Search Results (942)

The rapid development of high-density cities has triggered severe ecological challenges, including habitat fragmentation, urban heat island (UHI) effects, and conflicting demands for public recreation. Traditional ecological networks (ENs) often focus only on “source” landscapes while neglecting degraded “sink” areas. This bias limits the ability of planners to resolve complex spatial conflicts. Therefore, the primary aim of this study is to develop a robust spatial planning framework that mitigates urban ecological conflicts and enhances regional resilience. To achieve this, we constructed a composite ecological network (CEN) for the high-density city of Guangzhou that harmonizes bird habitat conservation, thermal regulation, and cultural recreation. We combined the MaxEnt model, morphological spatial pattern analysis (MSPA), and circuit theory to identify functional “sources” and “sinks” across these three dimensions. Next, using complex network theory, we optimized the CEN and evaluated its structural robustness using low degree addition (LDA) and low betweenness addition (LBA) strategies. The results indicate the following: (1) The CEN effectively captured the complex mosaic landscape of the city. (2) Single-objective networks displayed distinct spatial differences—the recreational network formed a dispersed web of 242 corridors, while habitat and climate networks remained highly clustered. (3) The integrated CEN generated 1137 multi-layered corridors, creating a vital green skeleton to support species dispersal, mitigate UHI effects, and improve cultural access. (4) Optimization simulations verified that the LBA strategy provided the highest stability against targeted attacks by balancing network connectivity with local aggregation. Ultimately, this framework offers a highly adaptable planning tool for dense cities, providing precise spatial guidance to overcome ecological bottlenecks and harmonize urban growth with ecosystem resilience. Full article

The urban heat island (UHI) effect has become a global environmental challenge, and quantifying the spatial heterogeneity of its driving mechanisms while developing differentiated regulation strategies remains a critical research gap. This study takes Berlin, Germany as a case study, integrating spatial autocorrelation analysis with a coupled geographically weighted regression (GWR) model to systematically investigate the spatial heterogeneity of the driving mechanisms of Local Climate Zones (LCZs) on surface urban heat island intensity (SUHII), and proposes refined regulation strategies. First, the WUDAPT method was employed to generate a LCZ map, and global and local Moran’s I were used to identify SUHII spatial clustering characteristics, dividing the study area into High–High (HH), Low–Low (LL), and Not Significant (NS) clustering zones. Second, Ordinary Least Squares (OLS) and GWR coupled models were constructed to analyze the global and local relationships between LCZ composition and SUHII. The results indicate: (1) Berlin’s SUHII exhibits significant spatial clustering characteristics (Moran’s I = 0.984), with clear differentiation between the HH zone (25.8%, mean 2.67 °C) and the LL zone (26.4%, mean −0.16 °C); (2) the GWR model (R² = 0.921, AICc = 1279.538) significantly outperforms the OLS model (R² = 0.822, AICc = 2871.608), confirming strong spatial heterogeneity in the LCZ-SUHII relationship, with more pronounced advantages of GWR in urban–rural fringe areas; (3) LCZ 5 (low-density mid-rise buildings) and LCZ 2 (high-density mid-rise buildings) are key warming factors across the entire study area, but their warming effects are stronger in suburban areas than in central urban areas; LCZ A (dense trees) and LCZ G (water bodies) are key cooling factors across the entire area, but their cooling effects are stronger in central urban areas than in the suburbs. Based on these findings, this study establishes a differentiated strategy framework of “Zoning—Identifying Heterogeneity—Regulating”, proposing that HH zones should implement “carbon sink enhancement and source reduction”, NS zones should balance “ecological expansion with growth management”, and LL zones should adopt “strict protection and development restriction”. This framework provides a quantifiable scientific basis and practical guidance for refined urban thermal environment management. Full article

