• 농업과학연구
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• 제39권1호
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• pp.87-95
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• 2012

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about $21{\sim}25^{\circ}C$ and maximum LST is observed over industrial area of about $28{\sim}32^{\circ}C$. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

• 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.

• 대한원격탐사학회지
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• 제36권4호
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• 대한원격탐사학회지
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• 제37권1호
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• pp.153-160
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• 2021

Land Surface Temperature (LST) is the radiological surface temperature which observed by satellite. It is very important factor to estimate condition of the Earth such as Global warming and Heat island. For these reasons, many countries operate their own satellite to observe the Earth condition. South Korea has many landcovers such as forest, crop land, urban. Therefore, if we want to retrieve accurate LST, we would use high-resolution satellite data. In this study, we made LSTs with 4 LST retrieval algorithms which are used widely with Landsat-8 data which has 30 m spatial resolution. We retrieved LST using equations of Price, Becker et al. Prata, Coll et al. and they showed very similar spatial distribution. We validated 4 LSTs with Moderate resolution Imaging Spectroradiometer (MODIS) LST data to find the most suitable algorithm. As a result, every LST shows 2.160 ~ 3.387 K of RMSE. And LST by Prata algorithm show the lowest RMSE than others. With this validation result, we choose LST by Prata algorithm as the most suitable LST to South Korea.

• 한국측량학회지
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• 제39권2호
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• pp.113-122
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• 2021

Urban expansion, particularly converting sub-urban areas to residential and commercial land use in metropolitan areas, has been considered as a significant signal of regional economic development. However, this results in urban climate change. One of the key impacts of rapid urbanization on the environment is the effect of UHI (Urban Heat Island). Understanding the effects of urban land cover change on UHI is crucial for improving the ecology and sustainability of cities. This research reports an application of remote sensing data, GIS (Geographic Information Systems) for assessing effects of urban land cover change on the LST (Land Surface Temperature) and heat budget components in Ho Chi Minh City, where is one of the fastest urbanizing region of Vietnam. The change of urban land cover component and LST in the city was derived by using multi-temporal Landsat data for the period of 1998 - 2020. The analysis showed that, from 1998 to 2020 the city had been drastically urbanized into multiple directions, with the urban areas increasing from approximately 125.281 km² in 1998 to 162.6 km² in 2007, and 267.2 km² in 2020, respectively. The results of retrieved LST revealed the radiant temperature for 1998 ranging from 20.2℃ to 31.2℃, while that for 2020 remarkably higher ranging from 22.1℃ to 42.3℃. The results also revealed that given the same percentage of urban land cover components, vegetation area is more effective to reduce the value of LST, meanwhile the impervious surface is the most effective factor to increase the value of the LST.

• 대한원격탐사학회지
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• 제24권1호
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• pp.65-78
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• 2008

This study compares the relative accuracy and consistency of four split-window land surface temperature (LST) algorithms (Becker and Li, Kerr et ai., Price, Ulivieri et al.) using 24 sets of Terra (Aqua)/Moderate Resolution Imaging Spectroradiometer (MODIS) data, observed ground grass temperature and air temperature over South Korea. The effective spectral emissivities of two thermal infrared bands have been retrieved by vegetation coverage method using the normalized difference vegetation index. The intercomparison results among the four LST algorithms show that the three algorithms (Becker-Li, Price, and Ulivieri et al.) show very similar performances. The LST estimated by the Becker and Li's algorithm is the highest, whereas that by the Kerr et al.'s algorithm is the lowest without regard to the geographic locations and seasons. The performance of four LST algorithms is significantly better during cold season (night) than warm season (day). And the LST derived from Terra/MODIS is closer to the observed LST than that of Aqua/MODIS. In general, the performances of Becker-Li and Ulivieri et al algorithms are systematically better than the others without regard to the day/night, seasons, and satellites. And the root mean square error and bias of Ulivieri et al. algorithm are consistently less than that of Becker-Li for the four seasons.

