Search Results (386)

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

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

Seagrass and macroalgae are critical components of shallow coastal habitats undergoing fragmentation due to environmental and anthropogenic stressors. Mapping and monitoring their extent are essential for understanding and managing ecosystem changes. Hyperspectral imaging (HI) is an emerging tool for ocean mapping, providing spectral reflectance per image pixel for benthic habitat mapping. This study evaluated the use of multiscale hyperspectral mapping of shallow seagrass and macroalgae habitats using two platforms: an Uncrewed Aerial Vehicle (UAV-HI, 10 × 10 cm spatial resolution, 20,200 m² coverage) and an Uncrewed Surface Vehicle (USV-UHI, 1 × 1 cm resolution, 230 m² coverage). A spectral angle mapper (SAM) classification algorithm was applied with varying thresholds to assess classification performance. As much as 2316 m² (11.5% of total area) was estimated to be seagrass by spectral angle mapper algorithms; of this, 150 m² was mapped at the centimeter scale by the USV. The overall accuracies of the SAM classifications reached 89% and 86% for the UAV and USV, respectively, for a subsampled overlapping area. With the training data available, the UAV performs better in the accurate classification of seagrass and brown algae; however, this is collected at a coarser resolution (10 × 10 cm). The lower accuracy across both platforms is explained by a higher rate of false positives in the sediment class, which was supported by corresponding Intersect over Union (IoU) and recall metrics. The classification and accuracy assessment presented in this study support the proposed uses of both platforms. These results contribute to the development of a methodological approach to hyperspectral imaging applications for mapping seagrass and macroalgal habitats, with clear relevance for environmental monitoring and management. Full article

Rapid urbanization has significantly altered urban landscape composition and configuration, making it a key driver exacerbating the urban heat island (UHI) effect. As a rapidly expanding inland city in Central China, Zhengzhou is highly sensitive to changes in landscape composition and spatial configuration. Therefore, clarifying the nonlinear relationship between landscape patterns and the urban thermal environment is of great significance for sustainable urban planning and thermal environment regulation. Taking the main urban area of Zhengzhou as the study area, this paper retrieves land surface temperature (LST) using the radiative transfer equation method based on Landsat 8 remote sensing images from August 2015 to August 2024, and constructs the surface urban heat island intensity (SUHII) index. By integrating multi-dimensional landscape pattern indices, the XGBoost machine learning model, and the SHAP interpretability method, this study systematically analyzes the nonlinear response mechanisms of landscape composition and configuration to SUHII, key regulatory thresholds, and their changes between 2015 and 2024. The results show that: (1) The SUHII in Zhengzhou was substantially higher in 2024 than in 2015. The area proportions of strong and extremely strong heat islands were higher in 2024 (26.16% and 2.34%) than in 2015 (2.22% and 0.12%), and the thermal environment differed between 2015 and 2024, shifting from a localized patch pattern to a more continuously expanding pattern. (2) Landscape area-related indices are the key factors. The areas of green space and water bodies, along with the landscape diversity index, show significant negative correlations, while built-up area and aggregation index show significant positive correlations. (3) SHAP feature importance indicates that water body area is the primary cooling factor, whereas built-up area is the primary warming factor, jointly dominating the spatial pattern of the thermal environment in Zhengzhou. (4) Landscape composition and configuration exhibit significant nonlinear responses to SUHII with region-specific thresholds, and these thresholds were higher/lower in 2024 than in 2015, suggesting a possible association with urban expansion. Specifically, stable cooling effects occurred when the water body area exceeded 3.5 km² in 2015, with the threshold rising to 4.2 km² in 2024. The warming threshold for built-up area decreased from 18.8 km² to 8.5 km², suggesting a higher sensitivity of the thermal environment to built-up area expansion in 2024 compared to 2015, characterized by a regulation pattern of “dominant scale effect and weakened configuration effect”. This study identifies thresholds specific to Zhengzhou’s main urban area at two time points (2015 and 2024), providing quantitative support and scientific basis for blue–green space optimization, precise heat island mitigation, and territorial spatial planning in Zhengzhou. These findings are based on a comparison of two time points (2015 and 2024) and do not directly capture continuous temporal dynamics. Full article

