Search Results (904)

Urban heat islands in densely built cities pose growing risks to public health and energy demand. Urban parks are key nature-based solutions, yet empirical evidence on park cool island (PCI) effects intensity and extent in compact cities remains limited. This study evaluated PCI for 12 pocket-to-medium/large urban parks in central Taipei, Taiwan. Land surface temperature (LST), mean radiant temperature (MRT), and effective temperature (ET) were measured along transects from park interiors into surrounding areas and linked to local environmental conditions. Parks showed PCI intensity in LST with an average cooling of 4.23 °C and an average cooling of 0.3 °C in ET; MRT cooling was weaker and spatially inconsistent. The cooling of LST extended to about 60 m beyond the park’s edges, while the cooling of ET reached approximately 150 m. In addition, the results show that shade and relative humidity are significant factors affecting PCI, and pervious pavement and wind speed also contribute to cooling LST and ET. The field observations provide evidence that urban parks contribute cooling effects and might reduce the risk of heat hazards. Full article

Surface urban heat island (SUHI) behavior in dryland cities can reverse sign when hot, bare peripheral surfaces exceed urban-core temperatures, yet long monthly records across contrasting climates remain scarce. This study reconstructs land surface temperature (LST) and standardized urban-core–periphery thermal contrasts for five Moroccan cities from 1995 to 2024 using Landsat, ERA5-Land, NDVI, and the annual MODIS MCD12Q1 land-cover product. The diagnostic analysis of SUHI and Urban Heat Sink (UHS) occurrence is explicitly separated from the forecasting component: SARIMA, Random Forest, XGBoost, and LSTM models predict monthly LST rather than UHI intensity. Tangier exhibits a persistent positive SUHI (mean: 4.6 °C; UHS frequency: 3.0%), whereas Béni Mellal, Ifrane, Laayoune, and Taza have negative mean contrasts of −1.4, −2.4, −1.0, and −0.7 °C, respectively; Ifrane records the highest UHS frequency (90.5%). No city shows a statistically significant monotonic UHI trend, and Sen’s slopes remain close to zero. Forecasting skill is city-dependent: SARIMA performs best in Ifrane and Tangier (R² = 0.94 and 0.93), while Random Forest performs best in Taza and Laayoune (R² = 0.90 and 0.79). Approximate 95% empirical uncertainty half-widths derived from held-out RMSE range from ±3.78 to ±15.48 °C, indicating substantial model- and city-specific uncertainty. The results support the hypothesis that local climate and peripheral land-cover context can outweigh urban fraction as controls on SUHI sign and amplitude. Generalization is limited by fixed reference distances, possible urbanization of the outer ring, clear-sky satellite sampling, the distinction between LST and air temperature, and the 36-month recursive forecasting chain used to display the 2026–2027 outlook. Full article

The study investigates the efficacy of various Urban Heat Island (UHI) mitigation measures within the United Nations Educational, Scientific and Cultural Organization UNESCO-listed historical center of Florence. Increasingly frequent and severe heatwaves during the summer season represent significant challenges for urban sustainability and public health in the outdoor urban environment. Using ENVI-met as a simulation tool, the research assesses the current microclimate conditions of a district within a historical center and simulates alternative mitigation scenarios. It quantifies the benefits in terms of microclimate characteristics (Potential Air Temperature-Ta and Mean Radiant Temperature-MRT) and human comfort indexes (Physiological Equivalent Temperature-PET and Universal Thermal Climate Index-UTCI). The proposed interventions include blue and green infrastructures as well as shading systems installed across the district. Current climate conditions are characterized by an average Ta of approximately 32 °C and MRT exceeding 59 °C; consequently, the analyzed area falls into the very strong heat stress category for both the calculated comfort indexes. All evaluated mitigation measures result in improving microclimate conditions as well as enhancing human thermal wellbeing within the outdoor environment. The most effective district-level intervention is the installation of shading fabrics, which reduces average Ta by 0.2 °C and MRT by up to 14 °C compared to the current scenario. Interventions tailored for the main square significantly reduce both UTCI and PET values, shifting the thermal stress from very strong to strong or even moderate. These findings highlight the potential of localized and tailored interventions to successfully integrate climate mitigation strategies within sensitive historic urban districts. Full article

