Urban Thermal Characteristics Research Articles

ASSESSING URBAN HEAT ISLAND IMPACT AND IDENTIFYING VULNERABILITY ZONES THROUGH GEOSPATIAL AND GEO-STATISTICAL TECHNIQUES

An urban heat island emerged due to micro urban temperature variations are also referred to as urban heat islands or urban hot spots. The high-rise buildings along the roads form "Urban Canyons" that inhibit reflected radiation from the built-up surface. Urban heat island develops over the cities due to man-made activity and the landscape. An understanding of the urban heat island and its formation is not only helpful in understanding urban thermal characteristics but also helps in understanding human comfort. A geospatial technique has the ability to acquire updated and cost-effective data over large regions. For urban climatology studies, remote sensing and geographic information systems are an important source of information and an effective methodology. Since 1971, the city of Krishnanagar and its vicinity have been witnessing rapid urban growth. Due to its dense population, urban climate and rapid urban expansion, they cause environmental degradation. Appraisal and Impact of urbanization on micro-climate in the Krishnanagar city complex based on satellite derived parameters. For the years 1995, 2007 and 2018, several satellite image analysis approaches such as NDVI, NDWI and NDVI were computed. Significant differences in land surface temperature were observed between 1995 and 2007, as compared to 2007 and 2018.

Modelling the impacts of land use/land cover changing pattern on urban thermal characteristics in Kuwait

• Changes of LULC, summer LST, UHI and UTFVI shift in Kuwait were analyzed. • Reduction of vegetation cover (47%) significantly increases the UHI effect. • LULC vs UTFVI relationship better explain the impacts of different land cover on thermal environment. • Summer UHI and UTFVI prediction exhibit a gradual decrease in overall thermal characteristics. • Predicted UTFVI demonstrated the highest UTFVI concentration in the built-up area. Rapid urbanization owing to population growth and economic development has made thermal environment-related studies increasingly prominent. This study aims to monitor and predict the changes in land use/land cover (LULC) and their impacts on land surface temperature (LST), urban heat island (UHI), and urban thermal field variance Index (UTFVI) in Kuwait from 1991 to 2021 for the very first time. Support Vector Machine (SVM) and Artificial Neural Network (ANN)machine learning algorithms were used to analyze and predict, respectively, using Landsat 4-5 and 8 images from 1991 to 2021 at 10 years interval. Results illustrated transformation of 27.24% bare land and 5.43% vegetation into the built-up area increased the mean LST by 5°C, resulting in an upsurge of UHI values by 0.861 and the strongest UFTVI effects by 108% from 1991 to2021. Predicted LULC, LST, UHI and UTFVI distribution modelled using the ANN-based Cellular Automata technique for 2031 shows the declination of vegetation cover (44%) and water bodies (57%) during 2021–2031, resulting upsurge in built-up areas (38%) and higher LST (10°C). Moreover, by 2031, 41% of the total study area will be covered by the strongest UTFVI affected zones. All the prediction was performed with a higher accuracy, and validated by RMSE and R 2 values with predicted and real datasets. Assessing the predicted LULC, LST, UHI, and UTFVI distribution maps will help prospective policymakers and city planners to take the necessary actions by reducing heat stress impacts and make cities sustainable.

The influence of seasonal land-use-land-cover transformation on thermal characteristics within the city of Pietermaritzburg

Urbanisation has been identified as a major threat to the environment as it increases demand for urban spaces and transforms natural landscapes to impervious surfaces, leading to the Urban Heat Island (UHI) phenomenon. Natural landscapes such as vegetation and water bodies act as thermal sinks that absorb heat while impervious surfaces such as buildings and concrete pavements act as thermal sources that retain and emit heat. The thermal emission results in several negative effects such as temperature inversion, compromised human health, pollution, species loss, high energy consumption and climate change at a local, regional and global scales. Whereas studies on UHI are abound, there is paucity in literature on the influence of seasonal urban Land Use Land Cover (LULC) transformation on urban thermal characteristics. Specifically, the proportional seasonal variability and contribution of individual LULCs to urban heat is often poorly understood. Using the freely available Landsat 8 optical and thermal bands, this study examined the seasonal characteristics of the UHI phenomenon in relation to LULCs in the Pietermaritzburg city, South Africa. Results in this study revealed that UHIs exist in both winter and summer, but with more intensity in summer. The study also established that LULCs varied with seasons. Bare surfaces and dense vegetation had the most thermal influence during winter while dense vegetation and low density buildings had the most thermal influence during summer. These findings provide a better understanding of thermal distribution based on LULC seasonality changes, valuable for sustainable urban planning and climate change mitigation.