As climate change intensifies heat extremes, the Urban Heat Island (UHI) effect amplifies local thermal stress. Assessing the UHI using robust observational data, whether ground- and/or satellite-based, is essential for climate risk assessment and evidence-based urban adaptation. Therefore, this study aims to provide a comprehensive climatological assessment of air temperature patterns and UHI intensity across the Lisbon Metropolitan Area (LMA) over a 26-year period (2000–2025). The methodology employs a dense, high-quality integrated network of in-situ weather stations from the Portuguese Institute for Sea and Atmosphere (IPMA) and the National Water Resources Information System (SNIRH). To bridge critical gaps in traditional climate assessments, this research implements a dual-perspective approach that combines the high temporal resolution of MSG-SEVIRI and the spatial precision of MODIS Land Surface Temperature (LST). This framework accurately captures the lag effects between surface heating and atmospheric response. Validation results demonstrate that satellite-derived LST is a robust proxy for monitoring the nocturnal UHI, with differences generally below 1 °C compared with near-surface air temperature observations (T2m). However, daytime LST significantly overestimates atmospheric temperatures, with deviations of 2–8 °C due to solar radiation and urban geometry. The selection of rural reference stations constitutes a critical methodological factor, as a baseline shift can alter perceived UHI intensities by more than 3 °C. Despite these sensitivities, the results unequivocally confirm a persistent and spatially heterogeneous UHI effect in Lisbon, which intensifies during extreme heat events by up to an additional 4 °C. Analysis of the 2003 and 2018 heatwaves reveals surface LST anomalies exceeding 10 °C and urban–rural thermal differentials reaching up to 7 °C under conditions of suppressed maritime breezes. These nocturnal anomalies are particularly pronounced in densely built-up areas, limiting thermal dissipation and preventing physiological recovery. Integrating multi-sensor satellite data with in-situ validation provides a new benchmark for climate risk assessments, delivering the reliable, reproducible data required to strengthen long-term urban resilience under increasingly frequent extreme heat events. Full article

The urban heat island (UHI) effect has become a prominent ecological and energy challenge amid rapid urbanization. This study comprehensively examined the spatiotemporal dynamics of UHI intensity in built-up areas across 216 Chinese cities spanning five climatic zones from 2000 to 2020 and quantified UHI-triggered energy consumption, as well as revealing its driving mechanisms. The results showed a significant increasing trend in UHI intensity across China’s urban built-up areas during summer days, summer nights, and winter nights from 2000 to 2020, with corresponding annual growth rates of 10.23, 5.61, and 5.08 km²·°C·a⁻¹, respectively. However, winter daytime UHI intensity declined dramatically from 4.72 °C in 2000 to −10.21 °C in 2020, which can be attributed to the reduction in socioeconomic activities during the COVID-19 period. UHI intensity intensified significantly across all climate zones, with the largest increases observed in the middle temperate zone and warm temperate zone, reaching 127.23 km²·°C and 116.04 km²·°C, respectively. Spatially, 39.8% of the 216 cities exhibited a significant increasing trend in UHI intensity, while only 2.8% showed a decreasing trend. After 2005, the contribution of large cities to UHI intensity continued to rise, reaching 54% in 2020. This study estimated UHI-induced energy consumption in terms of standard coal equivalent, with the northern and middle subtropical zones jointly accounting for over 61.9% of the annual average consumption. Regression results confirmed that impervious surface expansion served as the dominant positive driver of UHI, while vegetation coverage exerted a strong cooling effect. These findings can facilitate the formulation of region-specific UHI mitigation and energy conservation policies for cities under different climatic conditions and at diverse development scales. Mechanistic analysis further revealed that variations in impervious surface area dominated the rise in UHI intensity, whereas changes in the normalized difference vegetation index exerted a significant mitigating effect. These findings provide a solid scientific basis for targeted UHI mitigation and energy-saving management strategies for cities across different climate zones and urban scales. Full article

