• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.35-45
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• 1999

The research is to examine urban heat island effects which is resulted from urbanization using thermal infrared band of Landsat TM data and to demonstrate heat island alleviation effects of green spaces through correlation analysis of NDVI(Normalized Difference Vegetation Index) and surface temperature. According to the results, forests which are covered with natural vegetation have a high NDVI digital values, but surface temperature is very low, and urban areas which is composed of artificial paving materials have a low NDVI, surface temperature increases gradually. In summary, the analysis of relationship between NDVI and surface temperature, used in this study, is regarded as one of effective methodologies for proving heat island alleviation effects of vegetation.

• 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.5
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• pp.67-79
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• 2020

Plans to mitigate overheating in urban areas requires the identification of the characteristics of the thermal environment of the city. The key information is the distribution of higher and lower temperatures (referred to as "hotspot" or "coldspot", respectively) in the city. This study aims to identify the areas within Jeonju City that are suffering from increasing land surface temperatures (LST) and the factors linked to such this phenomenon. To identify the hot and cold spots, Local Moran's I and Getis-Ord Gi^* were calculated for the LST based on 2017 images taken using the thermal band of the Landsat 8 satellite. Hotspot analysis revealed that hotspot regions, (the areas with a high concentration of Land Surface Temperature) are located in the old town area and in industrial districts. To figure out the factors linked to the hotspots, a correlation analysis, and a regression analysis taking into account environmental covariates including Normalized Difference Vegetation Index (NDVI) and land cover. The values of NDVI showed that it had the strongest effect on the lowering LSTs. The results of this study are expected to provide directions for urban thermal environment designing and policy development to mitigate the urban heat island effect in the future.

• 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 Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.143-150
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• 2013

Recently, environmental issues such as climate warming, ozone layer depletion, reduction of tropical forests and desertification are emerging as global environmental problems beyond national problems. And international attention and effort have been carried out in many ways to solve these problems. In this study, the growth of green was calculated quantitatively using the technique of remote sensing and temperature change was figured out through temperature extraction in the city. The land-cover changes and thermal changes for research areas were analyzed using Landsat TM images on May 2002 and May 2009. Surface temperature distribution was calculated using spectral degree of brightness of Band 6 that was Landsat TM thermal infrared sensor to extract the ground surface temperature in the city. As a result of research, the area of urban green belt was increased by $2.87km^2$ and the ground surface temperature decreased by $0.6^{\circ}C{\sim}0.8^{\circ}C$ before and after tree planting projects. Henceforth, if the additional study about temperature of downtown is performed based on remote sensing and measurement data, it will contribute to solve the problems about the urban environment.

• Journal of Environmental Impact Assessment
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• v.28 no.1
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• pp.23-34
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• 2019

Global warming becomes a serious issue that poses subsidiary issues like a sea level rise or a capricious climate over the world. Because of severe heat-wave of the summer in Korea in 2016, a big attention has been focused on urban heat island since then. Not just about heat-wave itself, many researches have been concentrated on how to adapt in this trendy warming climate and weather in a small scope. A big part of existing studies is mitigating "Urban Heat Island effect" and that is because of huge impervious surface in urban area where highly populated areas do diverse activities. It is a serious problem that this thermal context has a high possibility causing mortality by heat vulnerability. However, there have been many articles of a green infrastructures' cooling impact in summer. This research pays attention to measure cooling effect of a street planting considering urban canyon and type of green infrastructures in neighborhood scale. This quantitative approach was proceeded by ENVI-met simulation with a spatial scope of a commercial block in Seoul, Korea. We found the dense double-row planting is more sensitive to change in temperature than that of the single-row. Among the double-row planting scenarios, shrubs which have narrow space between the plant and the land surface were found to store heat inside during the daytime and prevent emitting heat so as to have a higher temperature at night. The quantifying an amount of vegetated spaces' cooling effect research is expected to contribute to a study of the cost and benefit for the planting scenarios' assessment in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.320-320
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• 2022

