Search Results (856)

Amid accelerating climate change, intensifying urban heat island effects, and rising public demand for livable, walkable streets, there is an urgent practical need for interpretable and actionable evidence on streetscape quality. Yet, research on streetscape quality has often relied on single data sources and linear models, limiting insight into multidimensional perception; evidence from temperate monsoon cities remains scarce. Using Tianjin’s main urban area as a case study, we integrate street-view imagery with remote sensing imagery to characterize satellite-derived environmental indicators at the point scale and examine the following five perceptual outcomes: comfort, aesthetics, perceived greenness, summer heat perception, and willingness to linger. We develop a three-step interpretable assessment, as follows: Elastic Net logistic regression to establish directional and magnitude baselines; Generalized Additive Models with a logistic link to recover nonlinear patterns and threshold bands with Benjamini–Hochberg false discovery rate control and binned probability calibration; and Shapley additive explanations to provide parallel validation and global and local explanations. The results show that the Green View Index is consistently and positively associated with all five outcomes, whereas Spatial Balance is negative across the observed range. Sky View Factor and the Building Visibility Index display heterogeneous forms, including monotonic, U-shaped, and inverted-U patterns across outcomes; Normalized Difference Vegetation Index and Land Surface Temperature are likewise predominantly nonlinear with peak sensitivity in the midrange. In total, 54 of 55 smoothing terms remain significant after Benjamini–Hochberg false discovery rate correction. The summer heat perception outcome is highly imbalanced: 94.2% of samples are labeled positive. Overall calibration is good. On a standardized scale, we delineate optimal and risk intervals for key indicators and demonstrate the complementary explanatory value of street-view imagery and remote sensing imagery for people-centered perceptions. In Tianjin, a temperate monsoon megacity, the framework provides reproducible, actionable, design-relevant evidence to inform streetscape optimization and offers a template that can be adapted to other cities, subject to local calibration. Full article

Urban Heat Islands (UHIs) are urbanized areas that experience significantly higher temperatures than their surroundings, contributing to thermal discomfort, increased air pollution, heightened public health risks, and greater energy demand. In Bhutan, where urban expansion is concentrated within narrow valley systems, the formation and intensification of UHIs present emerging challenges for climate-resilient urban development. Thimphu, in particular, is experiencing rapid urban growth and densification, making it highly susceptible to UHI effects. Therefore, the aim of this study was to evaluate and simulate UHI conditions for Thimphu Thromde. We carried out the simulation using a GIS, multi-temporal Landsat imagery, and an Artificial Neural Network model. Land use and land cover classes were mapped through supervised classification in the GIS, and surface temperatures associated with each class were derived from thermal bands of Landsat data. These temperature values were normalized to identify existing UHI patterns. An Artificial Neural Network (ANN) model was then applied to simulate future UHI distribution under expected land use change scenarios. The results indicate that, by 2031, built-up areas in Thimphu Thromde are expected to increase to 72.82%, while vegetation cover is projected to decline to 23.52%. Correspondingly, both UHI and extreme UHI zones are projected to expand, accounting for approximately 14.26% and 6.08% of the total area, respectively. Existing hotspots, particularly dense residential areas, commercial centers, and major institutional or public spaces, are expected to intensify. In addition, new UHI zones are likely to develop along the urban fringe, where expansion is occurring around the current hotspots. These study findings will be useful for Thimphu Thromde authorities in deciding the mitigation measures and pre-emptive strategies required to reduce UHI effects. Full article

Urban heat vulnerability is an increasing public health concern, particularly in rapidly urbanizing regions of southern France. This study aims to quantify and map the Heat Vulnerability Index (HVI) for Toulouse and to analyze its temporal trends to identify high-risk zones and influencing factors. The assessment integrates recent years’ remote sensing data of pollutant emissions, land use/land cover and land surface temperature, statistical data of climate-related mortalities, and socioeconomic and demographic factors. Following a detailed analysis of recent real-time air quality and weather data from multiple monitoring stations across the city of Toulouse, it was observed that Urban Pollution Island (UPI) and Urban Heat Island (UHI) are closely interlinked phenomena. Their combined effects can significantly elevate the annual mortality risk rate by an average of 2%, as calculated using AirQ+ particularly, in densely populated urban areas. Remote sensing data was processed using Google Earth Engine and all factors were grouped into three key categories: heat exposure, heat sensitivity, and adaptive capacity to derive HVI. Temporal HVI maps were generated and analyzed to identify recent trends, revealing a persistent increase in vulnerability across the city. Comparative results show that 2022 was the most critical summer period, especially evident in areas with limited vegetation and extensive use of heat-absorptive materials in buildings and pavements. The year 2024 indicates resiliency and adaptation although some areas remain highly vulnerable. These findings highlight the urgent need for targeted mitigation strategies to improve public health, enhance urban resilience, and promote overall human well-being. This research provides valuable insights for urban planners and municipal authorities in designing greener, more heat-resilient environments. Full article

