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All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive, safe, resilient and sustainable”. In order to monitor progress regarding SDG 11, there is a need for proper indicators, representing different aspects of city conditions, obviously including the Land Cover (LC) changes and the urban climate with its most distinct feature, the Urban Heat Island (UHI). One of the aspects of UHI is the Surface Urban Heat Island (SUHI), which has been investigated through airborne and satellite remote sensing over many years. The purpose of this work is to show the present potential of Google Earth Engine (GEE) to process the huge and continuously increasing free satellite Earth Observation (EO) Big Data for long-term and wide spatio-temporal monitoring of SUHI and its connection with LC changes. A large-scale spatio-temporal procedure was implemented under GEE, also benefiting from the already established Climate Engine (CE) tool to extract the Land Surface Temperature (LST) from Landsat imagery and the simple indicator Detrended Rate Matrix was introduced to globally represent the net effect of LC changes on SUHI. The implemented procedure was successfully applied to six metropolitan areas in the U.S., and a general increasing of SUHI due to urban growth was clearly highlighted. As a matter of fact, GEE indeed allowed us to process more than 6000 Landsat images acquired over the period 1992–2011, performing a long-term and wide spatio-temporal study on SUHI vs. LC change monitoring. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations (calibration problems related to LST determination from Landsat imagery were evidenced), pave the way for a possible global service on SUHI monitoring, able to supply valuable indications to address an increasingly sustainable urban planning of our cities.

With rapid urbanization, population growth and anthropogenic activities, an increasing number of major cities across the globe are facing severe urban heat islands (UHI). UHI can cause complex impacts on the urban environment and human health, and it may bring more severe effects under heatwave (HW) conditions. In this paper, a holistic review is conducted to articulate the findings of the synergies between UHI and HW and corresponding mitigation measures proposed by the research community. It is worth pointing out that most studies show that urban areas are more vulnerable than rural areas during HWs, but the opposite is also observed in some studies. Changes in urban energy budget and major drivers are discussed and compared to explain such discrepancies. Recent studies also indicate that increasing albedo, vegetation fraction and irrigation can lower the urban temperature during HWs. Research gaps in this topic necessitate more studies concerning vulnerable cities in developing countries. Moreover, multidisciplinary studies considering factors such as UHI, HW, human comfort, pollution dispersion and the efficacy of mitigation measures should be conducted to provide more accurate and explicit guidance to urban planners and policymakers.

Due to its importance, the field of urban heat islands (UHIs) has witnessed an increasing trend of interest over time to many scientists on the international level. Consequently, large number of papers has been published aiming at reviewing the literature about UHIs internationally. However, this topic started to attract attention of researchers in the Arab world only relatively recently. Hence, the major goal of the present endeavor is to narratively review the literature about UHIs in the Arab world. The focus is on two significant aspects of UHIs: (1) determination of UHIs and (2) assessment of the impacts of UHIs. The results of this review exposed to the surface the historical development, current status, and future prospects of literature about determination and assessment of the impacts of UHIs in the Arab world. The research about this specific topic in the Arab world can be described as still in its infancy stage with huge gaps still exist and more further studies are needed.

Hanoi City of Vietnam changes quickly, especially after its state implemented its Master Plan 2030 for the city’s sustainable development in 2011. Then, a number of environmental issues are brought up in response to the master plan’s implementation. Among the issues, the Urban Heat Island (UHI) effect that tends to cause negative impacts on people’s heath becomes one major problem for exploitation to seek for mitigation solutions. In this paper, we investigate the land surface thermal signatures among different land-use types in Hanoi. The surface UHI (SUHI) that characterizes the consequences of the UHI effect is also studied and quantified. Note that our SUHI is defined as the magnitude of temperature differentials between any two land-use types (a more general way than that typically proposed in the literature), including urban and suburban. Relationships between main land-use types in terms of composition, percentage coverage, surface temperature, and SUHI in inner Hanoi in the recent two years 2016 and 2017, were proposed and examined. High correlations were found between the percentage coverage of the land-use types and the land surface temperature (LST). Then, a regression model for estimating the intensity of SUHI from the Landsat 8 imagery was derived, through analyzing the correlation between land-use composition and LST for the year 2017. The model was validated successfully for the prediction of the SUHI for another hot day in 2016. For example, the transformation of a chosen area of 161 ha (1.61 km2) from vegetation to built-up between two years, 2016 and 2017, can result in enhanced thermal contrast by 3.3 °C. The function of the vegetation to lower the LST in a hot environment is evident. The results of this study suggest that the newly developed model provides an opportunity for urban planners and designers to develop measures for adjusting the LST, and for mitigating the consequent effects of UHIs by managing the land use composition and percentage coverage of the individual land-use type.