“Cool” Roofs as a Heat-Mitigation Measure in Urban Heat Islands: A Comparative Analysis Using Sentinel 2 and Landsat Data

Urban growth, characterized by expansion of impervious at the cost of the natural landscape, causes warming and heat-related distress. Specifically, an increase in the number of buildings within an urban landscape causes intensification of heat islands, necessitating promotion of cool roofs to mitigate Urban Heat Islands (UHI) and associated impacts. In this study, we used the freely available Sentinel 2 and Landsat 8 data to determine the study area’s Land Use Land Covers (LULCs), roof colours and Land Surface Temperature (LST) at a 10-m spatial resolution. Support Vector Machines (SVM) classification algorithm was adopted to derive the study area’s roof colours and proximal LULCs, and the Transformed Divergence Separability Index (TDSI) based on Jeffries Mathussitta distance analysis was used to determine the variability in LULCs and roof colours. To effectively relate the Landsat 8 thermal characteristics to the LULCs and roof colours, the Gram–Schmidt technique was used to pan-sharpen the 30-m Landsat 8 image data to 10 m. Results show that Sentinel 2 mapped LULCs with over 75% accuracy. Pan-sharpening the 30-m-resolution thermal data to 10 m improved the spatial resolution and quality of the Land Surface map and the correlation between LST and Normalized Difference Vegetation Index (NDVI) used as proxy for LULC. Green-colour roofs were the warmest, followed by red roofs, while blue roofs were the coolest. Generally, black roofs in the study area were cool. The study recommends the need to incorporate other roofing properties, such as shape, and further split the colours into different shades. Furthermore, the study recommends the use of very high spatial resolution data to determine roof colour and their respective properties; these include data derived from sensors mounted on aerial platforms such as drones and aircraft. The study concludes that with appropriate analytical techniques, freely available image data can be integrated to determine the implication of roof colouring on urban thermal characteristics, useful for mitigating the effects of Urban Heat Islands and climate change.

Determining the Influence of Long Term Urban Growth on Surface Urban Heat Islands Using Local Climate Zones and Intensity Analysis Techniques

Urban growth, typified by conversion from natural to built-up impervious surfaces, is known to cause warming and associated adverse impacts. Local climate zones present a standardized technique for evaluating the implications of urban land use and surface changes on temperatures of the overlying atmosphere. In this study, long term changes in local climate zones of the Bulawayo metropolitan city were used to assess the influence of the city’s growth on its thermal characteristics. The zones were mapped using the World Urban Database and Access Portal Tool (WUDAPT) procedure while Landsat data were used to determine temporal changes. Data were divided into 1990 to 2005 and 2005 to 2020 temporal splits and intensity analysis used to characterize transformation patterns at each interval. Results indicated that growth of the built local climate zones (LCZ) in Bulawayo was faster in the 1990 to 2005 interval than the 2005 to 2020. Transition level intensity analysis showed that growth of built local climate zones was more prevalent in areas with water, low plants and dense forest LCZ in both intervals. There was a westward growth of light weight low rise built LCZ category than eastern direction, which could be attributed to high land value in the latter. Low plants land cover type experienced a large expansion of light weight low rise buildings than the compact low rise, water, and open low-rise areas. The reduction of dense forest was mainly linked to active expansion of low plants in the 2005 to 2020 interval, symbolizing increased deforestation and vegetation clearance. In Bulawayo’s growth, areas where built-up LCZs invade vegetation and wetlands have increased anthropogenic warming (i.e., Surface Urban Heat Island intensities) in the city. This study demonstrates the value of LCZs in among others creating a global urban land use land cover database and assessing the influence of urban growth pattern on urban thermal characteristics.

