Development Of Urban Heat Island Research Articles

Assessment of the influence of building parameters on the urban heat island in the districts of Moscow

Large cities, as financial centres, attract a dense adult population, leading to a high demand for housing. This growth requires urban expansion and increased building density, which disrupts the ecosystem and gives rise to a concentrated urban heat island (UHI). In a study conducted in Moscow, a numerical climate simulation model was used to explore the relationship between urban indices, specifically the building height-to-width ratio (H/W), sky view factor (SVF), and UHI intensity. The results indicated significant impacts of both H/W and SVF on UHI. More accurate predictions were achieved by adjusting coefficients in the Oke model using non-linear regression of simulated H/W and heat island intensity. These findings highlight the crucial role of urban morphology in UHI formation and development, providing a scientific basis for mitigating UHI impacts through urban planning strategies. While it is challenging to generalise a formula for calculating UHI intensity due to the diversity of urban forms, our research method offers a valuable approach for similar studies in other cities.

Analyzing the spatio-temporal pattern of urban growth and its influence on urban heat islands in the Sekondi-Takoradi metropolis, Ghana

The rapid urbanization in Sekondi-Takoradi, Ghana has significantly transformed the land cover, resulting in the proliferation of impervious surfaces and a decline in vegetation. However, the influence of this urban growth on the development of urban heat islands (UHIs) in the metropolis remains understudied. This study aimed to fill this research gap by employing Landsat images to explore the influence of urban growth on urban heat islands in the metropolis from 1991 to 2023. The supervised random forest technique was utilized to map the land cover changes. Furthermore, the computed normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), land surface temperature (LST), and urban thermal field variance index (UTFVI) were used to analyze the influence of urban expansion on UHIs. The findings revealed a 63.07 km2 increase in built-up areas and a 60.99 km2 decrease in vegetation cover during the study period. This dramatic land use change led to a 3.1°C rise in mean LST and a 19.38 km2 expansion of areas affected by the UHI effect. The UTFVI analysis further indicated a 33.63 km2 increase in the worst ecological zone due to the temperature rise. Statistical analysis between LST, NDVI, and NDBI revealed significant variability in explaining the intensity of LST and UHI in the metropolis over the study period. The study equips city authorities and planners with the fundamental knowledge needed to prepare a sustainable development plan that alleviates adverse effects of urban growth and elevated temperature-related issues. Also, the findings contribute to the global efforts in promoting more livable and climate-resilient urban environments.

Harnessing Machine Learning Algorithms to Model the Association between Land Use/Land Cover Change and Heatwave Dynamics for Enhanced Environmental Management

As we navigate the fast-paced era of urban expansion, the integration of machine learning (ML) and remote sensing (RS) has become a cornerstone in environmental management. This research, focusing on Silchar City, a non-attainment city under the National Clean Air Program (NCAP), leverages these advanced technologies to understand the urban microclimate and its implications on the health, resilience, and sustainability of the built environment. The rise in land surface temperature (LST) and changes in land use and land cover (LULC) have been identified as key contributors to thermal dynamics, particularly focusing on the development of urban heat islands (UHIs). The Urban Thermal Field Variance Index (UTFVI) can assess the influence of UHIs, which is considered a parameter for ecological quality assessment. This research examines the interlinkages among urban expansion, LST, and thermal dynamics in Silchar City due to a substantial rise in air temperature, poor air quality, and particulate matter PM2.5. Using Landsat satellite imagery, LULC maps were derived for 2000, 2010, and 2020 by applying a supervised classification approach. LST was calculated by converting thermal band spectral radiance into brightness temperature. We utilized Cellular Automata (CA) and Artificial Neural Networks (ANNs) to project potential scenarios up to the year 2040. Over the two-decade period from 2000 to 2020, we observed a 21% expansion in built-up areas, primarily at the expense of vegetation and agricultural lands. This land transformation contributed to increased LST, with over 10% of the area exceeding 25 °C in 2020 compared with just 1% in 2000. The CA model predicts built-up areas will grow by an additional 26% by 2040, causing LST to rise by 4 °C. The UTFVI analysis reveals declining thermal comfort, with the worst affected zone projected to expand by 7 km2. The increase in PM2.5 and aerosol optical depth over the past two decades further indicates deteriorating air quality. This study underscores the potential of ML and RS in environmental management, providing valuable insights into urban expansion, thermal dynamics, and air quality that can guide policy formulation for sustainable urban planning.