Rapid urban growth in South Indian coastal cities such as Chennai has intensified the Urban Heat Island (UHI) effect, with paved parking lots, walkways, and open spaces acting as major heat reservoirs. This study specifically compares conventional construction materials with natural and low-thermal-inertia alternatives to evaluate their relative ability to mitigate Surface Urban Heat Island (SUHI) effects. Unlike previous studies that examine isolated materials or single seasons, this pilot provides a unified, multi-season comparison of nine urban surfaces, offering new evidence on their comparative cooling performance. To assess practical mitigation strategies, a field pilot was conducted using nine surface types commonly employed in the region—concrete, interlocking tiles, parking tiles, white cooling tiles, white-painted concrete, natural grass, synthetic turf, barren soil, and a novel 10% coconut-shell biochar concrete. The rationale of this comparison is to evaluate how conventional, reflective, vegetated, and low-thermal-inertia surfaces differ in their capacity to reduce surface heating, thereby identifying practical, material-based strategies for SUHI mitigation in tropical cities. Surface temperatures were measured at four times of day (pre-dawn, noon, sunset, night) across three months (winter, transition, summer). Results revealed sharp noon-time contrasts: synthetic turf and barren soil peaked above 45–70 °C in summer, while reflective coatings and natural grass remained 25–35 °C cooler. High thermal-mass materials such as concrete and interlocked tiles retained heat into the evening, whereas grass and reflective tiles cooled rapidly, lowering late-day and nocturnal heat loads. Biochar concrete performed thermally similarly to conventional concrete but offered co-benefits of ~10% cement reduction, carbon sequestration, and sustainable reuse of locally abundant coconut shell waste. Full article

Large Urban Mountains (LUM) with their rich vegetation cover offer a key natural solution to mitigate Urban Heat Island (UHI) effects. This study uses Longquan Mountain Forest Park (LMFP) as a case to investigate the spatiotemporal variations in cooling effects and the key factors influencing cooling intensity. Using Landsat images from 2001, 2011, and 2023, surface temperatures (LST) were retrieved through radiative transfer methods, and the thermal environment and cooling effects of LMFP were systematically analyzed. The eXtreme Gradient Boosting (XGBoost) model and Shapley Additive exPlanations(SHAP) methods were applied to explore the complex relationships between cooling intensity and its driving factors. Results show that in the years 2001, 2011, and 2023, the heat island area in LMFP has gradually shrunk, while the cooling intensity area has expanded. In the three years, the cooling distance increased from 330 m to 420 m, the cooling area expanded to 124.84 km², and cooling efficiency increased to 18.31%. Vegetation coverage, leaf area index (LAI), and elevation are core factors influencing cooling, while human activities such as population and road density have a negative impact. This study provides important theoretical insights into the cooling mechanisms of large urban mountain parks. Full article

The urban heat island (UHI) effect is one of the most pressing challenges associated with rapid urbanization. It arises primarily from the replacement of natural vegetation with impervious surfaces, alterations in surface energy balance, and heat emissions from human activity. Mitigating these drivers has become a global priority, particularly in fast-growing cities. Pavements play a central role in UHI intensification due to their large surface coverage, low albedo, and capacity to retain heat. This study adopts a bibliometric approach to systematically map the knowledge structure and research trends in pavement-related UHI studies. A dataset of 834 publications from Web of Science was analyzed using VOSviewer to identify leading countries and journals, central publications, the temporal evolution of research themes, and the thematic structure of the field. The analysis revealed three dominant themes: (1) pavement materials and their properties, (2) mitigation strategies that prevent UHI, and (3) cooling interventions to mitigate UHI. This study attempts to provide a comprehensive overview of the field and to clarify its interdisciplinary connections with climate adaptation and sustainability discourse. Full article