Urban heat islands (UHI) intensify as cities expand, exposing residents to elevated thermal stress and complicating urban climate adaptation planning. Existing satellite-based approaches to detecting surface urban heat islands (SUHI) typically rely on a single class of data and narrow temporal windows, limiting their ability to capture the full range of processes driving surface overheating. This study develops and evaluates a random forest model for SUHI detection in Warsaw, Poland, integrating two classical spectral indices (NDVI, NDBI) derived from Landsat 8/9 Collection 2 imagery with three land-cover probability layers (built-up, tree, water) from the Dynamic World deep-learning product, processed in Google Earth Engine. Both a multi-year summer median composite (2020–2025) and individual annual summer composites were used, the latter enabling a leave-one-year-out temporal validation. Heat island pixels were defined as those whose land surface temperature anomaly exceeded +3 °C relative to the study area mean, a local criterion rather than a city-versus-rural contrast. The model achieved high and stable performance (accuracy = 0.831, AUC = 0.910 on the test set; AUC = 0.907 ± 0.004 in five-fold cross-validation and 0.905 ± 0.018 in leave-one-year-out validation). An ablation analysis showed that combining the probability layers with the spectral indices clearly outperformed the indices alone (AUC = 0.852 vs. 0.905), whereas the additional gain over the Dynamic World layers alone remained within uncertainty. Vegetation-related predictors (NDVI and tree probability) contributed more to classification than built-up indicators. These results indicate that vegetation deficit, rather than built-up presence alone, is the primary driver of surface overheating in Warsaw and that the proposed open-data workflow offers municipalities a low-cost screening tool for identifying priority areas for climate adaptation and, thanks to its reliance solely on open data, can be adapted to other cities, subject to further validation. Full article

Warsaw experiences significant urban heat island (UHI) effects driven by low-albedo surfaces and urban geometry, which pose ongoing challenges for public health and climate adaptation. This study evaluates daytime SUHI intensity at satellite acquisition time across the entire city to provide a comparison of two acquisition dates during heatwaves. Utilizing Landsat 7 and Landsat 9 satellite imagery from July 2015 and July 2022, the research compares six distinct SUHII calculation methods, including spectral indices, statistical normalizations, and area-based temperature differences, as minimum SUHII values differed significantly between the two observations (shifting from approximately −13.8 °C to −7.7 °C). This indicates that suburban areas can become thermally similar to the city due to rapid land conversion and decreased evaporative cooling of vegetation during severe heat. Average intensities calculated via the SUHII 4 method reached 5.80 °C in 2015 and 2.07 °C in 2022. Under the criteria considered in this case study—interpretability, explicit physical units, treatment of water bodies, data requirements, and spatial consistency—SUHII 4 was the most suitable of the six tested formulations for the Warsaw analysis. Conversely, dimensionless spectral indices and purely statistical approaches are not recommended due to interpretative limitations. Full article

As rapid population aging coincides with intensifying urban heat island (UHI) effects, ensuring the outdoor thermal comfort of the elderly in hot–humid regions has become a critical challenge. This study investigates the influence of residential spatial morphology and wind environment on elderly thermal comfort in Fuzhou, China, by integrating PHOENICS and RayMan numerical simulations with a multivariate statistical framework. The Physiological Equivalent Temperature (PET) was calculated across three metabolic intensities (sedentary, walking, and exercising), while the LMG algorithm was used in R to identify the driving mechanisms. Residential layouts are stratified into High-Performance (Group A) and High-Risk (Group B) categories based on their thermal risk. In Group A, the microclimate is convective-dominant wind speed and air changes per hour are the primary determinants of thermal comfort. Conversely, Group B exhibits a radiation-dominant mechanism, with the sky view factor acting as the primary driver of heat stress in confined environments. Furthermore, metabolic intensity emerges as a decisive factor, as physical exercise frequently pushes PET beyond the 37.1 °C threshold even in high-performance layouts. Accordingly, this study proposes differentiated strategies: prioritizing ventilation-led optimization for Group A and radiation-shielding interventions for Group B, while advocating for supplementary active cooling in high-intensity activity zones to safeguard the geriatric population during peak summer heat. Full article