Mitigating urban heat and air pollution considering green and transportation infrastructure

Global urbanization is causing an increase in population and transportation along with a reduction of green spaces. This phenomenon is leading to the development of Urban Heat Island (UHI) and Urban Pollution Island (UPI) effects, negatively impacting the urban environment. Numerous mitigation strategies have been proposed to reduce heat and air pollution. However, the combined impact of green and transportation infrastructure and their potential to mitigate heat and air pollution remains partially understood. This review aims to contribute by systematically investigating studies on mitigation strategies for urban green and transportation infrastructure from 2003 to 2023. These strategies are classified into two types: green infrastructure-related (greenery, green roofs, and green walls) and transportation-related (transportation fuel, transportation networks, and transportation organization systems). The findings are presented under five aspects: (1) Most research on transportation infrastructure adopts qualitative research methods, whereas research on green infrastructure tends to adopt quantitative methods; (2) Developed countries prioritize upgrading their transportation fuel, while developing countries remain inclined towards developing urban green spaces; (3) In subtropical and temperate zones, green roofs and green walls may cool the local ambient (within 1 m above the surface) by up to 10℃, whereas the cooling effect in other climate zones is within 5℃; (4) More focus was put on reducing the surface temperature rather than the air temperature. Green roofs and green walls are found to cool the former 2–3 times more than the latter; (5) Green infrastructure in the subtropical zone is 1.2 to 2 times more effective at adsorbing gaseous pollutants than in the temperate zone. This review can assist policymakers, urban planners and researchers in effectively mitigating urban heat and air pollution, and guide future research endeavors.

The spatial and temporal evolution of surface temperature in the main urban area of Hangzhou from 1990 to 2020 based on GEE

In this study, remote sensing (RS), geographic information system (GIS), Google Earth Engine (GEE), and mathematical analysis methods are applied to study the evolution and development trend of land surface temperature in Hangzhou. The GEE platform used in this study, which can fit remote sensing images of multiple regions under different spatial and temporal conditions, has the advantages of wide range and timeliness, and enables the study area to cover the entire Hangzhou city. The purpose of this study is to study the evolution of surface temperature in Hangzhou from 1990 to 2020 using a combination of remote sensing inversion and GIS spatial analysis, and to combine a variety of geostatistical analysis methods to specifically study the trend of surface temperature change and urban heat island development in Hangzhou in order to improve the local people’s life and local environment.

Spatio-temporal characteristics of urban heat Island of Jakarta metropolitan

Around 151 million people (56%) of Indonesia's population currently live in cities. When the inner city sees substantially warmer temperatures than neighboring rural areas, a city experiences the urban heat island (UHI) effect. For both day and night time, the inner city within the Jakarta area tends to have a higher land and surface air temperature in comparison to its surroundings. Using available remote sensing satellite data (MODIS and Landsat) and surface meteorological observations, this research detects and defines the spatiotemporal land surface (SUHI) development in the Jakarta agglomeration region. In this paper, how the intensity of land surface (SUHI) and surface air UHI (AUHI) is measured, the trend assessment of 20 years SUHI area, as well as how land use change contributes to UHI development in the Jakarta Metropolitan area, is discussed. The results show that the SUHI intensity is approximately 3°C–6°C and AUHI is approximately 1°C–2.5 °C. This paper offers a comprehensive feature of UHI in Greater Jakarta as a research novelty, which is getting worse in response to global warming.

Differences in urban heat island and its driving factors between central and new urban areas of Wuhan, China.