Predicting the impacts of land use/land cover changes on seasonal urban thermal characteristics using machine learning algorithms

Changes in land use/land cover (LULC) and land surface temperatures (LST) contribute significantly to the formation and intensity of urban heat islands (UHI) effects. The urban thermal field variance index (UTFVI) can effectively describe any city's UHI (thermal characteristics) effect. This study aims to assess and predict the seasonal (summer and winter) UTFVI scenario to evaluate the thermal characteristics of Sylhet city, Bangladesh. Landsat 4–5 TM and 8 OLI images from 1995 to 2020 were used to assess the previous status of LULC and UTFVI and predict the future changes for 2025 and 2030 using cellular automata and artificial neural network machine learning algorithms. Prediction results indicate a substantial increase in urban built-up areas by 42% and 44% in 2025 and 2035, followed by reductions in green cover (21% and 22%), bare land (20% and 21%) and water bodies (1%). The rapid expansion of built-up areas will lead to 13 km2 and 14 km2 stronger UTFVI zones in the predicted years. The study provides effective strategies for mitigating the UTFVI effects by avoiding dense infrastructural development, increasing plantation and water bodies, rooftop gardening and using white colour roofs in construction. The findings of this study will allow the urban planners, policymakers and local government to ensure an eco-friendly, inclusive and sustainable urban development through functional modification and replacement of the LULC distribution depending on the present and future circumstances.

Urban Thermal Characteristics of Local Climate Zones and Their Mitigation Measures across Cities in Different Climate Zones of China

Understanding the urban thermal environment is vital for improving urban planning and strategy development when mitigating urban heat islands. However, urban thermal characteristics of local climate zones (LCZ) are different within cities and most studies lack regional perspective. This study explored surface thermal performances of cities in three urban agglomerations (Jing-Jin-Ji, Yangtze River Delta and Pearl River Delta) in China using MODIS land surface temperature (LST). Besides that, the diurnal and seasonal LST variations of LCZs are also studied. Moreover, the optimal LCZs for better urban cooling are also investigated in this study. Although the thermal distributions of LCZs are different in China, there are still some similar features. Our four key findings were as follows. (1) LCZs in China are well classified, with average overall accuracy of 82% being higher than that in some previous studies. (2) The LST of mid-rise (LCZ 2, 5) is higher than that of high- and low-rise buildings (LCZ 1, 3, 4, 6); and compact buildings are warmer than open buildings (LCZ 1–3 > LST 4–6) in summer of China. That shows both mid-rise and compact buildings are not beneficial to cool urban. In addition, LST variations at daytime and in summer are more significant than nighttime and other seasons. (3) LST differences within LCZs are significant at p < 0.05, and are most significant in Jing-Jin-Ji (JJJ). The LST difference within built types (LCZ 1–10) is more significant than within natural types (LCZ A–G), showing that built types alteration will be more effective for thermal environmental improvement. (4) Under the current population and urban area, increasing greenness and water area in compact high-rise buildings are the most effective strategies for urban cooling in all three urban agglomerations, with the largest reduction in LST of 4.11 K in JJJ. These findings will provide support for thermal environment mitigation, urban planning and sustainable urban development.

Impacts of urban landscape patterns on urban thermal variations in Guangzhou, China

One of the key impacts of rapid urbanization on the environment is the effect of surface urban thermal variations (SUTV). Understanding the effects of urban landscape features on SUTV is crucial for improving the ecology and sustainability of cities. In this study, an investigation was conducted to detect urban landscape patterns and assess their impact on surface temperature. Landsat images: Thematic Mapper was used to calculate land surface temperature (LST) in Guangzhou, the capital city of Guangdong Province in southern China. SUTV zones, including surface urban heat islands (SUHI) and surface urban heat sinks (SUHS), were then empirically identified. The composition and configuration of landscape patterns were measured by a series of spatial metrics at the class and landscape levels in the SUHI and SUHS zones. How both landscape composition and configuration influence urban thermal characteristics was then analysed. It was found that landscape composition has the strongest effect on SUTV, but that urban landscape configuration also influences SUTV. These findings are helpful for achieving a comprehensive understanding of how urban landscape patterns impact SUTV and can help in the design of effective urban landscape patterns to minimize the effects of SUHI.

Determination of Urban Thermal Characteristics on an Urban/Rural Land Cover Gradient Using Remotely Sensed Data

The transformation from natural to impervious surfaces in an urbanization process and the urban heat island (UHI) phenomenon is known to significantly compromise urban environmental quality and has been linked to climate change and associated impacts. Whereas the existence of UHI is common knowledge, the implication of urban land use land cover (LULC) gradient on intra-urban thermal characteristics is often poorly understood. A recent proliferation of remotely sensed datasets offer great potential in understanding the relationship between urban LULCs and their respective thermal characteristics, a critical basis for urban environmental management and designing climate change mitigation measures. This study explores the potential of multispectral remotely sensed dataset in determining the influence of rural/urban LULC gradient on urban thermal characteristics. A rectangular eleven band Landsat 8 image subset was delineated from the central business district to the rural periphery and classified into most dominant LULCs and a corresponding Landsat 8 thermal layer used to determine the LULCs thermal characteristics. Digitized point data was used to determine differences in land surface temperature (LST) over gradient's LULC types. Results showed that there was varied contribution of LULCs to the LST. As expected, the density of built up surfaces and LST decreased towards the city’s periphery while a decline in vegetation density from the periphery led to an increase in LST. These results provide valuable insights into the value of remotely sensed datasets in understanding the implication of intra-urban LULC gradient on LST characteristics. Specifically, the study demonstrates the value of remotely sensed data as aids to sustainable urban environmental planning.