기후변화와 도시화로 인한 영향으로 도시의 폭우, 폭염을 비롯한 현상이 빈번하게 발생하고 있다. 특히 시가화 지역의 높은 불투수율은 도시홍수를 야기한다. 이러한 현상을 완화하기 위해 도시지역에서는 그린인프라와 저영향개발이 도입되고 있다. 그 중 지속가능한 발전을 위한 필수요소로 자리매김한 옥상녹화는 도시에 위치한 건물의 상층부와 내부의 온도를 낮춤으로써 에너지절감효과와 강우 시 빗물을 저류함으로써 우수유출 저감효과, 그리고 도시 공간 내 녹지도입으로 인한 이산화탄소 배출 저감 효과 등을 기대할 수 있다. 본 연구에서는 열섬현상완화와 유출 저감의 방안 중 하나인 옥상녹화(Green roof)의 효과를 정량적으로 평가하기 위해 콘크리트로 이루어진 동일한 제원의 실험동을 구축하고, 실험동 내외부의 온도, 습도, 강우, 풍속, 일사량 등의 기상자료를 측정할 수 있는 센서를 설치하였다. 각 실험동에서 측정된 기상요소를 Flux Profile Method를 적용하여 공간 내에 있는 열에너지의 총량인 순복사열을 구성하는 현열속, 잠열속, 토양열속(H, LE, G)을 산정하였다. 또한 에너지 평형에 따라 산정된 각 실험동의 열속과 지표면 복사량 관측자료을 정량적으로 비교하여 옥상녹화의 적용성을 평가하였다. 2021년 7월 21일부터 2021년 7월 28일 까지 모니터링한 결과 옥상녹화의 열 효율은 일반 콘크리트 지붕에 비해 실내온도가 최대 6.83℃ 낮게 나타나며 이는 여름철 건물 내부의 온도조절에 필요한 에너지 저감효과를 볼 수 있다. Flux Profile Method를 적용한 결과 옥상녹화의 전체 열속 중 현열속 28.5% 잠열속 70.7%, 토양열속 0.5% 의 복사량 분포를 보였고, 일반 콘크리트 지붕은 현열속 45.3%, 잠열속 38.6%, 토양열속 16.2% 으로 나타났다. 이와 같은 방법은 옥상녹화의 정량적 평가를 가능하게 함으로서 향후 기후변화 대응방안 및 전략 수립 시 옥상녹화의 온도저감효과 분석에 적극 활용할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.94-94
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• 2021

현재 전 지구적으로 일어나고 있는 극단적 기후현상과 이로 인한 자연재해의 원인은 복합적이다. 기후변화로 인한 영향과 동시에 도시화 또한 하나의 원인으로 작용하고 있다. 이러한 영향을 완화하기 위한 방안으로 도시의 그린인프라와 저영향개발은 최근 지속가능한 발전을 위해 꼭 필요한 요소로 자리잡고 있다. 그린인프라 유형 중 하나인 옥상녹화는 많은 이점을 제공한다. 도시에 위치한 건물의 상층부, 내부 및 주변 온도을 낮춤으로써 얻을 수 있는 에너지절감 효과와 강우 시 상당량의 빗물을 저류함으로써 기대되는 우수유출 저감효과, 그리고 도시 공간 내 식물의 적극적인 도입으로 인한 이산화탄소 배출 저감 효과 등을 기대할 수 있다. 본 연구에서는 도시지역의 열섬현상완화와 유출저감의 방안 중 하나인 옥상녹화(Green roof)의 효과를 정량적으로 평가하기 위해 콘크리트로 이루어진 동일한 제원의 실험동을 구축하고, 실험동 내외부의 연직방향 온도, 습도, 강우, 풍속, 일사량 등의 기상자료를 측정할 수 있는 센서를 설치하였다. 각 실험동에서 측정된 기상자료를 Flux Profile Method를 적용하여 무강우기간과 강우발생기간 동안의 연직 방향의 현열속, 잠열속, 토양열속(H, LE, G) 을 산정하였다. 에너지 평형에 따라 산정된 각 실험동의 열속과 지표면 복사량 관측자료을 정량적으로 비교하여 적용성을 평가하였다. 실험의 대조군인 일반 코팅재로 마감된 콘크리트 지붕의 무강우 기간 중 최대 현열속 693.82 W/m² 잠열속은 330.15 W/m² 으로 나타났으며, 실험군인 옥상녹화가 조성된 지붕의 최대 현열속 436.27 W/m², 잠열속 949.20 W/m² 으로 나타났으며, 산정치와 관측치 시계열의 NSE는 0.81 으로 Flux Profile Method를 통해 산정된 열속의 정확도는 비교적 높은 것으로 나타났다. 이와 같은 방법으로 옥상녹화의 정량적 평가가 가능해짐으로써 향후 기후변화 대응방안 및 전략 수립 시 옥상녹화의 온도저감효과 분석에 적극 활용할 수 있을 것으로 판단된다.

• 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.