Urban heat island (UHI) is one of the important effects of urbanization on built environment. Land surface temperature data was taken from moderate-resolution imaging spectroradiometer (MODIS) to investigate the long-term spatiotemporal patterns of UHI in Wuhan during 2001~2018 and, the UHI intensity changes of built-up land in 13 administrative regions in Wuhan were analyzed. Furthermore, 34 spatial error models and 34 ordinary least squares models were established and compared. Spatial error models showed good fitting effect, which were used to determine the influence of normalized difference vegetation index (NDVI), normalized difference building index (NDBI), and social-economic factors (population and nighttime light) on UHI intensity in central urban area and new urban area. The explanatory power changes of these four indicators during 2001~2018 were explored as well. The average UHI intensity in 2014~2018 has increased by about 0.45 °C compared to that in 2001~2005. NDBI is the most dominant factor contributing to the increase in temperature. The impact of NDVI on UHI intensity changes from negative to positive, and the impact of NDBI on UHI intensity in central urban area is weakened during 2001-2018. Social-economic factors have a greater impact on new urban area than on central urban area. These findings show the effects and the explanatory power changes of driving factors during 18 years, which can provide a better understanding of the formation and development of UHI and support for the future urban planning of Wuhan.

Investigating the Impact of Weather Conditions on Urban Heat Island Development in the Subtropical City of Hong Kong

Subtropical monsoon climates, high-density and heterogeneous urban built environments, as well as coastal–mountainous geographical environments influence the development of urban heat island (UHI) effects in Hong Kong. For better weather control of in situ observations and spatial analysis of UHI effects, it is necessary to quantitatively understand the influence of weather conditions on UHI development in Hong Kong and establish weather-based UHI estimation models. Meteorological records of four urban stations, one rural reference station, and one wind reference station at an hourly interval during the period of 2002–2012 were collected from Hong Kong observatory. A frequency analysis of the mean values of multiple meteorological elements and UHI parameters in urban stations was conducted to examine the prevailing and critical weather conditions, as well as the associated UHI conditions in Hong Kong. Multiple Linear Regression (MLR) was used to estimate the daily maximum UHI intensity (UHImax) based on a set of meteorological elements including cloud amount, wind speed, wind direction, relative humidity, and air temperature, as well as a UHI parameter of the daily maximum UHI intensity of the previous day (UHIpre-max). The results showed that MLR-based models can explain 33% and 56% variations of the UHImax in the summer and the whole year, respectively. The relative importance of each meteorological element on UHI development differed in the summer and annual periods, and the UHImax tended to be intensified under high temperature conditions in the summer.

Observations of the urban boundary layer in a cold climate city

Cold environment supports a large diversity of local climates. Among them, urban climates in northern cities stand out for their pronounced warm temperature anomaly known as the Urban Heat Island (UHI). UHI in northern cities has been already studies through satellite images and in-situ observations in the urban canopy layer (UCL). Yet, the vertical structure of the urban atmospheric boundary layer (UBL) has not been studied there. This work presents new observations of UBL in Nadym – a sub-Arctic Siberian city. During several intensive observing periods we run simultaneous registration of urban and rural meteorological parameters with unmanned drones, a microwave temperature profiler and a dense network of ground-based sensors. The data analysis reveals details of UHI development in the UCL and UBL, and links together horizontal urban-rural canopy-layer temperature differences, boundary layer stability, and UHI vertical extent. We show that during strong temperature inversions, UBL is less stratified than its rural counterpart, but it still remains very thin and limited in height by a few tens of meters. The observations disclose that the ground-based (50 m – 100 m above ground) temperature inversion is one of the strongest control factors for UHI in cold climate conditions in winter.

Applying a diagnostic equation for maximum urban heat island intensity based on local climate zones for Guangzhou, China

The Urban Heat Island (UHI) is a widely studied phenomenon, characterized by unique spatiotemporal variations depending on urban structure. Seeking a simple and rapid method to monitor the Urban Heat Island Intensity (UHII) for local urban area with multiple inner morphology is essential for energy saving, citizen health, and urban planning. Hence, this study proposed a diagnostic equation for daily maximum urban heat island intensity (UHIImax) based on routine meteorological data and basic urban properties. The applicability of equation, previously proposed by European scholars, was evaluated based on Local Climate Zone (LCZ) scheme by a long-term temperature observation experiment conducted in Guangzhou. Overall, the underestimation of UHIImax was caused by LCZ1,2,3,4, in which the morphological parameters were outside the application range of the original equation. Then, a revised equation was proposed by adding the impervious surface fraction (ISF) in morphological parameters based on the spatiotemporal variance of UHII for different LCZ. The revised equation was evaluated against a year dataset and revealed a higher accuracy than the original one with a decrease of RMSE and MEAE at 0.4K, 0.15K, an increase of dr at 0.1. Moreover, the efficiency of the equations for all the seasons and LCZs were elucidated. In summary, the results can be used as a tool for monitoring the development of UHI in outdoor temperature studies.