• Journal of Ecology and Environment
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• 제45권4호
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• pp.190-202
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• 2021

Background: Landscape metrics have been widely applied to quantifying the relationship between land surface temperature and urban spatial patterns and have received acceptable verification from landscape ecologists but some studies have shown their inaccurate results. The objective of the study is to compare landscape metrics and texture-based measures as alternative indices in measuring urban heterogeneity effects on LST at multiple scales. Results: The statistical results showed that the correlation between urban landscape heterogeneity and LST increased as the spatial extent (scale) of under-study landscapes increased. Overall, landscape metrics showed that the less fragmented, the more complex, larger, and the higher number of patches, the lower LST. The most significant relationship was seen between edge density (ED) and LST (r = - 0.47) at the sub-region scale. Texture measures showed a stronger relationship (R² = 34.84% on average) with LST than landscape metrics (R² = 15.33% on average) at all spatial scales, meaning that these measures had a greater ability to describe landscape heterogeneity than the landscape metrics. Conclusion: This study suggests alternative measures for overcoming landscape metrics shortcomings in estimating the effects of landscape heterogeneity on LST variations and gives land managers and urban planners new insights into urban design.

• 한국수자원학회논문집
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• 제45권8호
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• pp.755-765
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• 2012

지표면 온도는 수문기상학에서 매우 중요한 인자로써 지면-대기의 상호순환을 이해하는 데 필수적인 요소이다. 따라서 지표면 온도를 정확하게 산출하기 위한 연구가 이루어지고 있다. 그러나 국내에서는 현재까지 시 공간적으로 일정한 자료를 대상으로 한 연구가 미흡한 상황이다. 본 연구에서는 국내 최초의 정지궤도 위성인 Communication, Ocean and Meteorological Satellite (COMS)의 지표면 온도 자료를 사용하여 MODerate-resolution Imaging Spectroradiometer (MODIS) 센서를 탑재한 위성(Terra/Aqua)에서 제공되는 지표면 온도와 비교 분석을 실시하였다. 또한, COMS 자료의 정확성 확인을 위하여 지상관측지점의 자료와 비교하였다. 그 결과 MODIS와의 비교에서는 COMS가 Aqua/Terra에 비하여 전체적으로 과소 산정되었으며, Aqua보다는 Terra와 비슷한 경향을 가지고 있는 것을 확인할 수 있었다. 지상 관측 일평균자료와의 비교에서도 COMS가 과소 산정되는 것으로 나타났다. 각각의 오차는 알고리즘 사용 인자의 차이, 자료의 시간적 차이, 외부적인 요인 등으로 인해 발생하는 것으로 판단된다. 그러나 전체적인 경향성이 비슷한 것으로 나타나 COMS의 활용 가능성을 확인할 수 있었으며, 추후보다 정확한 검 보정에 대한 연구가 필요한 실정이다.

• 대한공간정보학회지
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• 제24권3호
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• pp.39-47
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• 2016

본 연구는 몽골 Tuul-basin 지역의 토지피복변화 상태와 토지황폐화에 대한 분석을 위해 1990, 2001, 2011년의 녹색식물의 활력도가 가장 높은 여름의 Landsat 위성영상을 활용하였다. 몽골 Tuul-Basin 지역의 시계열 데이터를 이용하여, 정규식생지수(NDVI, normalized difference vegetation index), 토양조절 식생지수(SAVI, soil-adjusted vegetation index), 지표면온도(LST, land surface temperature)를 계산하여 토지피복변화 분석을 하였다. 그 결과 연구지역 전체 지역의 산림 및 녹지는 감소되고, 건조지역, 휴경지는 증가된 것으로 나타났으며, 점진적으로 토지가 황폐화되어 감을 알 수 있었다. 또한 LST와 식생지수의 상관성 분석을 실시한 결과, 높은 상관관계를 나타내었으며, 이는 대상지역의 토지피복변화나 식생의 활력도가 지표면의 온도와 밀접하게 관계가 있다는 것을 알 수 있었다.

• 한국측량학회지
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• 제35권1호
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• pp.23-30
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• 2017

NDVI (Normalized Difference Vegetation Index) plays an important role in surface land cover classification and LST (Land Surface Temperature Extraction). Its characteristics do not full carry the information of the surface cover typically in urban areas even though it is widely used in analyses in urban areas as well as in vegetation. However, abnormal NDVI values are frequently found in urban areas. We, therefore, examined NDVI values on whether NDVI is appropriate for LST and whether there are considerations in NDVI analysis typically in urban areas because NDVI is strongly related to the surface emissivity calculation. For the study, we observed the influence of the surface settings (i.e., geometric shape and color) on NDVI values in urban area and transition features between three land cover types, vegetation, urban materials, and water. Interestingly, there were many abnormal NDVI values systematically derived by the surface settings and they might influence on NDVI and eventually LST. Also, there were distinguishable transitions based on the mixture of three surface materials. A transition scenario was described that there are three transition types of mixture (urban material-vegetation, urban material-water, and vegetation-water) based on the relationship of NDVI and LST even though they are widely distributed.