Rapid urbanization and climate change have severely exacerbated the urban heat island (UHI) effect in high-density subtropical megacities. Traditional linear models often fail to capture the complex, non-linear thermal responses driven by three-dimensional (3D) urban morphology and socio-ecological interactions. This study proposes a data-driven analytical framework explicitly tailored for macro/mesoscale climate-resilient urban planning to deconstruct the non-linear associations of Land Surface Temperature (LST) in Shenzhen, China. Integrating multi-source spatial data into a 500 m grid, we utilized the eXtreme Gradient Boosting (XGBoost) algorithm for high-precision LST modeling (R² = 0.7851, MAE = 1.1381 °C) and applied the SHapley Additive exPlanations (SHAP) approach for spatial interpretability. The results reveal critical non-linear thresholds: vegetation (NDVI) cooling efficiency saturates at 0.8, while impervious surfaces (ISA) transition into dominant heating drivers beyond 0.7. Notably, a synergistic effect indicates that high building volume density (BVD) significantly amplifies the marginal cooling benefits of vegetation. Furthermore, local SHAP attribution combined with K-Means clustering facilitated the delineation of four distinct thermal management zones. This framework shifts UHI mitigation from broad, uniform policies to precise, data-driven spatial diagnostics, offering actionable “one zone, one policy” strategies for sustainable architectural and climate-resilient urban planning. Full article

Cities are artificial ecosystems that suffer most from environmental issues and climate change. Urban Heat Island (UHI) effects represent an increasing challenge, especially for compact Mediterranean cities characterized by high population density and extensive impervious surfaces. This study assessed localized microclimatic conditions within the small Maltese coastal town of Isla through a 15-day summer field monitoring campaign. Air temperature, relative humidity, and wind speed were measured across urban locations characterized by different levels of vegetation coverage and thermal vulnerability. The analysis combined descriptive statistics, Mann–Whitney U testing, and Multiple Linear Regression (MLR) models. In addition, site-specific Nature-based Solutions (NbS) scenarios were proposed as context-sensitive strategies to support urban heat mitigation and climate resilience. The results highlighted distinct microclimatic responses between the sites investigated. In particular, the MLR analysis suggested that non-vegetated areas were more sensitive to short-term atmospheric variability associated with wind speed and relative humidity fluctuations. These findings suggest that urban vegetation may contribute not only to localized cooling, but also to increased microclimatic stability within compact Mediterranean urban environments. Full article

Urban heat island (UHI) mitigation is essential for improving urban sustainability by reducing heat stress, energy demand, and climate-related health risks. This study evaluates three rooftop measures—highly reflective roofs (HR), green roofs (GR), and rooftop water sprinkling (WR)—in Osaka Prefecture, Japan, using an integrated assessment framework. Temperature changes induced by each measure were simulated using the Weather Research and Forecasting (WRF) model and linked to energy consumption and health impacts through temperature sensitivity coefficients. Health impacts were quantified using disability-adjusted life years (DALYs), and all impacts were monetized for cost–benefit analysis. All measures reduced summer outdoor air temperatures, although their temporal and seasonal effects differed. HR and WR mainly produced daytime cooling, whereas GR provided stronger nighttime cooling. HR and GR increased residential energy consumption due to higher winter heating demand, while WR avoided this penalty through seasonal operation. All measures reduced office and commercial energy consumption and improved health impacts, with GR and WR producing larger benefits than HR. WR achieved the highest benefit–cost ratio, followed by GR and HR. These findings emphasize temporal characteristics, seasonal trade-offs, and spatial targeting in UHI policy. Full article