Characterizing fractional vegetation cover and land surface temperature based on sub-pixel fractional impervious surfaces from Landsat TM/ETM+

Estimating the distribution of impervious surfaces and vegetation is important for analysing urban landscapes and their thermal environment. The application of a crisp classification of land-cover types to analyse urban landscape patterns and land surface temperature (LST) in detail presents a challenge, mainly due to the complex characteristics of urban landscapes. In this article, sub-pixel percentage impervious surface areas (ISAs) and fractional vegetation cover (FVC) were extracted from bitemporal Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) data by linear spectral mixture analysis (LSMA). Their accuracy was assessed with proportional area estimates of the impervious surface and vegetation extracted from high-resolution data. A range approach was used to classify percentage ISA into different categories by setting thresholds of fractional values and these were compared for their LST patterns. For each ISA category, FVC, LST, and percentage ISA were used to quantify the urban thermal characteristics of different developed areas in the city of Fuzhou, China. Urban LST scenarios in different seasons and ISA categories were simulated to analyse the seasonal variations and the impact of urban landscape pattern changes on the thermal environment. The results show that FVC and LST based on percentage ISA can be used to quantitatively analyse the process of urban expansion and its impacts on the spatial–temporal distribution patterns of the urban thermal environment. This analysis can support urban planning by providing knowledge on the climate adaptation potential of specific urban spatial patterns.

Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

The urban heat island (UHI) effect resulting from rapid urbanization generally has a negative impact on urban residents. Shijiazhuang, the capital of Hebei Province in China, was selected to assess surface thermal patterns and its correlation with Land Cover Types (LCTs). This study was conducted using Landsat TM images on the mesoscale level and airborne hyperspectral thermal images on the microscale level. Land surface temperature (LST) was retrieved from four scenes of Landsat TM data in the summer days to analyze the thermal spatial patterns and intensity of surface UHI (SUHI). Surface thermal characteristics were further examined by relating LST to percentage of imperious surface area (ISA%) and four remote sensing indices (RSIs), the Normalized Difference Vegetation Index (NDVI), Universal Pattern Decomposition method (VIUPD), Normalized Difference Built-up Index (NDBI) and Biophysical Composition Index (BCI). On the other hand, fives scenes of airborne TASI (Thermal Airborne Spectrographic Imager sensor) images were utilized to describe more detailed urban thermal characteristics of the downtown of Shijiazhuang city. Our results show that an obvious surface heat island effect existed in the study area during summer days, with a SUHI intensity of 2–4 °C. The analyses reveal that ISA% can provide an additional metric for the study of SUHI, yet its association with LST is not straightforward and this should a focus in future work. It was also found that two physically based indices, VIUPD and BCI, have the potential to account for the variation in urban LST. The results concerning on TASI indicate that diversity of impervious surfaces (rooftops, concrete, and mixed asphalt) contribute most to the SUHI, among all of the land cover features. Moreover, the effect of impervious surfaces on LST is complicated, and the composition and arrangement of land cover features may play an important role in determining the magnitude and intensity of SUHI. Overall, the analysis of urban thermal signatures at two spatial scales complement each other and the use of airborne imagery data with higher spatial resolution is helpful in revealing more details for understanding urban thermal environments.

Multiscale analysis of urban thermal characteristics: case study of Shijiazhuang, China

The urban heat island (UHI) effect caused by urbanization generally leads to adverse economic and environmental impacts. Thus, a detailed assessment of the thermal properties over individual land cover types at different spatial resolutions is required to better understand the establishment of UHI. Two scale levels are utilized to examine surface thermal characteristics in the case of Shijiazhuang, China. At the regional level, Landsat TM data are used to extract subpixel impervious surface area (ISA) and to inverse land surface temperature (LST) by means of multiple endmember spectral mixture analysis. Urban thermal characteristics are analyzed by relating the LST to normalized difference vegetation index (NDVI) and ISA. On the other hand, thermal airborne spectrographic imager data, with a high spatial resolution, are employed to describe the spatial distribution of urban thermal patterns at the local level. Results indicate that there is an approximate linear relationship among LST, NDVI, and ISA. In addition, the thermal characteristics over each land cover type are consistent at both levels, suggesting UHI is evident at Shijiazhuang and impervious surface is contributing most to this phenomenon. This confirms that different spatial scales are requested in UHI studies.