Rapid urbanization in tropical Asia has fundamentally transformed land use–land cover while intensifying urban thermal stress, yet the relationship between land cover change and thermal conditions is frequently assumed to be spatially uniform. This study challenges that assumption by demonstrating that land cover–thermal relationships in Colombo District, Sri Lanka, are highly spatially and temporally heterogeneous, with statistically significant associations detected in only 17–47% of the study area in any given year, underscoring that context, not land cover type alone, governs thermal outcomes. Using multi-temporal Landsat satellite imagery, LULC maps were derived, and the urban heat island effect (UHIE) and urban thermal field variance index (UTFVI) were calculated for seven time periods (1989, 1996, 2002, 2009, 2014, 2019, 2024). Geographically weighted regression (GWR) was applied to model local relationships between LULC classes, namely wetland vegetation, water bodies, impervious surfaces, and other pervious surfaces, and thermal indices across a 500 m spatial grid, revealing a 74% loss in wetland vegetation and a 326% increase in impervious surfaces over the study period. Water bodies exhibited spatially variable cooling effects relative to wetland vegetation, most pronounced in eastern regions during earlier periods, while impervious surfaces showed consistent, spatially persistent warming effects concentrated in western and southern urban cores. By coupling GWR with a 35-year multi-sensor time series, this study provides a spatially explicit, longitudinal account of how land cover–thermal relationships evolve as tropical urbanization intensifies, offering an evidence base for spatially targeted rather than uniform climate adaptation planning in rapidly urbanizing tropical cities. Full article

Most studies have explored the impact of different types of local climate zones (LCZs) on energy consumption, but few have examined climate differences within intra-local climate zones (intra-LCZs) and the impact of cold waves (CW) on energy consumption. This study conducted a 150-day long-term observation of air temperature (Ta) and relative humidity (RH) in six LCZs in Shenyang, a severe cold region, to examine climate differences within intra-LCZs and the influence of CW and the urban heat island (UHI) on energy consumption. The results show that the temperatures and heating energy consumption in 5 LCZ4s exhibited a clear gradient from the urban core to the suburbs. During CW, the differences increased, and the nighttime differences were more pronounced. CW significantly increased residential heating energy consumption, whereas the urban heat island (UHI) reduced it in urban areas. Additionally, there was a clear positive correlation between UHI and the urban-suburban energy consumption difference. Under the combined effects of CW and UHI, the average daily cumulative heating energy consumption in urban areas (CW) was much higher than in suburban areas during non-cold-wave (NCW) periods, increasing by 69.2–85.9%. This study provides empirical evidence for energy conservation and strategies for responding to extreme weather events. Full article

The urban heat island (UHI) refers to higher air temperatures (T_air) in urban areas than in surrounding rural environments, while the surface urban heat island (SUHI) describes analogous differences in land surface temperature (LST). This study presents a long-term assessment of UHI and SUHI in Modena, Italy, combining meteorological T_air observations with Landsat-derived LST from 188 daytime and 19 nighttime summer scenes (1985–2023). Four indicators—magnitude and range 1 of overall thermal variability and magnitude and range 2 of urban–rural thermal excess—were applied in parallel to LST and T_air to characterize the intensity and spatial variability of thermal conditions within a consistent daytime/nighttime framework. Results indicate significant long-term increases in summer LST, with daytime warming rates of 0.26 °C yr⁻¹ (urban) and 0.27 °C yr⁻¹ (rural). Daytime urban–rural LST differences ranged from 4 to 6 °C; nighttime differences were smaller (1–3 °C). Daytime T_air urban–rural differences were weak and not statistically significant, whereas nighttime T_air showed a clearer urban warming signal. Nighttime LST correlated more closely with T_air (r = 0.49–0.52 across indicators) than daytime LST, and nighttime LST showed strong correlations with T_air in both urban and rural areas (r = 0.96–0.98). Daytime imagery better captures SUHI spatial intensity, whereas nighttime observations provide a more consistent surface-to-atmosphere thermal link, highlighting the value of integrating satellite LST with in situ T_air for integrated UHI and SUHI assessment in medium-sized cities. Full article

Urbanisation and climate change have intensified the Urban Heat Island (UHI) effect in European cities, increasing thermal stress and health risks, especially for vulnerable people. Nature-based Solutions (NbS), such as green infrastructures (GI), offer effective mitigation strategies. A notable example is the Horizon 2020 URBAN GreenUP project in Valladolid, Spain, where a green shade shelter infrastructure was installed and monitored between 2019 and 2022 to evaluate its cooling performance and its effects on temperature-based urban heat indicators through the use of Key Performance Indicators (KPIs). Local thermal conditions were monitored across two adjacent narrow streets—one with the green shade shelter and one as a control. The installation of the green shade shelter in Valladolid produced measurable thermal benefits. During summer peaks, it reduced ambient temperatures by approximately 0.9 °C, with daily maximum temperatures decreasing by 1.0–3.0 °C. In winter, daily minimum temperatures dropped by around 1.0 °C, while autumn saw an increase of 0.7 °C. Summer minimum temperatures varied, ranging from a 0.2 °C decrease in early summer to a 0.7 °C increase in late summer, with a 0.3 °C rise during peak summer in mid-July. The intervention also reduced the frequency and delayed the onset of days exceeding 35 °C and nights above 20 °C, although the delay in peak tropical nights was limited to seven days. These findings indicate that green shade shelters can contribute to improving street-level thermal conditions and reducing temperature-based heat exposure indicators in dense urban environments. Full article