Presently, the urban heat island (UHI) phenomenon, and its adverse impacts, are becoming major research foci in various interrelated fields due to rapid changes in urban ecological environments. Various cities have been investigated in previous studies, and most of the findings have facilitated the introduction of proper mitigation measures to overcome the negative impact of UHI. At present, most of the mountain cities of the world have undergone rapid urban development, and this has resulted in the increasing surface UHI (SUHI) phenomenon. Hence, this study focuses on quantifying SUHI in Kandy City, the world heritage tropical mountain city of Sri Lanka, using Landsat data (1996 and 2017) based on the mean land surface temperature (LST), the difference between the fraction of impervious surfaces (IS), and the fraction of green space (GS). Additionally, we examined the relationship of LST to the green space/impervious surface fraction ratio (GS/IS fraction ratio) and the magnitude of the GS/IS fraction ratio. The SUHI intensity (SUHII) was calculated based on the temperature difference between main land use/cover categories and the temperature difference between urban-rural zones. We demarcated the rural zone based on the fraction of IS recorded, <10%, along with the urban-rural gradient zone. The result shows a SUHII increase from 3.9 °C in 1996 to 6.2 °C in 2017 along the urban-rural gradient between the urban and rural zones (10 < IS). These results relate to the rapid urban expansion of the study areas from 1996 to 2017. Most of the natural surfaces have changed to impervious surfaces, causing an increase of SUHI in Kandy City. The mean LST has a positive relationship with the fraction of IS and a negative relationship with the fraction of GS. Additionally, the GS/IS fraction ratio shows a rapid decline. Thus, the findings of this study can be considered as a proxy indicator for introducing proper landscape and urban planning for the World Heritage tropical mountain city of Kandy in Sri Lanka.

Urban heat islands (UHI) are a well-known phenomenon adversely affecting human health and urban environments. The worldwide COVID-19 lockdown in 2020 provided a unique opportunity to investigate the effects of decreased emission of air pollution and anthropogenic heat flux (AHF) on UHI. Although studies have suggested that reduced AHF during lockdown decreased atmospheric UHI (AUHI) and surface UHI (SUHI), these results contain inherent uncertainties due to unaccounted weather variability and urban-rural dynamics. Our study comprehensively analyzes the impact of the COVID-19 lockdown on AUHI and SUHI in Prague, Czechia. By selecting days with similar weather conditions, we examined changes in mean SUHI using MODIS satellite images and in AUHI based on air temperature from Prague weather stations for the Lockdown period during March–April 2020 versus a Reference period from March–April 2017–2019. Our results show that, in comparison to the Reference period, the Lockdown period was associated with a 15% (0.1 °C) reduction of SUHI in urbanized areas of Prague and a 0.7 °C decline in AUHI in the city center. Additionally, the observed decreases in satellite-based aerosol optical depth and nitrogen dioxide by 12% and 29%, respectively, support our hypothesis that the weakened UHI effects were linked to reduction in anthropogenic activities during the lockdown. Revealing the largest decrease of mean SUHI magnitude around the periphery of Prague, which has predominantly rural land cover, our study emphasizes the need to consider the effects of urban-rural dynamics when attributing changes in SUHI to AHF. Our findings provide additional insights into the role of reduced anthropogenic activities in UHI dynamics during the COVID-19 lockdown and offer policymakers a comprehensive understanding of how the complex interaction between urban and rural microclimate dynamics influences the SUHI phenomenon.