Urban growth and climate change intensify urban heat islands (UHIs), altering atmospheric stability and promoting the accumulation of particulate matter ≤ 10 µm (PM₁₀) and particulate matter ≤ 2.5 µm (PM_2.5), particularly in high-altitude megacities. However, there remains a scarcity of integrated dynamic models capable of representing these interactions at the intra-urban scale. This study develops a socio-environmental dynamic model to evaluate the influence of UHIs on PM₁₀ and PM_2.5 concentrations across localities of a high-altitude Latin American megacity (Bogotá, Colombia). A dynamic simulation model was developed in Vensim^®, integrating temperature, PM₁₀, PM_2.5, and citizen perception data. Statistical and spatial analyses were conducted to represent intra-urban thermo-atmospheric interactions. The results show that the model captures the influence of UHIs on PM₁₀ and PM_2.5 concentrations. Higher PM concentrations are simulated in localities with high imperviousness (PM₁₀: 33.4–50.4 µg/m³; PM_2.5: 21.5–25.1 µg/m³) and lower PM concentrations in areas with greater vegetation cover. Sensitivity analysis of the dynamic model reveals nonlinear amplifications of up to 15–20 µg/m³ in PM₁₀ and 8–10 µg/m³ in PM_2.5 associated with small thermal variations (1–2 °C). Under scenarios with significant UHI intensity, increases reach 4–6 µg/m³ in PM₁₀ and 3–4 µg/m³ in PM_2.5. These findings confirm that UHIs act as amplifiers of pollution and that urban thermal interventions could reduce PM concentrations by up to 10–20%. Full article

Urban–climate interactions in a warming climate remain largely uncertain; therefore, it is crucial to realistically evaluate and project these feedbacks to establish effective adaptation strategies. This study investigates projected shifts in summertime urban–climate interactions over eastern North America by employing the GEM regional climate model coupled with the Town Energy Balance (TEB) scheme, driven by RCP4.5 and RCP8.5 scenarios for the 1981–2100 period. Evaluations for the current climate (1981–2010) demonstrate that the model simulates an urban-induced warming of 0.5–0.7 °C and a precipitation reduction of 0.2–0.4 mm/day with high fidelity. By the late 21st century (2071–2100), projections under the RCP8.5 scenario indicate a steady weakening of the summer mean Urban Heat Island (UHI) intensity by approximately 0.10 °C, with a more pronounced nighttime attenuation of 0.15 °C. Physically, this weakening is attributed to an enhanced urban-induced evaporative fraction, which limits solar radiation storage within the urban fabric during the day, thereby reducing the thermal energy available for post-sunset release. This UHI attenuation correlates strongly with localized increases in precipitation, particularly in coastal regions where urban-induced effects contribute 20–40% to the total precipitation rise. While this study intentionally utilizes static urban boundaries to isolate the specific sensitivities of current urban morphologies to global warming, these results emphasize that diverse climatological regions will undergo distinct urban–climate feedback changes, providing essential baseline data for resilient urban planning. Full article

Climate change exerts growing pressure on the built environment, intensifying urban heat stress, altering microclimatic conditions, and increasing energy demand and health risks. Urban areas, characterized by dense construction and extensive soil sealing, are particularly susceptible to thermal anomalies such as Urban Heat Islands (UHIs), making thermal assessment a crucial element in adaptation and mitigation strategies. This research provides an updated and critical review of methodologies for the thermal evaluation of the built environment, with a focus on remote sensing as an emerging and integrative measurement paradigm. The study presents a comprehensive framework of detection systems, including satellite and aerial remote sensing, ground-based monitoring, and hybrid approaches, complemented by analytical and modeling techniques that combine physical and data-driven methods. A comparative assessment of open-access satellite sensors is carried out, analyzing spatial, spectral, and temporal resolutions and their relevance to urban-scale applications. The integration of remote sensing data with artificial intelligence, machine learning, and cloud-based processing is highlighted as a key advancement for improving interpretative, predictive, and decision-support capabilities. The findings indicate that such integration represents a new frontier for multiscale thermal analysis, supporting resilient urban planning, enhanced energy efficiency, and effective climate change mitigation policies. Full article