Analysis of urban Heat Island intensity through air mass persistence: A case study of four United States cities

In conjunction with the ongoing rise in global air temperature, there is evidence to suggest that mid-latitude synoptic air masses have changed in frequency and persistence. The research presented here focuses on an analysis of urban heat island (UHI) intensity through the period of synoptic-scale air mass stagnation for four UHI-prone United States cities. It is theorized that the thermal inertia associated with a stagnant air mass conducive to UHI development causes an intensification of the urban-rural temperature difference through time. Results indicate that UHI intensification is responsive to more than just the thermal characteristics of the respective air mass in place. While the magnitude of UHI was found to be smallest under a cool, dry air mass, it generally intensifies with persistence. Conversely, commonly associated with the greatest UHI intensity, a warm, moist air mass exhibits little change in UHI intensity or even a de-intensification with persistence. The warm, moist air masses that are conducive to a stronger UHI appear to be increasing in frequency, partly due to greater persistence. However, somewhat encouraging is that the results here do not show UHI intensification through the period of their persistence.

Mapping daytime thermal patterns of Bologna municipality (Italy) during a heatwave: A new methodology for cities adaptation to global climate change

Remotely sensed Land Surface Temperature (LST) is widely used to characterize Surface Urban Heat Island (SUHI) intensity and spatial variability. SUHI may differ significantly from the Urban Heat Island (UHI), which is related to air temperature and is more representative of human wellbeing. The lack of information and results on UHI development is due to the difficulty in having measurements with high spatial density within the city and the uncertainties in finding relationships between air and surface temperatures. Characterizing UHI is fundamental when dealing with human thermal wellbeing especially when extreme events occur. A new index, named Urban Heatwave Thermal Index (UHTI), was presented here to quantify daytime air temperature variability patterns in an urban environment during a meteorological heatwave. UHTI integrates a) air temperature recorded by local sensors; b) structural microclimatic Envi-met fluidodynamic modeling simulations; and c) remotely sensed environmental indicators. UHTI is a reliable representation of thermal criticalities in the city for its inhabitants. A case study on Bologna (Italy) municipality is presented. Moreover, UHTI was calculated and compared with the Urban Thermal Field Variance Index (UTFVI), commonly used for urban climate characterization. Results showed a high degree of correlation (R2 = 0.795) between the two indexes; residual mapping and hot-spot detection indicated that their biggest differences are next to dense urban fabric areas like historical centers and water body areas.

Temporal Evolution of Urban Heat Island and Quantitative Relationship with Urbanization Development in Chongqing, China

Urban development always has a strong impact on the urban thermal environment, but it is unclear to what extent urbanization factors influence urban heat island intensity (UHII) in mountainous cities, and fewer studies have been conducted on the trends of long-term UHII in mountainous cities. Chongqing, as the only municipality directly under the central government in Southwest China and a typical mountainous city, is chosen as the case study. This study analyzed the interannual and seasonal variations of UHII based on the data from meteorological stations in Chongqing from 1959 to 2018 using the least-squares method and the Mann–Kendall test, and explored the relationship between urbanization factors (urban resident population, gross domestic product (GDP), fixed investments, and gross industrial output value) and UHII. The results show that the increasing rates of temperature in urban areas of Chongqing are significantly higher than those in rural areas affected by urbanization. Using the Mann–Kendall test, it is found that almost all abrupt temperature changes in Chongqing occurred after the rapid urbanization of Chongqing in the 21st century. The annual mean UHII increased from 0.1 °C to 1.5 °C during the study period, with summer making the largest contribution. It is also found that the UHII in Chongqing has increased year by year, especially after the 1980s. The increasing rates of UHII are larger at night and smaller during the day. The increasing trends of nighttime UHII are statistically significant, while those of daytime UHII are not. In addition, UHII and urbanization factors are found to be correlated using the grey relational analysis (GRA). Eventually, a comprehensive UHII index and a comprehensive urbanization index are constructed using principal component analysis (PCA). A tertiary regression model of UHII and urbanization index is established, which reflects that the UHII in Chongqing will continue to grow rapidly with the development of the city.