The urban heat island (UHI) effect poses significant challenges to cities worldwide, particularly in regions like Thessaloniki, Greece, where rising temperatures exacerbate urban living conditions. This study investigates the effectiveness of sustainable urban planning strategies in mitigating the UHI effect by analyzing the spatial distribution of Land Surface Temperature (LST) during the summer heatwave of 2023. Utilizing LANDSAT 8–9 satellite imagery processed with QGIS, we calculated LST, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI). Additionally, urban structure data from OpenStreetMap (OSM) was integrated to assess the urban fabric. Our findings reveal significant spatial temperature variations, with densely built-up areas, such as the old town and industrial district, exhibiting higher LSTs compared to greener spaces. Based on these results, we propose targeted interventions, including the large-scale implementation of green roofs and the use of light-colored asphalts, which have shown potential for substantial LST reduction. This work underscores the importance of integrating these strategies into a standardized urban planning framework to enhance urban resilience, providing a model that can be applied to other European cities facing similar climate challenges. Full article

The COVID-19 pandemic presented an unprecedented opportunity to assess the environmental effects of reduced anthropogenic activity on urban climates. This study investigates the impact of COVID-19-induced lockdowns on land surface temperature (LST) and the intensity of the surface urban heat island (SUHI) in Nowshera District, Khyber Pakhtunkhwa Province, Pakistan, which is experiencing rapid urbanization. Using Landsat 8/9 imagery, we assessed thermal changes across three periods: pre-lockdown (April 2019), during lockdown (April 2020), and post-lockdown (April 2021). Remote sensing indices, including NDVI and NDBI, were applied to evaluate the relationship between land cover and LST. Our results show a significant reduction in average LST during lockdown, from 31.38 °C in 2019 to 25.34 °C in 2020, a 6 °C decrease. Urban–rural LST differences narrowed from 9 °C to 6 °C. A one-way ANOVA confirmed significant differences in LST across the three periods (F (2, 3) = 3691.46, p < 0.001), with Tukey HSD tests indicating that the lockdown period differed significantly from both the pre- and post-lockdown periods (p < 0.001). SUHI intensity fell from 35.10 °C to 28.89 °C during lockdown, then rebounded to 35.37 °C post-lockdown. The indices analysis shows that built-up and rangeland areas consistently recorded the highest LST (e.g., 35.36 °C and 37.09 °C in 2021, respectively), while vegetation and water bodies maintained lower temperatures (34.68 °C and 32.69 °C in 2021). NDVI confirmed the cooling effect of green areas, while high NDBI values correlated with increased LST in urban areas. These findings underscore the impact of human activity on urban heat dynamics and highlight the role of sustainable urban planning and green infrastructure in enhancing climate resilience. By exploring the relationships among land cover, anthropogenic activity, and urban climate resilience, this research offers policymakers and urban planners’ valuable insights for developing adaptive, low-emission cities amid rapid urbanization and climate change. Full article

Land surface temperature (LST) is a key indicator of the urban heat island effect and is affected by multiple factors. However, existing research mainly focuses on the contributions of urban landscape and meteorology, and the impact of changes in atmospheric environment has not been fully considered. Based on multisource data and a random forest model, this study quantified the independent and interactive effects of aerosols, meteorological conditions, and urban features on LST in Beijing. The results revealed that the effects of the meteorological factors and aerosol optical depth (AOD) on LST were significantly greater than those of the urban landscape index. The response of LST to multiple factors is nonlinear, and the interactions of precipitation with wind speed and vegetation have the strongest cooling effects on LST. The aerosol impact shifts seasonally, with its direct radiative effect dominating in spring and inducing a cooling of up to about 2.0 °C. Notably, the land use type plays a background role in determining the LST, and the average LST decreases by approximately 1.5 °C for every 50% increase in tree coverage. As the building height increases by 10%, the summer LST increases by approximately 2 °C. In addition, the interactions of precipitation with wind speed and vegetation were identified as having the strongest cooling effects on LST. By elucidating the nonlinear interactions among aerosol, meteorological, and urban features, this work moves beyond isolated factor analysis and offers mechanism cognition for urban planning strategies. Full article