This paper attempts to illustrate the complexity of thermal infrared (TIR) data analysis for urban heat island studies. While a certain shift regarding the use of correct scientific nomenclature (using the term “surface urban heat island”) could be observed, the literature is full of incorrect conclusions and results using erroneous terminology. This seems to be the result of the ease of such literature implicitly suggesting that “warm surfaces” result in “high air temperatures”, ultimately drawing conclusions for urban planning authorities. It seems that the UHI is easy to measure, easy to explain, easy to find, and easy to illustrate—simply take a TIR-image. Due to this apparent simplicity, many authors seem to jump into UHI studies without fully understanding the nature of the phenomenon as far as time and spatial scales, physical processes, and the numerous methodological pitfalls inherent to UHI studies are concerned. This paper attempts to point out some of the many pitfalls in UHI studies, beginning with a proper correction of longwave emission data, the consideration of the source area of a thermal signal in an urban system—which is predominantly at the roof level—demonstrating the physics and interactions of radiation and heat fluxes, especially in relation to the importance of urban storage heat flux, and ending with an examination of examples from the Basel study area in Switzerland. Attention is then turned to the analysis of spatially distributed net radiation in the day- and at nighttime as a minimum requirement for urban heat island studies. The integration of nocturnal TIR images is notably recommended, as satellite data and the UHI-phenomenon cover the same time period.

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (T[sub.air]), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside T[sub.air] climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in T[sub.air] and LST during the summer months from 1984 to 2023, with a notable positive correlation between T[sub.air] and LST across both datasets. MODIS data exhibit a stronger correlation (R[sup.2] = 0.879) compared to Landsat (R[sup.2] = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects.

Context Cities have elevated temperatures compared to rural areas, a phenomenon known as the “urban heat island”. Higher temperatures increase the risk of heat-related mortality, which will be exacerbated by climate change. Objectives To examine the impact of climate change and urban growth on future urban temperatures and the potential for increased heat stress on urban residents. Methods We conducted a systematic review of scientific articles from Jan 2000 to May 2016. Results The majority (n = 49, = 86%) of studies examined climate change and the urban heat island in isolation, with few (8) considering their combined effect. Urban growth was found to have a large impact on local temperatures, in some cases by up to 5 °C in North-east USA. In some locations climate change increased the heat island, such as Chicago and Beijing, and in others decreased it, such as Paris and Brussels. When the relative impact of both factors was considered, the temperature increase associated with the urban heat island was always higher. Few studies (9) considered heat stress and its consequences for urban populations. Important contributors to urban temperatures, such as variation in urban density and anthropogenic heat release, were often excluded from studies. Conclusions We identify a need for an increased research focus on (1) urban growth impact on the urban heat island in climate change studies; (2) heat stress; and, (3) variation in urban density and its impacts on anthropogenic heat. Focussing on only one factor, climate change or urban growth, risks underestimating future urban temperatures and hampering adaptation.

Urban and building typologies have a serious impact on the urban climate and determine at large the magnitude of the urban overheating and urban heat island intensity. The present study aims to analyze the impact of various city typologies and urban planning characteristics on the mitigation of the urban heat island. The effect of the building height, street width, aspect ratio, built area ratio, orientation, and dimensions of open spaces on the distribution of the ambient and surface temperature in open spaces is analyzed using the Sydney Metropolitan Area as a case study for both unmitigated and mitigated scenarios. Fourteen precincts are developed and simulated using ENVI-met the simulation tool. The ambient temperature, surface temperature, and wind speed are extracted. The parameter ‘Gradient of the Temperature Decrease along the Precinct Axis’ (GTD) is introduced to study the cooling potential of the various precincts. In the mitigated precincts, the GTD ranges between 0.01 K/m to 0.004 K/m. In the non-mitigated precincts, the GTD ranges between 0.0093 K/m to 0.0024 K/m. A strong correlation is observed between the GTD of all the precincts, with and without mitigation, and their corresponding average aspect ratio, (Height of buildings to Width of streets). The higher the aspect ratio of the precinct, the lower the cooling potential. It is also observed that the higher the Built Area Ratio of the precincts, the lower the cooling contribution of the mitigation measures.