• 대한원격탐사학회지
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• 제28권2호
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• pp.203-214
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• 2012

콘크리트와 아스팔트가 상당 부분을 차지하는 도시의 물리적인 환경은 도시열섬효과를 일으키는 주요 원인이며, 일차적으로 토지이용 또는 토양피복에 따른 지표면온도의 상승으로 나타난다. 본 연구에서는 도시의 토지피복유형이 지표면온도에 미치는 영향을 공간해상도가 다른 MODIS, Landsat ETM+과 RapidEye 위성영상을 사용하여 비교 분석해 보았다. 연구대상지인 일산 신도시지역의 지표면온도는 토지 이용에 따라 뚜렷이 구분되는 패턴을 보여주었는데 건폐율이 높은 저층단독주택지구보다 건폐율이 낮고 녹지율이 높은 고층 아파트단지의 지표면온도가 현저히 낮게 나타났다. 토지피복유형과의 관계는 건물이나 도로 등 도시화지역의 면적이 증가할수록 기후존의 지표면온도가 증가하고, 식생과 수면, 그림자 지역의 면적이 늘어날수록 지표면온도는 떨어진다. NDVI와 지표면온도 사이에도 음의 선형상관관계가 나타나지만, 계절적 영향을 배제하기 어렵다는 단점이 있다.

• 대한원격탐사학회지
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• 제35권4호
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• pp.609-616
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• 2019

Land surface temperature ($T_s$) is a critical variable for understanding the surface energy exchange between land and atmosphere. Using the data measured from micrometeorological flux towers, three types of $T_s$, obtained using a thermal-infrared radiometer (IRT), a net radiometer, and an equation for sensible heat flux, were compared. The $T_s$ estimated using the net radiometer was highly correlated with the $T_s$ obtained from the IRT. Both values acceptably fit the $T_s$ from the Terra/MODIS (Moderate Resolution Imaging Spectroradiometer)satellite. These results will enhance the measurement of land surface temperatures at various scales. Further, they are useful for understanding land surface energy partitioning to evaluate and develop land surface models and algorithms for satellite remote sensing products associated with surface thermal conditions.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.281-286
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• 2006

In this study, acquired time series Landsat TM/ETM+ image to extract land surface temperature for wide-area region and executed geometric correction and radiometric correction. And extracted land surface temperature using NASA Model, and I achieved the first correction by perform land coverage category for study region and applies characteristic emission rate. Land surface temperature that acquire by the first correction analyzed correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two datas using establishing correction formula. As a result, land surface temperature that acquire by 1,2th correction could correct in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, could acquire land surface temperature about study region by relative high accuracy by applying to other Landsat image for re-verification of study result.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.927-929
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• 2003

Using received northeast region in China of Terra/MODIS data at Tokyo University of information Sciences. Make monthly division Land Surface Temperature maximum composite image. Using monthly division Land Surface Temperature maximum composite image, considered characteristic of monthly variation of Land surface temperature and relation with land covering and NDVI at the northeast region in China.

• 한국환경과학회지
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• 제18권4호
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• pp.355-367
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• 2009

Comparison study on the land surface temperatures, which are calculated from four different algorithms for MODIS data, was carried out and the characteristics of each algorithm on land surface temperature estimation were also analysed in this study. Algorithms, which are well used for various satellite data analysis, in the comparisons are proposed by Price, Becker and Li, Ulivieri et al., and Wan. Verification of estimated land surface temperature from each algorithm is also performed using observation based regression data. The coefficient of determination ($R^2$) for daytime land surface temperature estimated from Wan's algorithm is higher than that of another algorithms at all seasons and the value of $R^2$ reach on 0.92 at spring. Although $R^2$ for Ulivieri's algorithm is slightly lower than that for Wan's algorithm, the variation pattern of land surface temperature for two algorithms are similar. However, the difference of estimated values among four algorithms become small at the region of high land surface temperature.

• 도시과학
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• 제9권1호
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• pp.17-31
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• 2020

This study aims to analyze the relations among greenbelt, urban land surface temperature empirically in order to assess the environmental effects of the greenbelt in the Seoul metropolitan area, objectively. For this purpose, this study conducts an empirical analysis of impacts of greenbelt on urban land surface temperature using a multiple-regression model. The main data employed in the analysis include real-time air pollution data, Landsat 8-OLI Landsat imagery data, KLIS data and Jip-gye-gu data. The major findings are summarized as follows. NDVI has a negative (-) correlation with the land surface temperature, and the urban temperature is high in areas with poor vegetation. The land surface temperature is low in residential or commercial areas, while the temperature is high in industrial areas. The temperature is low in green fields, open spaces, and river areas. it is found that the urban land surface temperature is low in the greenbelt zone. In the greenbelt zone, there is an effect that reduces the land surface temperature by 1% on average, as compared to that at the center of the Seoul metropolitan area. Especially, the center of the Seoul metropolitan area, in a range from 0.6% to 1.9% of the average temperature, the temperature gets lower up to approximately 3km from the greenbelt boundary.