The urban heat island (UHI) effect in Andean cities is a critical yet understudied phenomenon, where complex topography and rapid urbanization uniquely alter local climates. This research analyzes the spatiotemporal evolution of the surface UHI and its linkage to urban morphology in Ayacucho, Peru, through a 40-year multi-temporal analysis (1986–2016) using Landsat images. We developed a synthetic Urban Heat Island Index (UHII) through Principal Component Analysis (PCA), integrating land surface temperature (LST), spectral indices, and urban morphological parameters. Our results identify a critical transition in 2006, with the emergence of persistent heat spots driven by unplanned expansion. The surface UHI intensity reached urban-rural differences of 4.31 °C (day) and 5.82 °C (night), showing a positive trend. Urban morphology was a key determinant, with high-density blocks exhibiting a minimum nocturnal LST 3.53 °C higher than low-density areas. Statistical trend tests confirmed a significant intensification, while a strong negative correlation with vegetation indices (R² = 0.97) underscored the vital mitigation role of green infrastructure. This study provides academics with a robust methodological framework for UHI analysis in complex terrains. For public and private urban managers, it offers spatially explicit evidence to prioritize actionable strategies, such as integrating green infrastructure and regulating urban form, to enhance climate resilience in Andean cities. Full article

Urban areas and their surroundings feature unique, horizontally inhomogeneous spatial distributions of land use and land cover, leading to urban heat islands (UHIs) for both air and land surface temperature that complicate the estimation of urban sensible heat flux. The urban dispersion option in AERMOD, the American Meteorological Society (AMS)/Environmental Protection Agency (EPA) Regulatory Model, incorporates this effect at night through a “convective like boundary layer” that modifies the single column meteorology based on a population number representative of the urban area. The model produces positive nighttime sensible heat flux values that often significantly overestimate observed values from the literature. This study re-examines the formulation of the AERMOD urban option assumptions, methodology, and original evaluation against a field study of a power plant in Indianapolis. We investigate replacing the population-based parameterizations of urban–surrounding temperature differences ($\Delta \mathit{T}$) with observations of remotely sensed land surface temperature (LST) data from the Advanced Baseline Imager on the GOES-16/R/East geostationary satellite. We generated a monthly averaged, hourly, wind direction-dependent, clear sky land surface urban heat island $\Delta \mathit{T}$ database for 480 continental United States (CONUS) urban areas, as defined by the 2010 US Census. These $\Delta \mathit{T}$ values are used to advise city-specific horizontal advection corrections to sensible heat flux estimates that are neglected from simple energy balance models. The four cities of Cleveland, Amarillo, Atlanta, and Baltimore are highlighted, showing that the AERMOD predicted nighttime $\Delta \mathit{T}$ values are 794%, 416%, 1048%, and 758% higher, respectively, than the GOES-16 observations. These overestimated $\Delta \mathit{T}$ values in AERMOD lead to nighttime sensible heat flux values > 100 W/m² that rival daytime values. However, using the GOES-16 observations as horizontal advection corrections to sensible heat flux results in trends that match the expected neutral to slightly positive nighttime values from observations recorded in the literature. The annual nighttime average in 2021 was −0.8 W/m², 8.6 W/m², 3.0 W/m², and 3.1 W/m² in Cleveland, Amarillo, Atlanta, and Baltimore, respectively, using this approach. Finally, reviewing the initial evaluation with the Indianapolis database against independent studies from the literature suggest that the AERMOD urban option inadvertently implements an urban heat island modeling approach to account for what was a low-level jet during the field study. Full article

The urban heat island (UHI) has been a critical social problem as urbanization intensifies worldwide, significantly impacting human life by exacerbating heat-related health issues, increasing energy demand for cooling, and resulting in associated environmental problems. However, the fine-scale diurnal and spatial characteristics of UHI remain poorly understood due to the limited resolution of traditional satellite datasets. This study aims to quantify the diurnal and spatial dynamics of surface urban heat islands (SUHI) in Busan and Daegu—the two hottest metropolitan cities in Korea—by integrating high-resolution ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) (70 m) and Geostationary Korea Multi-Purpose Satellite-2A (GK-2A) (2 km) land surface temperature (LST) data. Using the combined datasets, season-representative diurnal LST variations were characterized, and locational heat intensification (LHI) was evaluated across land use types and densities at sub-district scales. The results show that the maximum SUHI intensity reached 10 °C in Daegu and 7 °C in Busan during summer, up to 8 °C higher than estimates from coarse-resolution data. Industrial areas recorded the highest LST (47 °C in Daegu and 43 °C in Busan) with rapid morning intensification rates of 2.0 °C/h and 1.9 °C/h, respectively. Dense urban land uses amplified LHI by nearly twofold compared to less dense urban areas. These findings emphasize the critical role of land use density and industrial heat emissions in shaping urban thermal environments, providing key insights for use in urban heat mitigation and climate-adaptive planning. Full article