Rapid urban expansion is reshaping large metropolitan regions into polycentric systems in which multiple centers interact through transport, infrastructure, land-use, economic and ecological networks. Urban heat island (UHI) research has traditionally relied on single-city or core–periphery models; these remain useful for explaining heat contrasts within individual cities, but are insufficient for explaining how thermal loads form, propagate and accumulate across interconnected metropolitan regions. This study combines bibliometric analysis and a PRISMA-guided systematic review to synthesize research on UHI processes in polycentric cities, mega-urban regions and metropolitan systems. The bibliometric corpus comprises 468 Scopus-indexed records published in 2020–2025, while 35 full-text studies were retained for qualitative synthesis. The results show strong publication growth from 54 records in 2020 to 124 in 2025, an annual growth rate of 18.09%, and an interdisciplinary evidence base led by environmental science, social science, Earth-system science and engineering. Three spatial patterns recur across the core studies: multi-core hotspots, corridor-based heat propagation and peripheral thermal expansion. The review contributes a network-based interpretation of UHI as a nested metropolitan process in which node morphology, functional hierarchy, transport connectivity, blue–green infrastructure (BGI) and governance coordination jointly shape heat intensity, footprint and exposure. Rather than displacing single-city or core–periphery interpretations, the proposed framework extends them by positioning local heat analysis as one layer within a larger multiscale heat-governance architecture. 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

The recast Energy Performance of Buildings Directive (EPBD) accelerates the transition from nearly zero-energy buildings (nZEBs) to zero-emission buildings (ZEBs), requiring solar readiness and life-cycle Global Warming Potential (GWP) disclosure. Yet operational performance, future-climate adaptation and whole-life carbon (WLC) are still often assessed separately, limiting actionable evidence for residential ZEB design in northern climates. This study provides an integrated design-decision framework coupling annual IDA-ICE simulations under five weather scenarios, including Urban Heat Island (UHI)-adjusted present and 2080 RCP8.5 + UHI files, with an EN 15978/Level(s)-based WLC assessment in One Click LCA for twelve design cases of a Lithuanian dwelling. For the PV-equipped baseline, heating electricity decreases by 24% and cooling increases by 31% from present conditions to 2080 RCP8.5 + UHI. External shading and night purge provide the strongest annual cooling and operative-temperature-exceedance reductions. The ZEB baseline reduces WLC by 19.0% relative to A0; the biogenic-insulation green-roof case gives the lowest non-storage WLC (−25.2%); and battery-assisted cases provide the largest reductions under the static B6 electricity factor (up to −52.1%). The findings provide case-study evidence that EPBD-aligned residential ZEB design should evaluate passive cooling, PV/storage and material choices jointly, rather than sequentially, when developing future performance thresholds and design guidance. Full article

Rising temperatures within the urban context, as a result of climate change and the Urban Heat Island effect, have deteriorated thermal comfort conditions in outdoor urban spaces, especially during hot, Mediterranean summer days. This study investigates the potential cooling effects of integrating individual urban green spaces into a connected network, with the aim of improving thermal conditions in public areas. Thermal conditions of an 800 m² urban area in the city of Athens, Greece, were evaluated for a typical summer day using the environmental model ENVI-met. Based on an assessment of the current microclimatic conditions, a potential thermal adaptation strategy was developed, aiming to redesign the study area as a network of green-blue infrastructure. This includes a 1.5 km walking route connecting various spaces, such as squares, parks, and schools. Air temperature (Tair) and the bioclimatic index PET (Physiologically Equivalent Temperature) were used to evaluate the thermal conditions of the study area. In addition, a new function of the ENVI-met model, Dynamic Comfort, has been implemented to calculate the dynamic Physiological Equivalent Temperature (dPET) index for the selected route. The results revealed significant Tair and PET reductions compared to the current layout, indicating that the integration of open spaces into a network of green-blue infrastructure can improve thermal conditions and reduce the hazardous effects of thermal stress on people. Some notable results include the spatial and temporal decrease of the Tair of up to 6 °C, mainly in the proximity of buildings and fountains. Similarly, PET values decreased mainly by 3 to 5 °C. The Dynamic PET showed a slight reduction during the hours of maximum temperature and a higher decrease during the evening, ranging from 1 to 2 °C. Full article