Observation and Simulation of Low-Level Jet Impacts on 3D Urban Heat Islands in Beijing: A Case Study

Abstract In this study, we focused on the impacts of the planetary boundary layer (PBL) low-level jet (LLJ) on the horizontal distribution, vertical development, and 3D structure of urban heat island (UHI). Observational datasets were collected from 224 automatic weather stations (AWSs), and an intensive sounding experiment was conducted in Beijing from 28 August to 2 September 2016. Three-dimensional simulations were operated by the Weather Research and Forecasting (WRF) Model. The results show the following: Ri was smaller than 0.25 at both urban and suburban stations near the surface when the LLJ was present. Through turbulent mixing, the LLJ extended the horizontal distribution of the canopy UHI downwind and increased the total UHI area by approximately 1 × 103 km2. The temperature lapse rate in the urban area was 0.7°C (100 m)−1 with the LLJ, twice that in the absence of an LLJ. The jet enhanced the vertical mixing above the urban area, accompanied by a near-surface TKE up to 0.52 m2 s−2, elevating the vertical UHI development height to 200 m. The LLJ is capable of increasing the temperature of the downwind urban area by a maximum of 8.5°C h−1 through warm advection. The temperature advection in the upper air caused by the LLJ also tilted the 3D UHI structure as a plume. Results reproduced the process by which the LLJ affect the 3D UHI structure through turbulence and advection, and could also provide ideas regarding the influence of the LLJ in other PBL processes.

Earth observation data sets in monitoring of urbanization and urban heat island of Delhi, India

Rapid urbanization and land use transformation coupled with climate change impact are witnessed for development urban heat island worldwide and make it major environmental concerns for human health. National Capital Region (NCR) is one of the fast sprawling National Capital city of India. The aim of the present study is to explore the spatial changes in major biophysical parameters of city over last 20 years from 2000 to 2020 using satellite data. The spatial variation in the land surface temperature and its relation with Land use, NDVI and Built-up area were evaluated and discussed in the present work. The major changes were observed in minimum and maximum temperature of the city, in 2000 minimum temperature was 23.20 °C and maximum 34.85 °C, which increased to 26.31 and 39.92 °C in 2010; and 31.70 to 44.74 °C in 2020 . Normalized differential vegetation index (NDVI) decrease from 82 to 62%, Non-Vegetated area has reduced to 62% from 82% due to fast urbanization and land transformation in last two decades. Barren and fallow land also reduces about 27% in last two decades and built-up area also shown increasing trend . The spatial changes in biophysical parameter of the city clearly indicated that NDVI, NDBI and Land use/land cover charges are the main driving forces for development of urban heat island in the city and many health issues related to heat waves are already reported in the city along with many other negative impacts on natural landscape and resources. The observations from present work will be very useful scientific information to understand the causes of elevated land surface temperature and mitigation measures. Results could be used by policy makers to develop the suitable model for long term sustainability of the cities.

Spatial Variations of Urban Heat Island Development in Khulna City, Bangladesh: Implications for Urban Planning and Development

Spatial Variations of Urban Heat Island Development in Khulna City, Bangladesh: Implications for Urban Planning and Development

Estimation of anthropogenic heat release in Mexico City

The urban heat island (UHI) is a phenomenon that appears in cities due to the alteration of the energy balance caused by the drastic land use change. A factor that can contribute to its development is the energy generated by the city inhabitants, or the anthropogenic heat flux (QF). Therefore, the determination of this component can improve the predictability of UHI development and variability. The objective of this work was to estimate the main sources of anthropogenic heat flux, based on a vehicle classification (taxis, cars, minibuses and buses), surveys of electricity consumption and population density in Mexico City. The anthropogenic heat determination is based on a simple distribution of heat generated by vehicles, buildings and people. Vehicle classification was made through video analysis and the vehicle flow was also accounted for with sensors at the road level, within a radius of 1 km. The consumer surveys were applied to businesses and homes, and with the support of basic geostatistical areas the population density was determined. The analysis showed that the highest heat emission occurs from 15:00 to 21:00 h. This heat flux in average was not significant when compared to net radiation. However, anthropogenic heat flux generation in dense areas of Mexico City, can exceed 75 W·m−2 for certain times of the day, while the inventory carried out QF averaged 24.7 W·m−2 at San Agustin, in the historical center. With the obtained results, also a standard car was idealized, and the electricity consumption profiles of some sectors were generated, which will allow obtaining the heat flux more easily and quickly. According to the results, it is advisable to integrate the anthropogenic heat flux component into the energy balance for future studies of the UHI.