Urban Heat Island (UHI) effects are increasingly acknowledged as a critical urban climate challenge with far-reaching consequences for human health and overall well-being. However, the conceptual structure, temporal evolution, and intellectual landscape of studies examining the relationships between UHI and human well-being remain fragmented, thereby constraining the development of integrated knowledge frameworks needed to guide future research, urban adaptation strategies, and evidence-based policy interventions. To this end, a total of 4857 studies were retrieved from the Scopus and Web of Science databases and screened following the PRISMA guidelines. These studies were then analyzed using Bibliometrix and VOSviewer. The results reveal a rapid and exponential growth in scientific output, particularly after 2010, with the output reaching its highest level in recent years. These outputs were shaped mostly in China and the United States with a well-established international collaboration network, while the Global South remain significantly underrepresented in scientific productions. We also found that studies are primarily structured around four dominant research clusters: urban heat island, thermal comfort, land surface temperature, and climate change. Furthermore, early studies predominantly focused on urban surface properties and built-environment characteristics, while recent research has increasingly shifted toward human health impacts, thermal stress, heat vulnerability, and well-being. Emerging research directions further highlight growing interest in nature-based solutions for mitigating UHI effects, alongside the application of advanced technologies such as machine learning and remote sensing for high-resolution urban climate assessment. Overall, our findings indicate a transition toward a more integrated urban climate–health–well-being research framework, while simultaneously revealing persistent geographical and conceptual gaps, particularly across the Global South. We therefore advocate for increased empirical research, stronger international collaboration, and context-specific urban adaptation strategies to better safeguard human well-being under intensifying urban heat conditions. Full article

Urban Heat Island (UHI) effects are increasingly affecting Mediterranean coastal cities, where climate change, urbanization, and seasonal tourism intensify thermal stress and environmental vulnerability. In this context, climate-oriented planning and green infrastructure are recognized as key strategies for urban adaptation. This study investigates the spatiotemporal evolution of Land Surface Temperature (LST) and vegetation cover in the coastal municipality of Lignano Sabbiadoro (northeastern Italy) through the analysis of Landsat imagery acquired between 1984 and 2023. Summer LST and Normalized Difference Vegetation Index (NDVI) maps were derived from June–August observations and used to assess long-term thermal dynamics, vegetation patterns, and Urban Heat Island development. Meteorological data indicate a significant increase in mean annual air temperature, with a warming trend of approximately 0.57 °C per decade between 1984 and 2023. Correspondingly, Landsat-derived LST maps reveal a marked intensification of summer surface temperatures, with mean summer LST increasing from 32.16 °C in 1984–1993 to a peak of 35.91 °C in 2004–2013, followed by a slight decrease to 35.77 °C during 2014–2023. During the same period, the proportion of municipal surfaces characterized by temperatures above 35 °C increased from 10.7% to more than 60%, while cooler areas (<30 °C) declined from 17.7% to 2.3%. The comparison between LST and NDVI patterns revealed a persistent inverse relationship between vegetation cover and surface temperature, with coastal pinewoods, green spaces, and water bodies consistently exhibiting lower thermal values than densely urbanized sectors. A key methodological contribution of the study is the operational integration of satellite-derived thermal remote sensing into the Green Plan of Lignano Sabbiadoro. LST mapping was used to identify priority areas for climate adaptation measures, including ecological corridors, wooded landscape connections, urban green corridors, and depaving interventions. The results demonstrate how multi-temporal thermal analysis can support evidence-based planning by linking climate assessment with the spatial prioritization and design of green infrastructure strategies. The proposed workflow provides a transferable framework for integrating remote sensing into climate-informed planning processes in Mediterranean coastal cities and other urban contexts increasingly exposed to heat-related risks. Full article