As urban areas expand, the sustainable management of municipal water becomes a critical challenge, especially in arid and semi-arid regions facing severe water scarcity. Accurate assessment of urban plant water requirements (PWR) is essential for developing sustainable landscape architecture and resilient green infrastructure. In this study, a new quantitative equation (PWR_q) was developed as a regional proof of concept to adjust reference evapotranspiration estimates for hyper-arid conditions. A Tree Morphology Coefficient (K_tm) is introduced to combine canopy features (form, height) and leaf traits (size, density) with an updated drought-resistance coefficient (K_dr). Field measurements of 277 mature trees, representing 27 native and introduced species in Riyadh and Jeddah, Saudi Arabia, were analyzed. The framework explicitly includes an empirical multiplier to account for extreme urban heat island (UHI) effects and aerodynamic canopy scaling. Instead of direct empirical validation, the PWR_q model was benchmarked against established reference indices: Water Use Classification of Landscape Species (WUCOLS) and Simplified Landscape Irrigation Demand Estimation (SLIDE), showing strong alignment with established categorical indices and structural traits. The results confirm that the morphology-based method effectively makes previously subjective classifications objective. Notably, the quantitative assessment found that the dominant introduced species require about 3.5 times more water than native species. As a proof of concept, future research should empirically validate these findings against direct physical measurements, such as sap flow sensors or lysimeters. The proposed framework presents a practical, objective decision-support tool for municipal policymakers and landscape architects to optimize species selection, implement nature-based solutions (NBS), and achieve long-term sustainability in urban greening. 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 areas in Mediterranean climates are increasingly affected by extreme heat, exacerbated by the Urban Heat Island (UHI) effect and the lack of climate-responsive public spaces. This study addresses the need for integrated methodologies combining empirical monitoring and simulation tools to support regenerative urban design. The objective is to evaluate the effectiveness of Nature-Based Solutions (NBSs) in improving microclimatic conditions and outdoor thermal comfort during summer heatwave periods in a vulnerable urban area in Seville (Spain). A mixed-method approach combining microclimatic monitoring and ENVI-met simulations in situ was applied. A field campaign conducted in summer 2023 was used to characterize baseline conditions and calibrate the model, which simulated both current and proposed scenarios incorporating vegetation, shading systems, permeable materials, and water features. Results from the Seville case study show significant improvements, with air temperature reductions of up to 1.6 °C (daytime) and 1.9 °C (nighttime), surface temperature decreases of up to 11 °C, and thermal comfort improvements reaching 8 °C in UTCI. Beyond environmental benefits, the intervention promotes socially regenerative public space by enhancing usability, inclusivity, and comfort. Limitations include the use of a single representative summer day and inherent simplifications of the ENVI-met model. These findings demonstrate the potential of integrated NBS strategies to mitigate urban heat and support climate-adaptive and socially responsive urban design. 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

Amid growing concerns over global warming, ensuring the outdoor thermal comfort (OTC) of public urban spaces is crucial for creating liveable and resilient cities. This study focused on the intensification of the urban heat island (UHI) effect and the heat stress experienced by the vulnerable older population. Evidence was found through the case study in a highly vulnerable area of Porto, with a high ageing ratio. The primary aim was to assess the influence of design-based adaptation strategies on OTC using ENVI-met, with a specific focus on older adults. Thermal stress was evaluated using the Physiological Equivalent Temperature (PET) index. The analysis confirms that older adults consistently experience higher PET values (+2–5 °C) and larger areas of thermal discomfort than active-age adults. Simulations reveal that the effectiveness of adaptation measures depends on the characteristics of the urban space but enhanced green infrastructure achieves the most significant heat mitigation results. Artificial shading only provides localized thermal relief. Cool pavements contribute meaningfully by lowering surface heat storage and reducing longwave radiation. However, their impact on PET, beneficial or detrimental, depends significantly on the morphology of the outdoor space and the materials used. In the analysed street canyon, PET was higher in the central hours of the day for both age ranges, when the pavement material had a higher albedo. An effective heat mitigation needs a combination of vegetation-based strategies and climate-responsive materials to ensure comfortable and age-inclusive public spaces. This research presents an actionable methodological approach for evaluating and enhancing OTC, advocating the use of microclimate simulations in a carefully selected set of public spaces within an intervention urban area to define effective climate adaptation measures for each space. Full article

