• 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.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.277-279
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• 2003

The study utilizes remote sensing as the main monitoring means. With different spatial high-resolution, multichannel ASTER remote sensing image as the main information in Beijing city zone; with regional border and statistical data as auxiliary factor a study between the thermal space distribution character and the underground medium is analyzed based on the GIS logical algorithm and synthetic analysis technology. Results show thermal forming mechanism and the rule of distribution is mainly related to the underground medium and the change of the city distribution. Different underground medium has different degree and intensity influence on the thermal space distribution. Furthermore, urban greenbelt and water areas can reduce the thermal effect and large-scale greenbelt creates green island effect. In addition, Road net, residential area, population density, heat resources and so on have some positive effect on the thermal distribution, which increase the local temperature and intensity on the other hand. It is important to study the thermal distribution and its related factors, which contributes to the plan, construction and development of the city.

• Atmosphere
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• v.20 no.1
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• pp.13-26
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• 2010

The Urban Canopy Model (UCM) implemented in WRF model is applied to improve urban meteorological forecast for fine-scale (about 1-km horizontal grid spacing) simulations over the city of Seoul. The results of the surface air temperature and wind speed predicted by WRF-UCM model is compared with those of the standard WRF model. The 2-m air temperature and wind speed of the standard WRF are found to be lower than observation, while the nocturnal urban canopy temperature from the WRF-UCM is superior to the surface air temperature from the standard WRF. Although urban canopy temperature (TC) is found to be lower at industrial sites, TC in high-intensity residential areas compares better with surface observation than 2-m temperature. 10-m wind speed is overestimated in urban area, while urban canopy wind (UC) is weaker than observation by the drag effect of the building. The coupled WRF-UCM represents the increase of urban heat from urban effects such as anthropogenic heat and buildings, etc. The study indicates that the WRF-UCM contributes for the improvement of urban weather forecast such nocturnal heat island, especially when an accurate urban information dataset is provided.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.4
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• pp.363-372
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• 2000

In order to overtake a quantitative analysis of effect of anthropogenic heat and different land-use on urban thermal environment numerical simulation of surface energy budget was carried out under typical summer synoptic condition. It is beneficial to understand surface temperature of complex urban surace. The different land-use types are classified of rice field farm fruit garden residential region forest water and swamp by using map scaled 1/25000 of Pusan metropolitan. The model predicts that maximum heat island intensity in the central part of Pusan is 7$^{\circ}C$ at 2000 LST in summertime. The surface temperature is propotional to the density of constructions. The effect of anthropogenic heat generation on surface temperature is the increase of 0.3$^{\circ}C$ at 1400LST in the central part of Pusan during summertime.

• Journal of Environmental Science International
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• v.16 no.9
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• pp.1063-1069
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• 2007

The present study investigated the causes and intensity of the urban heat island phenomenon by the seasons according to the pattern of land use in Chungju City. Highest temperature and lowest moisture areas of the urban were very similar to the distribution of commercial districts, on the other hand, lowest temperature and highest moisture areas were distributed in manufacturing districts, green zones and the Hoam Lake. If appear at intensity of the distance from the outer circumference of commercial districts, wind direction and the rise of temperature, we could observe the remarkable expansion of high temperature from commercial districts toward residential districts around of downwind in all seasons. In case the effect of the wind was not significant as well, high temperature in commercial districts appeared tendency that a little spread to 1, 2 residential districts around. But checked up the intimate relations between the amount of moving heat and wind, when out of consideration that size of area was not much compared than residential areas of downwind affected by the wind. These phenomenon was relatively obvious in summer, the other side, in spring and autumn appeared a similar tendency.

• Advances in environmental research
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• v.9 no.1
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• pp.19-39
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• 2020

Urban heat island (UHI) is one of the most important climatic implications of urbanization and thus a matter of key concern for environmentalists of the world in the twenty-first century. The relationship between climate and urbanization has been better understood with the introduction of thermal remote sensing. So, this study is an attempt to understand the influence of urbanization on local temperature for a small developing city. The study focuses on the investigation of intensity of atmospheric and surface urban heat island for a small urbanizing district of Punjab, India. Landsat 8 OLI/TIRS satellite data and field observations were used to examine the spatial pattern of surface and atmospheric UHI effect respectively, for the month of April, 2018. The satellite data has been used to cover the larger geographical area while field observations were taken for simultaneous and daily temperature measurements for different land use types. The significant influence of land use/land cover (LULC) patterns on UHI effect was analyzed using normalized built-up and vegetation indices (NDBI, NDVI) that were derived from remote sensing satellite data. The statistical analysis carried out for land surface temperature (LST) and LULC indicators displayed negative correlation for LST and NDVI while NDBI and LST exhibited positive correlation depicting attenuation in UHI effect by abundant vegetation. The comparison of remote sensing and in-situ observations were also carried out in the study. The research concluded in finding both nocturnal and daytime UHI effect based on diurnal air temperature observations. The study recommends the urgent need to explore and impose effective UHI mitigation measures for the sustainable urban growth.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1447-1460
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• 2021

Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

• Atmosphere
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• v.21 no.3
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• pp.257-271
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• 2011

The aim of this study is to examine weather modification by urbanization and human activities. The characteristics of the urban heat island (UHI) and precipitation in Seoul metropolitan area of Korea are investigated to demonstrate that cities can change or modify local and nearby weather and climate, and to confirm that cities can initiate convection, change the behavior of convective precipitation, and enhance downstream precipitation. The data used in this study are surface meteorological station data observed in Seoul and its nearby 5 cities for the period of 1960 to 2009, and 162 Automatic Weather System stations data observed in the Seoul metropolitan area from 1998 to 2009. Air temperature and precipitation amount tend to increase with time, and relative humidity decreases because of urbanization. Similar to previous studies for other cities, the average maximum UHI is weakest in summer and is strong in autumn and winter, and the maximum UHI intensity is more frequently observed in the nighttime than in the daytime, decreases with increasing wind speed, and is enhanced for clear skies. Relatively warm regions extend in the east-west direction and relatively cold regions are located near the northern and southern mountains inside Seoul. The satellite cities in the outskirts of Seoul have been rapidly built up in recent years, thus exhibiting increases in near-surface air temperature. The yearly precipitation amount during the last 50 years is increased with time but rainy days are decreased. The heavy rainfall events of more than $20mm\;hr^{-1}$ increases with time. The substantial changes observed in precipitation in Seoul seem to be linked with the accelerated increase in the urban sprawl in recent decades which in turn has induced an intensification of the UHI effect and enhanced downstream precipitation. We also found that the frequency of intense rain showers has increased in Seoul metropolitan area.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.556-559
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• 2007

The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.