Search Results (150)

Urban green infrastructure is increasingly exposed to fine-scale thermal heterogeneity generated by anthropogenic point-source heat emissions, yet the leaf-level responses of adjacent vegetation to such localized stress remain poorly understood. Here, we examined whether air-conditioner (AC) exhaust, a widespread point-source heat emitter, is associated with functional trait shifts in Fraxinus chinensis street trees, and whether easily measurable leaf traits can serve as candidate indicators for ecological monitoring. Using a matched treatment–control field comparison, we compared trees located 2 m from operating AC units with unaffected controls and quantified nine leaf functional traits together with concurrent microclimate variables. AC exhaust created a distinct compound heat–drought–wind micro-environment at the 2 m patch scale, with higher air temperature (+6.3 °C), lower relative humidity (−12.3 percentage points), and higher wind speed (5.2-fold). Exposed trees showed a coordinated shift toward more resource-conservative leaf traits: leaf dry matter content (+14.8%), tissue density (+13.6%), leaf thickness (+6.3%), and stomatal density (+11.7%) increased significantly, whereas specific leaf area (−10.6%), leaf area (−12.5%), chlorophyll content index (−4.6%), and stomatal area (−10.4%) decreased significantly. The observed “small-and-numerous” stomatal configuration suggests altered stomatal regulation, although its implications for transpiration-driven cooling require direct physiological validation. Exploratory structural equation modeling suggested associations among AC-exhaust exposure, leaf economic strategy, and stomatal traits; stomatal regulation showed the highest proportion of model-explained variance (R² = 0.598), but this value should not be interpreted as direct evidence of impairment severity or restoration potential. Leaf dry matter content, specific leaf area, and stomatal density emerged as sensitive and practical candidate indicators of AC-exhaust-associated leaf functional shifts. These findings support precautionary management near AC exhaust outlets, while specific planting-distance thresholds and zoning frameworks require future validation through distance-gradient or manipulative experiments. Full article

Previous research has primarily focused on the restorative effects of environments on the general population, often overlooking the specific restorative capacity of urban settings for the disabled population. There is a lack of comprehensive investigation into the interaction between accessibility elements and urban restorativeness. This study, conducted in Shenzhen, Guangdong Province, China, categorizes streetscape accessibility elements for the disabled population and develops a recognition system based on an enhanced DeeplabV3+ framework. Semantic segmentation of streetscape accessibility elements was performed using 201,860 sampling points and 807,440 street view images. This study employed a combination of TrueSkill scoring, sentiment semantic analysis, LDA topic modeling, and LAB color clustering to quantify and visualize urban restorativeness. The impact of accessibility elements on urban restorativeness was explored using the XGBoost-SHAP model. Results indicate significant effects of architectural space constraints and high-density motor vehicle distribution on the safety of the disabled population’s mobility. The low pixel ratio of accessibility facilities and signs indicates insufficient infrastructure, while high landscape recognition rates exhibit significant spatial coverage heterogeneity. Detection rates for the disabled population in street views are nearly zero, highlighting a severe lack of inclusivity in pedestrian environments. Urban restorativeness exhibited a pattern of being higher in the south and east, and lower in the north and west. Among the accessibility elements, public green spaces (PGS) contributed the most to urban restorativeness, accounting for 25% of the impact, and the study elucidates the mechanisms through which various elements affect urban restorativeness. This absence stems from spatial competition, missing co-design, threshold effect conflicts, and color interference mechanisms. This research breaks away from traditional linear analytical frameworks and reveals the complex non-linear relationship between accessibility elements and urban restorativeness through the XGBoost-SHAP model, providing a quantitative decision-making tool for planning accessible environments in high-density cities. Full article

