation project was carried out. The statistical results derived through this research can be used as the reference data for identifying the urban heat island problem in urban planning and establishing the reduction plan.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.760-760
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• 2012

도심 지역은 인구집중, 토지 피복의 변화 및 교통량 증가 등의 인공열 배출원의 다양화 등의 요인에 의해 주변지역보다도 기온이 높은 도시 열섬(Urban Heat Island) 현상에 의해 독특한 도시기후의 특색을 보이게 된다. 일반적으로 도시 열 환경에 대한 연구는 도시 열섬의 강도나 현상을 파악하는데 집중되어 왔다. 최근 들어 도시 열섬 현상 완화 또는 개선을 위한 관심이 높아지면서 도시내에 존재하는 수면이나 녹지를 이용한 기후개선에 대한 연구가 진행되고 있다. 하천은 다양한 생물이 서식하는 공간이면서 생물의 다양성이 풍부한 생태계의 보고로 인간과 환경이 조화를 이루어 온 공간이기도 하다. 이와 같이 하천은 지역의 다양성과 특수성에 따라 가지고 있는 기능이 다양하다. 그 중 하천의 환경 기능은 많은 열용량을 축적시켜 수면의 온도상승을 적게 하여 하천의 온도는 물론 주변지역의 온도를 낮추는 역할을 하게 된다. 특히 흐르는 물은 대류와 혼합과정을 거치며 열을 운반할 수 있으므로 효율적인 축열체가 된다. 또한 하천의 물 등은 광의 투과성이 높기 때문에 표면에서는 반사되지 않고 수체 내에 열을 저장한다. 따라서 이러한 현상이 종합적으로 작용하여 도심하천은 도심지에서 높게 형성된 온도를 낮추는 냉각효과가 있다고 판단된다. 이러한 영향을 알아보기 위해 본 연구에서는 원격탐사 기법을 이용하여 도심하천이 도시 열완경 완화에 미치는 영향을 분석하였다. 분석을 위해 2009년 9월 6일 Landsat 7 ETM+ 위성영상을 이용하여 LST (Land Surface Temperature)를 추출하고, SEBAL (Surface Energy Balance Algori- thms for Land) 모델을 이용하여 지표면 열수지 성분을 추출하였다. 그 결과, 도심하천 주변의 온도가 도심지에 비해 $2{\sim}3^{\circ}C$ 정도 낮게 형성되었으며, 잠열은 주변 도심지에 비해 하천에서 높은 분포를 나타내었다. 그러나 하천 둔치나 하천 주변의 콘크리트, 아스팔트 및 나대지 등의 토지피복은 지표면 온도가 높게 형성되어 도심의 heat spot으로 작용하여 열 환경을 악화시키나 도심하천은 cool spot 작용을 하여 도심의 열을 완화하는 기능을 갖는 것으로 판단된다.

• Spatial Information Research
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• v.20 no.4
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• pp.1-16
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• 2012

There is no doubt that the urban heat island (UHI) is a mounting problem in built-up environments, due to energy retention by the surface materials of dense buildings, leading to increased temperatures, air pollution, and energy consumption. To investigate the UHI, three-dimensional (3-D) information is necessary to analyze complex sites, including dense building clusters. In this research, 3-D building geometry information is combined with two-dimensional (2-D) urban surface information to examine the relationship between urban characteristics and temperature. In addition, this research introduces spatial regression models to account for the spatial spillover effects of urban temperatures, and includes the following steps: (a) estimating urban temperatures, (b) developing a 3-D city model, (c) generating urban parameters, and (d) conducting statistical analyses using both Ordinary Least-Squares (OLS) and Spatial Regression Models. The results demonstrate that 3-D urban characteristics greatly affect temperatures and that neighborhood effects are critical in explaining temperature variations. Finally, the implications of the results are discussed, providing guidelines for policies to reduce the UHI.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.266-266
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• 2012

오늘날 도시는 인간 중심적으로 환경을 고려하지 않은 채 개발위주의 발전이 계속되고 있으며 도시화가 진행됨에 따라 도심지에 콘크리트와 아스팔트의 비율이 증가하고 농경지와 녹지가 감소하는 등 도시주변의 피복 변화가 빠르게 일어나고 있다. 이와 같이 열 환경을 고려하지 않은 도시의 급성장은 각종 인공 열과 대기오염 물질의 증가와 함께 도시상공의 기온을 상승시켜 도시의 기온이 주변 지역보다 높아지는 열섬현상의 원인이 되고 있다. 이에 따라 최근 미국, 유럽 등의 선진국을 비롯하여 아시아지역에서도 도시열섬현상 대책수립이 활발히 진행되어오고 있으며 국내에서도 열섬완화 대책 수립의 중요성이 인식되고 있다. 그러나 자연토지피복은 농경지, 나지, 수면과 같은 다양한 종류의 피복으로 구성되며 각 피복특성에 따라 도시내부에 영향을 미치는 정도가 다르게 나타나므로 도시계획에 반영될 수 있는 자연피복의 종류와 피복비율의 적정조합을 도출할 필요가 있다. 따라서 본 연구에서는 청주시를 대상으로 농경지를 포함하는 녹지의 감소, 공업단지의 증가에 따른 열 환경 영향을 분석하기 위하여 청주시의 연도별 토지피복 분포 현황과 과거 기상자료를 통해 토지피복 분포변화에 따른 온도 변화를 조사하였다. 토지피복은 농경지, 녹지, 주거지, 공업 단지 및 수역으로 분류하였으며, 대상지역의 기후 특성 파악을 위하여 청주시 총 면적에 대한 면적비율의 증감추이와 그에 따른 온도 변화를 정량적으로 파악하였다. 그 결과, 청주시는 녹지의 경우 정체 또는 감소추세를 나타낸 반면 공업단지는 지속적인 증가추세를 나타내었다.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.30 no.9
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• pp.80-82
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• 2001

• 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.

• Journal of the Korean Regional Science Association
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• v.33 no.2
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• pp.47-59
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• 2017

The purpose of this study is to examine various definitions of urban heat island and to analyze the characteristics and differences of each methodology by applying each methodology for deriving the heat island region to Seoul. The definition of the heat island is divided into the atmospheric heat island and the surface heat island according to the utilized temperature data. The methodology for deriving the heat island area differs depending on the comparison method and the spatial extent of the analysis. As a result of analyzing each methodology for Seoul city, it was confirmed that the heat island area of Seoul is different according to temperature data. Also, it is confirmed that the distribution range of the heat island area is different according to the spatial range of analysis. This shows that even if the heat island area is analyzed for the same space and the same view point, the heat island area is derived differently according to each methodology. This study can be used as a basic study to solve the urban heat island problem in the future.