• 대한원격탐사학회지
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• 제32권1호
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• pp.39-48
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• 2016

Yangon Mega City is densely populated and most urbanization area of Myanmar. Rapid urbanization is the main causes of Land Use and Land Cover (LULC) change and they impact on Land Surface Temperature (LST). The objectives of this study were to investigate on the LST with respect to LULC of Yangon Mega City. For this research, Landsat satellite images of 1996, 2006 and 2014 of Yangon Area were used. Supervised classification with the region of interest and calculated change detection. Ground check points used 348 points for accuracy assessment. The overall accuracy indicated 89.94 percent. The result of this paper, the vegetation area decreased from $1061.08sq\;km^2$ (24.5%) in 1996 to $483.53sq\;km^2$ (11.2%) in 2014 and built up area clearly increased from $485.33sq\;km^2$ (11.2%) in 1996 to $1435.72sq\;km^2$ (33.1%) in 2014. Although the land surface temperature was higher in built up area and bare land, lower value in cultivated land, vegetation and water area. The results of the image processing pointed out that land surface temperature increased from $23^{\circ}C$, $26^{\circ}C$ and $27^{\circ}C$ to $36^{\circ}C$, $42^{\circ}C$ and $43.3^{\circ}C$ for three periods. The findings of this paper revealed a notable changes of land use and land cover and land surface temperature for the future heat management of sustainable urban planning for Yangon Mega city. The relationship of regression experienced between LULC and LST can be found gradually stronger from 0.8323 in 1996, 0.8929 in 2006 and 0.9424 in 2014 respectively.

• 상하수도학회지
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• 제35권2호
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• pp.163-174
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• 2021

Heatwaves are one of the most common phenomena originating from changes in the urban thermal environment. They are caused mainly by the evapotranspiration decrease of surface impermeable areas from increases in temperature and reflected heat, leading to a dry urban environment that can deteriorate aspects of everyday life. This study aimed to calculate daily maximum ground surface temperature affecting heatwaves, to quantify the effects of urban thermal environment control through water cycle restoration while validating its feasibility. The maximum surface temperature regression equation according to the impermeable area ratios of urban land cover types was derived. The estimated values from daily maximum ground surface temperature regression equation were compared with actual measured values to validate the calculation method's feasibility. The land cover classification and derivation of specific parameters were conducted by classifying land cover into buildings, roads, rivers, and lands. Detailed parameters were classified by the river area ratio, land impermeable area ratio, and green area ratio of each land-cover type, with the exception of the rivers, to derive the maximum surface temperature regression equation of each land cover type. The regression equation feasibility assessment showed that the estimated maximum surface temperature values were within the level of significance. The maximum surface temperature decreased by 0.0450℃ when the green area ratio increased by 1% and increased by 0.0321℃ when the impermeable area ratio increased by 1%. It was determined that the surface reduction effect through increases in the green area ratio was 29% higher than the increasing effect of surface temperature due to the impermeable land ratio.

• 한국측량학회지
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• 제36권4호
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• pp.263-270
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• 2018

지표면 온도는 지면-대기의 상호 순환을 이해하는데 중요한 요소로 알려져 있지만 시공간적 변동성이 크기 때문에 정규적인 관측은 거의 이루어지지 못하고 있다. 기존의 지표면 온도는 위성 영상을 이용하여 관측하고 있지만 위성의 특성상 긴 재방문주기와 낮은 정확도의 한계를 가지고 있다. 본 연구에서는 기존의 위성 영상을 활용한 지표면 온도 관측의 대체가능성을 확인하기 위해 무인항공기에 열적외선 센서를 탑재하여 단일 영상을 취득하였다. 취득된 영상은 JPEG 영상에서 TiFF 영상으로 변환하여 정사영상을 제작하였으며 정사영상의 DN값을 이용하여 실제 지표면 온도로 계산하였다. 계산된 피복별 지표면 온도의 정확도를 평가하기 위해 영상촬영과 동시에 적외선 온도계로 직접 관측한 지표면 온도와 비교하였다. 두 가지 방법으로 관측한 지표면 온도를 비교 했을 때, 모든 피복들에 대해서 정확도가 열적외선 센서의 관측 정확도 이하로 나타났다. 따라서 무인항공기에 탑재된 열적외선 센서를 이용하여 기존의 지표면 온도 관측 방법인 위성 영상의 대체 가능성을 확인하였다.

• 대한원격탐사학회지
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• 제39권1호
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• pp.99-110
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• 2023

Land surface temperature (LST) is a critical environmental indicator affected by land cover (LC) changes. Currently, the most convenient and fastest way to retrieve LST is to use remote sensing images due to their continuous monitoring of the Earth's surface. The work intended to investigate land cover change and temperature response inAn-Najaf province. Landsat multispectral imageries acquired inAugust 1989, 2004, and 2021 were employed to estimate land cover change and LST responses. The findings exhibited an increase in water bodies, built-up areas, plantations, and croplands by 7.78%, 7.27%, 6.98%, 3.24%, and 7.78%, respectively, while bare soil decreased by 25.27% for the period (1989-2021). This indicates a transition from barren lands to different land cover types. The contribution index (CI) was employed to depict how changes in land cover categories altered mean region surface temperatures. The highest LSTs recorded were in bare lands (42.2℃, 44.25℃, and 46.9℃), followed by built-up zones (41.6℃, 43.96℃, and 44.89℃), cropland (30.9℃, 32.96℃, and 34.76℃), plantations (35.4℃, 36.97℃, and 38.92℃), and water bodies (27.3℃, 29.35℃, and 29.68℃) respectively, in 1989, 2004, and 2021. Consequently, these changes resulted in significant variances in LST between different LC types.