• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.1-16
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• 2017

This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

• 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.

• Journal of the Korean Regional Science Association
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• v.35 no.4
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• pp.61-73
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• 2019

Urban development and densification have led to the Urban Heat Island Effect, in which the temperature of urban space is higher than the surrounding areas, and the intensity is increasing with climate change. In addition, when the city's air temperature rises in summer, low-income, elderly population, and socially vulnerable people who have health problems lack the ability to cope with the elevated heat environment. Therefore, this study aimed to identify the urban heat island area of Seoul through Hotspot analysis, which is a spatial statistics technique, and explored physical environments, demographic and socioeconomic characteristics of urban heat island effect areas using logistic regression models. This study performed urban heat island hotspot analysis using the average air temperatures of the 423 administrative dongs in Seoul. Analysis results identified that the urban heat islands were concentrated in Jung-gu, Jongno-gu, Yongsan-gu, and Yeongdeungpo-gu. Logistic regression analysis results indicated that urban heat island areas of Seoul were affected by residential floor area ratio, commercial facility floor area ratio, overall floor area ratio, impervious surface ratio, and normalized difference vegetation index(NDVI). In addition, as a result of analyzing the vulnerable area of thermal environment considering the demographic and socioeconomic characteristics of the heat island area, urban heat island areas of Seoul were significantly associated with the proportion of low-income elderly living alone. The result of this study provided useful insights for urban thermal environmental design and policy development that could improve the thermal environment for the socially disadvantaged urban population.