This study examines pedestrian perceptions of streetscapes in Isfahan’s cultural heritage site by integrating deep learning–based image segmentation with urban morphological analysis. It addresses the opportunity to develop a scalable and context-sensitive method for assessing pedestrian-oriented heritage streetscapes, particularly where conventional street-view datasets are unavailable. Using a U-Net model applied to First-Person Pedestrian View (FPPV) images, five perceptual indices, imageability, enclosure, human scale, greenness, and walking index, were quantified to examine their associations with pedestrian experience. Street width was incorporated as a morphological variable to explore its relationship with perceptual qualities using Spearman correlation and visual trend analysis. The results indicate exploratory associations between visual composition and perceptual outcomes within the analysed heritage streetscape context, particularly between imageability, enclosure, and vegetation structure. In contrast, variables such as human scale and walking index showed weak or negligible associations with street width, indicating that pedestrian activity patterns within the analysed heritage streetscape may be influenced by additional spatial, landscape, and socio-functional factors beyond dimensional characteristics alone. Segmentation-based analysis achieved an accuracy of 83% in classifying dominant streetscape elements, offering a reproducible alternative to traditional survey-based methods. This study contributes a data-driven framework for assessing pedestrian streetscapes, emphasising morphological continuity, human-scale design, and green infrastructure as important dimensions of walkability assessment. It also identifies key challenges, including fragmented spatial morphology and inconsistent urban furniture placement, which may affect pedestrian comfort and use of space. These findings offer evidence-informed design considerations for historic streetscape assessment, with implications for balancing heritage conservation and contemporary pedestrian needs. Future research may refine perceptual metrics, incorporate behavioural or longitudinal validation, and extend the approach across diverse urban contexts. Full article

This manuscript creates a framework for decision support based on green urbanism to direct the sustainable development of Gamasa, an Egyptian seaside city. The paper aims to convert the concepts of green urbanism into a multi-criteria evaluation that can support strategic urban development and prioritize spatial interventions. Sustainable mobility, green and blue infrastructure, energy and resource efficiency, urban form and density, social livability and public space quality, and governance and implementation feasibility are the six dimensions that are defined. These dimensions are derived from international sustainability literature and tailored to Gamasa’s particular challenges. The study’s methodology combines a multi-criteria decision-making approach based on the AHP with spatial analysis of land use, street hierarchy, building shape, and green space distribution. Weights for these dimensions are determined by expert-based pairwise comparisons, which are backed by a SWOT analysis. To prioritize priority zones for green transformation, the weighted framework is applied to four important urban areas: residential districts, a large urban park, the waterfront, and the main urban corridor. The top priorities, according to the results, are climate-responsive coastal design, increased green and blue infrastructure, and sustainable transportation. For quickly urbanizing coastal cities, the method demonstrates how the AHP operationalizes green urbanism into quantifiable, context-sensitive goals. Full article

This article examines sustainable urban morphological principles for new large cities, given that it may take decades for them to reach their target population and attain economic viability. Its novelty lies in the integration of these three fields of knowledge. It examines the grid model based on a comparative analysis of two new cities: Milton Keynes in the UK and Modi’in in Israel. The twenty years separating them embody a conceptual shift in urban development: from a modernist city to one that strives for premodern urban principles. Despite these divergent paradigms that pertain to the urban fabric, the comparison reveals significant similarities regarding state-level motivations, the grid’s advantages, the externalization of uses, and green qualities. The findings suggest that sustainable planning of new cities should incorporate three key components: (1) an initial infrastructure for human interaction through meeting points, not necessarily in commercial streets, despite their importance in established cities; (2) integrating urban elements to maximize connectivity, rather than planning each independently; and (3) adopting a green city concept, which provides not only ecological and psychological benefits but also planning flexibility, which is particularly crucial for new cities. Full article