Urban noise complaints reflect not only perceived acoustic disturbance, but also complaint behaviour shaped by thermal conditions and the built environment. Using Sanya, China, as a case study, this study integrated Landsat-derived land surface temperature data with the spatial distribution of noise complaints to examine how thermal environment and urban contextual factors jointly influence complaint patterns. An interpretable modeling framework combining eXtreme Gradient Boosting (XGBoost) and Multiscale Geographically Weighted Regression (MGWR) was employed to assess the associations of urban heat island intensity (UHI), road density, point of interest (POI) count, and population density on complaint occurrence and intensity, while also generating spatial predictions of complaint distribution. The results revealed a weak but statistically significant spatial association between the thermal environment and noise complaints, with urban heat island intensity showing nonlinear and spatially heterogeneous associations with complaint counts. POI count emerged as the strongest global predictor, while road density, population density, and thermal environment exhibited substantial spatial heterogeneity in their associations with complaint patterns. The integrated model outperformed both individual models alone, achieving the highest prediction accuracy. Overall, the findings suggest that urban noise complaint patterns reflect not only perceived acoustic disturbance, but also context-dependent social perception and reporting behaviour, providing empirical support for more place-sensitive and people-centered urban noise governance. Full article

Urban heat intensification is an increasing concern in rapidly urbanizing arid cities, where extreme climatic conditions intersect with expansive urban growth. This study examines the spatiotemporal dynamics of urban thermal patterns in the Doha metropolitan region, Qatar, by integrating multi-season remote sensing with urban morphological analysis. Seasonal composites of land surface temperature (LST), Urban Heat Island (UHI) intensity, and Normalized Difference Vegetation Index (NDVI) were derived from Landsat 8–9 Collection 2 Level-2 imagery across eight seasons from Spring 2024 to Winter 2026. Urban form was characterized using Local Climate Zones (LCZs) and quantified through class-level landscape metrics, i.e., Largest Patch Index (LPI), Number of Patches (NP), and CLUMPY. The results showed a pronounced seasonal variability, with LST ranging from approximately 12.5 °C in winter to 61.3 °C in summer, and intra-urban UHI exceeding 10 °C during peak conditions. The bare soil/sand, with relative coverage of 52.84% and LPI of 25.45%, and the large low-rise, with relative coverage of 38.60% and LPI of 14.70%, typologies dominate the landscape, forming highly aggregated spatial structures, while vegetation cover remained minimal. Weak negative relationships between NDVI and thermal indicators revealed that vegetation alone had limited explanatory power. In contrast, LCZ-based analysis revealed a better thermal differentiation across urban typologies, with compact forms associated with higher thermal intensities. These findings highlight the dominant role of urban morphology and spatial configuration in shaping thermal patterns and support the need for morphology-sensitive planning strategies in arid urban environments. Full article

Urban heat island effects increasingly challenge pedestrian mobility by intensifying thermal stress and reducing the attractiveness of walking during hot periods. However, most pedestrian routing systems still prioritize distance or travel time, while environmental conditions such as heat exposure and shade are rarely incorporated into operational route generation. Existing comfort-aware approaches often rely on static maps, simulated microclimatic indicators, or descriptive greenery measures, limiting their direct integration into user-configurable pedestrian navigation. This study develops a thermal comfort-aware pedestrian routing framework that integrates heterogenic data sources including observed land surface temperature, pedestrian-perspective tree-canopy coverage, and network distance into a unified multi-criteria pathfinding model. The workflow proceeds in four steps: first, airborne thermal imagery is processed to derive a high-resolution land surface temperature layer; second, Google Street View images are sampled at street-segment locations and segmented using SegFormer to extract visible tree-canopy coverage; third, both environmental indicators are aggregated to a cleaned pedestrian network; and fourth, normalized distance, temperature, and canopy attributes are combined through a user-adjustable edge-cost formulation and solved using Dijkstra’s algorithm. The framework is implemented as an operational web-based routing tool for the historic center of Clermont-Ferrand, France. The routable graph includes 551 nodes and 796 edges, with 600 segments carrying GSV-derived canopy information and 623 segments carrying airborne-derived LST values. Across the network, we observed LST ranges from 19.5 °C to 39.1 °C, while canopy coverage ranged from 0 to 70.6%. For a representative origin–destination pair, the coolest route reduces average LST by nearly 5 °C and almost triples canopy coverage compared with the shortest path, although at the cost of a 72% longer distance. These results demonstrate that the framework can generate interpretable comfort–efficiency trade-offs and support user-comfort pathfinding as an operational approach for heat-resilient pedestrian navigation. Full article