This study examines long-term trends in maximum (Tmax) and minimum (Tmin) near-surface air temperatures and precipitation across South America, focusing on Brazilian biomes and national capitals, using ERA5 reanalysis data for 1979–2024. To isolate the underlying climate signal, seasonal cycles were removed using Seasonal-Trend decomposition based on Loess (STL), which effectively separates short-term variability from long-term trends. Temperature trends were quantified using ordinary least squares (OLS) regression, allowing consistent estimation of linear changes over time, while precipitation trends were assessed using the non-parametric Mann–Kendall test combined with Theil–Sen slope estimation, a robust approach that minimizes the influence of outliers and serial correlation in hydroclimatic data. Results indicate widespread but spatially heterogeneous warming, with Tmax increasing faster than Tmin, consistent with reduced cloudiness and evaporative cooling. A meridional precipitation dipole is evident, with drying across the Cerrado, Pantanal, Caatinga, and Pampa, contrasted by rainfall increases in northern South America linked to ITCZ shifts. The Pantanal emerges as the most vulnerable biome, showing strong warming (+0.51 °C decade⁻¹) and the steepest rainfall decline (−10.45 mm decade⁻¹). Satellite-based fire detections (2013–2024) reveal rising wildfire activity in the Amazon, Pantanal, and Cerrado, aligning with the “hotter and drier” climate regime. In the capitals, persistent Tmax increases suggest enhanced urban heat island effects, with implications for public health and energy demand. Although ERA5 provides coherent spatial coverage, regional biases and sparse in situ observations introduce uncertainties, particularly in the Amazon and Andes, these do not alter the principal finding that the magnitude and persistence of the 1979–2024 warming lie well above the range of interdecadal variability typically associated with the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). This provides strong evidence that the recent warming is not cyclical but reflects the externally forced secular warming signal. These findings underscore growing fire risk, ecosystem stress, and urban vulnerability, highlighting the urgency of targeted adaptation and resilience strategies under accelerating climate change. Full article

In the context of global climate change and rapid urbanization, the Urban Heat Island (UHI) effect has become a pressing environmental and public health concern, particularly in semiarid regions. This study evaluates the microclimatic performance of various urban design strategies aimed at enhancing thermal comfort along a densely built-up street in Van, a medium-sized city located in Turkey’s semiarid climate zone. Using ENVI-met 5.7.2, nine alternative scenarios were simulated, incorporating different configurations of vegetation cover (0%, 25%, 50%, 75%), ground surface materials, and green roof applications (0%, 25%, 50%, 75%). Physiological Equivalent Temperature (PET) and other thermal comfort indicators were assessed at multiple time intervals on the hottest summer day. Results indicate that increasing vegetation cover substantially reduces PET values, with a maximum reduction of 3.0 °C observed in the 75% vegetation scenario. While the scenario with no vegetation but light-colored pavements achieved a 1.8 °C reduction in air temperature at 2:00 p.m., the maximum PET value remained unchanged. Conversely, using dark-colored asphalt decreased the average air temperature by 1 °C and improved the thermal comfort level by reducing the PET by 0.4 °C compared to a non-vegetated scenario. The scenario with the highest overall greenery led to a 2.9 °C drop in air temperature and a 12.8 °C reduction in average PET at 2:00 p.m. compared to other scenarios. The study provides evidence-based recommendations for human-centered urban planning and advocates for the integration of microclimate simulation tools in the early stages of urban development. Full article

Rapid urban growth and the expansion of impervious surfaces have intensified environmental issues such as flooding, water pollution, and urban heat islands. Permeable pavements have emerged as a green infrastructure solution to mitigate these impacts and support the sustainable development of cities. The aim of this study was to conduct an integrative review on the state of the art of permeable pavements, with a focus on their technical and environmental contributions. The methodology followed the PRISMA guidelines, using the Scopus database to select the most cited articles across four thematic areas: Life Cycle Assessment; infiltration capacity and pollutant retention; mitigation of heat islands and flooding; and the impacts of climate and clogging. The results show that, despite the initial cost and production-related impacts, permeable pavements offer long-lasting benefits, including reduced surface runoff, pollutant filtration, and evaporative cooling. The main economic limitations identified were clogging, which decreases system efficiency, and the high implementation cost, highlighting the need for regular maintenance and innovations in materials. In summary, permeable pavements are an effective strategy for sustainable urban development, but their longevity depends on proper design and maintenance. Full article