The 2024 World Heritage inscription of the Beijing Central Axis shifts the focus of historic district governance to quality-oriented urban regeneration. However, evaluating the precise alignment between infrastructural topology and cultural meaning remains a methodological challenge. To move beyond macro-level assumptions, this study constructs a novel “spatial–semantic coupling” diagnostic framework. Integrating multi-source street-view data, Space Syntax, and the zero-shot semantic extraction capabilities of the CLIP model, we performed high-resolution visual semantic identification across 550 fine-grained sampling points in the 6.6 km² South Central Axis Core Area. Rather than merely observing a general “decoupling,” our diagnostic tool successfully mapped the complex spectrum of spatial alignments. While it accurately diagnosed areas with “idle spatial potential”—where high Global Integration (Mean = 0.924) fails to translate into Visual Attraction (r = −0.03) or Historical Perception (r = 0.01)—it also precisely identified “Synergistic” heritage cores and “hidden gems” within capillary hutongs. Furthermore, the framework diagnosed a severe “green island” effect (Mean = 0.26) and a structural contradiction between Spaciousness and Historical Perception (r = −0.33). By utilizing Bivariate LISA to geographically pinpoint these varying coupling characteristics (e.g., severe “High–Low” spatial frictions at gateway transportation hubs), this study establishes a highly scalable, data-driven analytical paradigm for targeted micro-renewal, ensuring the precise alignment of physical centrality and cultural perception in complex historic districts globally. 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

Most established street-vitality assessment tools were developed in temperate, predominantly Western urban settings and therefore do not adequately capture the climatic and socio-spatial conditions of hot–arid cities. This study develops and validates the Resident-Centered Street Vitality Framework (RCSVF) using Riyadh as a case study representative of the Arabian Desert urban context. Drawing on a cross-sectional quantitative design, the research integrates a resident survey across nineteen neighborhoods (N = 1102), physical observations of 133 street segments, a visual preference survey (N = 418), and GIS-based spatial analysis. The results reveal marked intra-urban inequality in perceived environmental quality and demonstrate that service proximity is a substantially stronger predictor of residential satisfaction than street physical quality alone. Residents consistently rated shading, green space, and pedestrian infrastructure as the weakest dimensions of their neighborhoods. These findings indicate that street vitality in hot–arid settings cannot be validly assessed through imported observer-based metrics. A resident-centered, climate-responsive framework is required to capture how thermal exposure, functional accessibility, and everyday social use interact in shaping street experience. Full article

Urban canyons, integral components of the built environment, significantly influence microclimatic conditions and thermal comfort. This review investigates their combined effects with green infrastructure on thermal comfort, offering a comprehensive framework for supporting urban design and greening strategies. The review is based on a structured literature analysis of peer-reviewed studies retrieved from major scientific databases (Scopus and Web of Science), following defined selection and screening criteria. Urban canyon orientation determines solar exposure and its interaction with prevailing wind patterns, affecting ventilation and heat dissipation. The urban canyon aspect ratio influences shading and airflow regulation, while their sky view factor moderates radiative cooling and daylight availability. Urban greening—encompassing street trees, green roofs, and vertical green walls—complements urban geometry by reducing air temperatures, enhancing evapotranspiration, and modifying local wind dynamics. Tree shading can reduce the physiological equivalent temperature in urban canyons, mitigating extreme heat stress. Key vegetative parameters, such as leaf area index and canopy density, are critical for quantifying cooling contributions. Key findings underscore the role of higher aspect ratios in enhancing shading and ventilation while they emphasize the critical influence of street orientation and sky view factor on microclimatic regulation. Vegetation emerges as a vital component, with tree shading contributing substantially to cooling effects and reducing physiological equivalent temperature. The beneficial synergistic interaction between urban geometry and vegetation optimizes thermal comfort. Tailored strategies based on urban canyon typologies balance urban development with environmental sustainability. The proposed framework provides actionable strategies for designing resilient and thermally optimized urban spaces, promoting climate-adaptive urban planning by addressing the dual challenges of the urban heat island and thermal discomfort in cities. Full article