Rapid urbanization in South Asian coastal cities is systematically dismantling natural cooling infrastructure, driving unprecedented urban heat island (UHI) intensification with severe consequences for human health, energy systems, and urban livability. Despite growing research attention, comprehensive frameworks that simultaneously capture temporal UHI dynamics, machine learning-based thermal projections, and community-grounded validation remain scarce, particularly for secondary coastal cities in tropical developing regions. This study addresses these gaps by investigating UHI dynamics in Chattogram City Corporation (CCC), Bangladesh, through three integrated methodological pillars: (1) multi-temporal remote sensing analysis using Landsat 5 and 8 imagery spanning 2005–2025; (2) comparative evaluation of five machine learning algorithms (LightGBM, Random Forest, XGBoost, SVM, and MLP) for land use/land cover (LULC) classification and land surface temperature (LST) regression, with iterative scenario projections for 2029, 2033, and 2037; and (3) a structured public perception survey of 384 residents validated through participatory mapping and focus group discussions. Landsat analysis revealed dramatic LULC transformations: built-up areas expanded 88% (12,649 to 23,719 acres), while waterbodies declined 53.1% and vegetation decreased 21.9%. Mean LST increased by 9.09 °C (from 30.94 °C to 40.03 °C), with mean UHI intensity rising from 19.59 to 33.88 standardized units over two decades. LightGBM achieved optimal LULC classification (F1-weighted: 0.765) while Random Forest best predicted LST (RMSE: 1.51, R²: 0.809). Projections indicate continued thermal escalation, with mean LST reaching 43.64 °C and UHI intensity exceeding 37.41 standardized units by 2037. Persistent thermal hotspots were identified in the southwestern coastal corridor, western industrial belt, and central business district. Community survey data corroborated satellite-derived patterns, with 73.44% of respondents observing environmental degradation, yet only 22% aware of formal heat mitigation policies, and 87% supporting vegetation-based cooling interventions. This integrated framework advances urban thermal monitoring in tropical coastal cities and provides spatially targeted, community-endorsed evidence for climate-responsive urban planning. Full article

Rapid urbanization and complex topography complicate Urban Heat Island (UHI) spatio-temporal dynamics. Traditional models and coarse-resolution imagery often fail to capture fine-scale, spatially non-stationary seasonal driving mechanisms. This study investigates the multi-dimensional drivers of surface thermal dynamics in Kunming, a typical low-latitude plateau city, using seasonal median LST composite (2018–2025). Integrating eXtreme Gradient Boosting (XGBoost) with eXplainable Artificial Intelligence (XAI) models decoupled the nonlinear impacts of these drivers. Results reveal a seasonal thermal dichotomy: Summer exhibits the most intense UHI effect with extreme peak temperatures, while Spring presents an anomaly where natural and vegetated Local Climate Zones (LCZs) show pronounced warming. SHapley Additive exPlanations (SHAP) analysis identified a seasonal rotation: anthropogenic and structural factors dominate Summer and Autumn warming, whereas natural and topographic regulators govern Spring and Winter. GeoShapley deconstruction demonstrated strong spatial non-stationarity. Building-density warming is amplified in poorly ventilated urban cores, and fragmented vegetation’s cooling is offset by anthropogenic heat during peak summer. This study provides new insights into the seasonal drivers of urban thermal environments in plateau cities. Full article

As a critical component of urban ecological infrastructure, urban forests play a pivotal role in regulating regional climate and mitigating the urban heat island (UHI) effect. However, existing studies have predominantly focused on single temporal snapshots or aggregate spatial scales, with limited attention to the seasonal dynamics of urban forest landscape patterns and a lack of systematic quantification of their nonlinear regulatory mechanisms. Empirical evidence from subtropical cities remains particularly scarce. In this study, Hangzhou was selected as the study area. Land Surface Temperature (LST) was retrieved using the Google Earth Engine (GEE) platform, and the Thermal Field Variance Index was employed to classify UHI intensity. Six representative forest landscape indices were selected to construct an evaluation framework. Pearson correlation analysis and the XGBoost model were further applied to quantify the relationships between landscape patterns and seasonal LST variations. The results reveal that: (1) LST in Hangzhou exhibits pronounced seasonal variability, following the order of summer > spring > autumn > winter. Areas without UHI effects dominate in spring, summer, and autumn, whereas the extent of strong UHI zones increases markedly in winter. (2) All landscape indices are significantly correlated with seasonal LST; forest ratio and forest largest patch index show negative correlations, while forest patch density, forest landscape shape index, number of patches, and landscape division index (DIVISION) are positively correlated. (3) The XGBoost model indicates that DIVISION consistently exhibits high contribution across all seasons, identifying it as a key determinant of LST variation. These findings provide a scientific basis for optimizing urban forest landscape configuration and developing effective UHI mitigation strategies. Full article