• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.921-932
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• 2023

Land cover change due to urban population concentration and urban expansion can cause various environmental problems such as urban heat islands. In particular, New towns are considered an appropriate study site to analyze changes in urban climate due to rapid urbanization in a short period. This study used Landsat satellite imagery to compare and analyze the land cover changes before and after the development of two new towns with different plans, and the resulting changes in surface urban heat island (SUHI) phenomena. Correlation analysis was also conducted between urban structural features that may affect the SUHI intensity. The results of the analysis confirm the rapid change in land cover as new town development progresses and the direct intensification of the SUHI phenomenon. This study confirms the differences in SUHI caused by different urban plans and suggests the need for three-dimensional urban planning to improve the thermal environment.

• 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 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.198-198
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• 2022

최근 도시화에 따른 토지 피복 변화와 열섬현상 등의 원인으로 상승하는 도시의 기온이 식물 계절에 미치는 영향에 관한 연구들이 다수 진행되고 있다. 본 연구는 수도권인 서울과 경기도 지역을 대상으로 도시 내 열섬현상으로 인한 기온 상승과 도시 지역 내 식생 생장기간 변화의 관계성을 분석하였다. 식물계절 모니터링에 사용한 개량식생지수(Enhanced Vegetation Index, EVI)는 Google Earth Engine (GEE)에서 제공하는 30 m 해상도의 2000-2021년 NASA-USGS Landsat 위성(TM5, ETM+7, OLI8)의 지표면 반사율(surface reflectance, SR) 자료에서 도출하여 생장기간 산정에 사용하였다. 또한 PRISM (Parameter-elevation Regressions on Independent Slopes Model)을 각 기상관측지점의 일별 지상 기온 자료에 적용하여 30 m 해상도로 생성한 격자형 지표면 온도의 공간적 패턴을 분석하였다. 연구 지역 내 도시화 정도(magnitude)를 도심으로부터의 거리와 환경부 토지피복도 및 인구 밀도를 종합하여 특정하였고, 최종적으로 기후변화 및 도시화 정도와 생장기간 변화의 특징을 분석하였다. 비선형 로지스틱 회귀를 사용하여 EVI 데이터를 종합하여 분석한 결과, 수도권 지역에서 전반적으로 식물계절 개엽일(Start of Season)은 앞당겨지며 낙엽일(End of Season, EOS)은 늦춰져 생장기간(Length of Growing Season, LOS)이 길어짐을 발견하였다.

• 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.

• 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 Wetlands Research
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• v.13 no.2
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• pp.199-208
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• 2011

Scarcity of water worldwide, increasing greenhouse gas emissions, increased energy consumption due to the Earth is threatened. Existing in the process of urban planning and development of forests, rivers and other natural ecosystems have been destroyed and that there was increased impervious pavement. Impervious pavement increase water circulation system to destroy the natural and urban water retention, infiltration and decreased evaporation. Nonpoint source pollution(NPS) occurs when rainfall impervious pavement and appeal directly to the river water inflow is adversely impacts of the situation. In this study, rainfall occurs impervious pavement NPS pollution reduction and temperature increase due to the increase in urban areas, and to solve heat island phenomenon is to develop small HSSF constructed wetland technology. The small HSSF constructed wetland sedimentation, filtration, adsorption, absorption by vegetation, including such mechanisms. Techniques for verification of the pilot-scale test was conducted. In the future domestic urban heat island phenomenon and restore the natural water cycle for the facilities will be used as a basis to develop.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.468-468
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• 2022

기후변화 및 도시열섬화 등의 영향으로 여름철 폭염 및 봄·겨울철 미세먼지 영향은 증가하고 있다. 최근 40년(1980년~2019년) 동안 서울의 최고기온은 2.2℃ 증가하였으며, 이는 전국에서 두 번째로 높은 증가추세이다. 서울시는 도시열섬과 미세먼지 저감을 일환으로 '스마트 물순환도시 조성사업'을 추진하고 있다. 본 연구에서는 서울형 물순환도시 소개와 더불어 쿨링포그, 쿨루프, 클린로드시스템, 투수블록, 식생수로 빗물정원 등 수자원을 활용한 기술을 조사하고 문헌조사를 통해 저감효과를 비교분석하였다. 이는 수자원을 활용한 도시 형태 개선으로 쾌적한 도시환경 조성 뿐만 아니라 시민의 행복과 만족감 증대에 기여할 것으로 판단되며, 향후 서울형 스마트 물순환도시 보다 많은 지역에 확대운영 할 수 되도록 기여하고자 한다.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.12-22
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• 2012

In Seoul, skyscrapers are built in commercial zones known as residential-commercial complexes, which cause such environmental problems as urban heat islands(UHI) and air pollution. To investigate air temperature differences in areas near skyscrapers at Gangnam-gu, Seoul, South Korea, fixed air temperature observation and traverse observations were performed from March 16, 2008 to March 15, 2009. The annual mean air temperature at Tower Palace(TPL) was higher than that at Sookmyung Girls' High School(SMG) by $0.7^{\circ}C$, although the distance between the two observation positions is only 200m. The number of tropical nights at TPL was 13, while that at SMG was 5. The higher air temperature at TPL was due to a significantly lower sky view factor(SVF), which prevented long-wave radiation from emitting into the sky. The highest air temperature increases near TPL occurred on summer nights because of the high-electricity consumption value of $70.22Wh/m^2$ for the TPL block in August due to air conditioning for cooling. It is concluded that the warm air pocket centered on TPL.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.42-54
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• 2023

The population is concentrated in the metropolitan areas in Korea, and low-density residential areas are transforming into high density residential areas through redevelopment to meet this demand. However, large-scale redevelopment in a short period of time has a negative impact on the urban climate, such as generating a heat island effect due to the reduction of urban green areas. In this study, the change in surface temperature from 2013 to 2022 in the redevelpment areas of Godeok-dong and Dunchon-dong, Gangdong-gu, Seoul, was analyzed using Landsat 8 satellite images. In the Godeok-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, mixed forest and urban area, and low density residential area. In the Dunchon-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, and low density residential area. The difference in surface temperature was analyzed through multiple regression analysis conducted yearly over the three different stages in redevelopment period. The results from the multiple regression analysis show that in both areas, the land surface temperature of target redevelopment area was higher than that of the forest area and lower than low density residential area. It can be seen that these results occurred because the low-density residential area in Godeok-dong and Dunchon-dong had a lower green area ratio and a higher building-to-land ratio than the target redevelopment area. The results of this study suggest that even if low-density residential areas are transforming into high-density areas, adjusting the management of green areas and building-to-land ratio can contribute to lessen urban heat island effect.