Urban squares remain underrepresented in conservation-oriented literature compared with parks, street trees and green infrastructure. This scoping review uses CS-derived categories as an analytical lens to examine how the literature on urban squares frames conservation targets, direct threats, contributing factors and conservation actions. Following PRISMA-ScR, we searched Scopus and Web of Science for English-language peer-reviewed articles (2014–2024). After screening, 69 studies were included. Full texts were coded into CS-derived components and synthesised through frequency distributions, a cross-case conceptual synthesis, and an exploratory clustering of recurrent CF-DT-CT configurations. The reviewed literature is strongly centred on human-centred outcomes, particularly health, air quality and water quality, while biodiversity-related targets remain comparatively underrepresented. The most frequently investigated direct threats are pollution-related and linked to natural system management and modification, whereas other pressures are addressed less consistently. Contributing factors are dominated by meteorological conditions and vegetation coverage and composition. Reported conservation actions emphasise monitoring technologies, regulatory policy and green infrastructure, while others receive limited attention. Together, these analytical steps help make recurrent pathways and underrepresented dimensions more explicit, providing a more transparent evidence base for context-sensitive urban planning and nature-based solutions. Full article

Mapping urban tree species supports green infrastructure planning. An essential issue refers to the monitoring of exotic species that may become invasive. Street-level imagery provides a complementary perspective to aerial images for species identification that are difficult to distinguish from above. In this context, our study aimed to evaluate deep learning-based object detection and image segmentation approaches to identify a potentially invasive tree species known as Leucaena leucocephala in an urban environment in Brazil, using 422 street-level images acquired from Google Street View (SV) and mobile phones (MPs). Object detection models (YOLOv8 and DETR) and a foundation segmentation model (SAM, zero-shot) were applied to assess how deep learning paradigms perform under heterogeneous urban imaging conditions. YOLOv8 achieved detection performance with mAP50 above 0.83 and recall up to 0.76. DETR showed domain sensitivity, with mAP50 of 0.45 in SV images and 0.84 in MP imagery. For segmentation, SAM zero-shot achieved 0.92 accuracy and 0.93 F1-score in SV images, decreasing to 0.63 accuracy and 0.66 F1-score in MP images. Overall, this study demonstrates that combining detection and segmentation approaches provides complementary information for urban vegetation monitoring, supporting decision-making related to invasive species management and sustainable urban landscape planning. Full article

Urban street greenery plays a crucial role in enhancing biodiversity, environmental quality, and human well-being. However, how different street greening strategies shape urban plant diversity across functional urban contexts remains insufficiently understood. Taking Jinan, a rapidly urbanizing city in China, as a case study, this research investigates the spatial patterns, compositional differences, and driving mechanisms of plant diversity between Green Streets (GS) and Non-Green Streets (NGS) across various Urban Functional Units (UFUs). A 1 km × 1 km grid was used to delineate UFUs, combined with field-based plant surveys, linear regression analyses, and the public space assessment framework of Sustainable Development Goal (SDG) 11.7.1. Results indicate that plant diversity is strongly dependent on urban functional types, with higher species richness observed in residential and recreation/leisure districts, and lower levels in industrial, commercial, and transportation districts. The ecological effects of GS exhibit clear context dependence, being more pronounced in residential, educational, and public service areas, but limited in commercial and industrial zones. NGS recorded a significantly higher total number of plant species (346) than GS (116), with NGS dominated by native spontaneous species and GS characterized by introduced cultivated plants, reflecting the filtering effects of different management intensities. Management variables, particularly watering (positive) and fertilization frequency (negative), is primarily positively associated with plant diversity in GS, whereas diversity in NGS is more closely associated with socio-economic and spatial factors such as UFU area and housing prices. Furthermore, the current SDG 11.7.1 indicator emphasizes the quantity and accessibility of public spaces but insufficiently captures their ecological quality. This study highlights the need to integrate biodiversity and vegetation structural complexity into public space assessments, providing scientific support for quality-oriented urban green infrastructure planning and sustainable urban development. Full article