Earth Observation Data Exploitation in Urban Surface Modelling: The Urban Energy Balance Response to a Suburban Park Development

Cities are developing rapidly as an increasing percentage of the global population resides in urban areas. In the face of climate change, the sustainable development of cities is crucial for the well-being and safety of urban populations. The potential of planning interventions towards improving of urban resilience can be evaluated based on methodological approaches used in the domain of urban climate. In this study, we present how Earth Observation (EO) can be systematically used to evaluate urban planning interventions, based on Urban Surface Models (USM) simulations. More specifically, the impact of a suburban park development in Heraklion, Crete, was assessed based on simulations of the USM SUEWS (Surface Urban Energy and Water Balance Scheme), which was forced by EO data. Multi-source satellite data were analyzed to provide information on urban form, highlighting the importance of EO data in evaluating the environmental sustainability potential of urban planning interventions. The modifications caused by this planning intervention to surface energy fluxes were simulated. The scale (102 m) and the type (no-use vegetated area changed to recreational vegetated) of the intervention triggered minor responses in the Urban Energy Balance (UEB) at neighborhood scale, since the change of the relevant surface fluxes was not greater than 10 W m−2, on average, assuming no irrigation and no important changes in soil moisture. However, the planned substitution of grass and bare soil with paved surfaces and trees was found to increase the overall net change in heat storage, therefore contributing to the urban heat island development.

Seasonal Contrast and Interactive Effects of Potential Drivers on Land Surface Temperature in the Sichuan Basin, China

Little is known about the seasonal heterogeneity of land surface temperature (LST) and the interaction relationship between potential drivers in Sichuan Basin, China. In this study, based on exploring the spatial heterogeneity of LST in Sichuan Basin, China, multi-source remote sensing data as potential drivers were selected and a Geo-detector model was applied to analyze the main drivers and the interactive relationship between drivers on LST during different seasons. The results showed that the high-temperature areas in Sichuan Basin in different seasons all appeared in the cities near the high mountains on the edge of the basin. This phenomenon was summarized as “sinking heat island” by us. From the driving factors, the biophysical parameters (DEM, SLOPE and NDVI) had the greatest impact on LST in each season, reaching the peak in the transition season. The climate parameters (WIND, HUM, PRE and TEM) and socioeconomic parameters (LIGHT, POP and ROAD) also had a certain impact on LST. The influence of a single landscape parameter (SHDI, PD, LPI, ED and LSI) on LST is limited. From the effect of factor interaction on LST, the interaction of biophysical parameters, climatic parameters and landscape parameters from summer to the transitional season was strengthened obviously, and it showed a downward trend in the winter; in contrast, the socioeconomic parameters showed the opposite characteristics, indicating that the interaction between human activities and other factors affected LST more obviously in the winter. The results of this study are not only valuable for understanding the spatial features of LST but also important for formulating mitigation strategies and sustainable development of urban heat island in Sichuan Basin.

Tailored methods for mapping urban heat islands in Greater Cairo Region

Globally, there is a rapid development of urban heat island (UHI) detection tools, and their results can be accepted regardless of their accuracy in measuring the real impact of the phenomenon. In this study, we investigated various UHI measuring tools and analysed their findings to better interpret their reliability. The tools in the current research adopted remote sensing and field measurements including those using air temperature monitors and thermal imaging technologies to examine the multiple urban structures of four cases in the Greater Cairo Region. The results showed that UHI detection by remote sensing analysis was affected by normalised difference vegetation index. In contrast, field measurements were also influenced by the albedo of morphological materials present. The conclusions revealed that the tools do not provide the same results and indicate that studying UHIs in the built environment differs from investigating it in a two-dimensional layer using remote sensing.