Studying the urban thermal environment under a human-biometeorological point of view: The case of a large coastal metropolitan city, Athens

The thermal environment in modern cities has become potentially unfavorable and harmful for its residents, as a result of urbanization and industrialization. Exposure to these extreme thermal conditions increases the heat stress of people in cities considerably. In this context, the present study aims to investigate the urban thermal environment of the large coastal metropolitan city of Athens, in a human-biometeorologically significant way, utilizing the thermo-physiological assessment index PET. The analysis was based on three hour measurements derived from three-year datasets (2006–2009), at 12 monitoring sites located in the urban complex of Athens, on its boundaries and beyond them. The differences of PET values have been investigated in order to attribute urban and exurban thermal characteristics to the considered sites. The frequency and spatial distribution of PET as well as the urban/rural differences of PET have also been analyzed. Finally, a trend analysis has been applied in order to detect possible PET trends by employing long-term recording data (1985–2008). In terms of thermal human-biometeorological conditions, the analysis reveals that among the considered stations, those located inside the urban complex and the industrialized area present urban thermal characteristics, regardless the fact that they are installed either in a park and on a hill or at an open field. The spatial distribution of PET, at 0200 LST, shows a difference of about 3 to 4°C, on the main axis of the city (SSW–NNE) in the summer period, while the difference exceeds 2.5°C in the winter period. In general, cooler (less warm) thermal perception is observed at the north/northeast sites of the city as well as at the areas beyond the eastern boundaries of it. The PET differences between urban and rural sites hold a positive sign, except of those at 0500 LST and at 0800 LST. The highest differences are noted at 1400 LST and the most intense of them is noticed in the summer period (exceeds 5°C). The trend analysis reveals statistically significant increasing heat stress for certain stations and months.

Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery

Studies of urbanization and urban thermal environment are now attracting wide interests among scientists all over the world. This study investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Guangzhou, China utilizing three dates of Landsat TM/ETM+ images acquired in 1990, 2000, and 2005, respectively. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban enlargement. As a key parameter for studying urban thermal characteristics, the land surface temperature (LST) was also retrieved from thermal infrared band of each TM/ETM+ dataset. Based on these parameters, the urban expansion, urban heat island effect and the relationships of LSTs to other biophysical parameters were then analyzed. Results indicated that the area ratio of impervious surface in Guangzhou increased significantly, which grew from 20.56% in 1990, to 34.72% in 2000, and further to 41.12% in 2005, however, the intensity of urban heat island was not always enlarged in observed years. In addition, Geostatistical analyses showed that the mean-centre of the impervious surface was moving towards the northwest during 1990–2005. And correlation analyses revealed that, at the pixel-scale, the association of LSTs to other two variables (vegetation abundance and percent impervious surface) was not straightforward, while LSTs possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional-scale, respectively. This study provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis

As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions.

An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data

Remote sensing data from both Landsat 5 and Landsat 7 systems were utilized to assess urban area thermal characteristics in Tampa Bay watershed of west-central Florida, and the Las Vegas valley of southern Nevada. To quantitatively determine urban land use extents and development densities, sub-pixel impervious surface areas were mapped for both areas. The urban–rural boundaries and urban development densities were defined by selecting certain imperviousness threshold values and Landsat thermal bands were used to investigate urban surface thermal patterns. Analysis results suggest that urban surface thermal characteristics and patterns can be identified through qualitatively based urban land use and development density data. Results show the urban area of the Tampa Bay watershed has a daytime heating effect (heat-source), whereas the urban surface in Las Vegas has a daytime cooling effect (heat-sink). These thermal effects strongly correlated with urban development densities where higher percent imperviousness is usually associated with higher surface temperature. Using vegetation canopy coverage information, the spatial and temporal distributions of urban impervious surface and associated thermal characteristics are demonstrated to be very useful sources in quantifying urban land use, development intensity, and urban thermal patterns.