With China’s urban growthism past its peak, urban development has shifted from incremental expansion to inventory quality improvement. Renovating historical and cultural blocks—a core area for urban quality enhancement—makes exploring their integration with surroundings highly significant. Existing studies on historical district research mainly focus on single-dimensional research such as protection policies, spatial structure analysis, and quality evaluation, lacking a systematic and quantitative evaluation of the spatial integration degree between historical and cultural blocks and their surrounding areas. To improve research on the integrated development of historical and cultural districts and their surrounding areas, this study employs deep learning and machine learning techniques to process street view images from 2721 data points in 2024, investigating the integration of Wuhan Hankou’s historical and cultural districts with their surrounding areas. The spatial integration degree between a historical and cultural district and its surroundings refers to the coordinated development level in terms of history and culture, spatial ecology, and transportation infrastructure. Specifically, the DeepLab v3+ model processes the blocks’ street view images to generate indicator data (Green Visual Index, Sky Visibility Index, Road Area Index, Spatial Enclosure Index, Color Richness (Wheel), Color Richness (Entropy), Spatial Accessibility Index, Vehicle Disturbance Index, Traffic Sign, which is used to quantify the historical culture, spatial ecology, and transportation facilities of historical and cultural blocks and their surrounding areas. The Coupling Coordination Degree model evaluates spatial integration, while the Geodetector Model quantitatively analyzes interactions between spatial integration and driving factors here. The results show that the spatial interaction and dependence between the Hankou Historical and Cultural District and its surrounding areas are relatively high, but spatial coordination is insufficient; the integration remains at a primary stage with structural contradictions. SVI, SEI, and RAI have a significant impact on integration, while Spatial Accessibility Index, Green Visual Index, and CRW have a moderate influence, and CRE, Vehicle Disturbance Index, and Traffic Signs have a relatively weak impact. Among them, SVI exhibits the strongest interactive effect with other indicators and plays a leverage role in improving integration. Full article

Current sustainability discourse promotes sustainable yard practices as a means for residents to contribute to urban environmental health and soil conservation. Social–ecological research suggests that yard practices are shaped by multiscale social drivers, including social contagion, whereby visible expressions of individuality in front yard design are copied by nearby neighbors. This study evaluated residential areas within the Río Piedras Watershed (RPWS) in the San Juan metropolitan area to assess evidence of social contagion in front yard configuration and vegetation structure, and to examine whether these variables were associated with socio-demographic and economic characteristics when spatial effects were considered. A total of 6858 front yards across six highly urbanized sites were analyzed using Google Earth Street View imagery. Housing lot sizes were quantified, and yards were classified into eight landscape configurations based on green and gray cover elements. Woody vegetation structures, including trees, shrubs, and palms, were also quantified to generate estimates of functional diversity and a front yard quality index. Significant differences in yard characteristics were observed among sites. Spatial analyses revealed significant clustering at distances of 65–80 m, particularly for front yard configuration, while clustering of woody vegetation density was weaker. Local clustering patterns and the distribution of outliers varied across sites. Spatial lag models indicated that lot area positively influenced yard configuration and quality, and the density and diversity of woody vegetation. While socio-economic variables were not significant predictors of yard quality, their effects cannot be discarded. Overall, results are consistent with social contagion processes but also highlight neighborhood design as a key driver of clustering, alongside widespread conversion of green to paved front yards, with implications for soil and green infrastructure loss as well as environmental and human health in the RPWS. Full article

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a 1D-2D-coupled hydrodynamic model (InfoWorks ICM). The model was calibrated using continuous monitoring data, achieving a Nash–Sutcliffe Efficiency (NSE) of 0.91. Its spatial accuracy was subsequently validated against historical waterlogging records, showing a strong consistency between simulated flood-prone areas and observed flood locations. We simulated waterlogging distribution under rainfall events with return periods of 0.5 to 5 years. Results reveal two key deficiencies in the current drainage system under a 0.5-year return period storm event. Firstly, 75.3% of the pipe segments are hydraulically overloaded, failing to meet the design standard. Secondly, this widespread network overload contributes to surface waterlogging, with 9.58 ha (1.80% of the total area) being waterlogged. We evaluated three strategies: Low Impact Development (LID), underground storage tanks, and intercepting sewers. A hybrid grey-green infrastructure (HGGI) system was proposed, integrating source reduction and terminal storage. The HGGI system reduced waterlogged areas by 83.58% (0.5-year event) and 64.87% (5-year event), outperforming single measures. Crucially, this hybrid system achieves minimal intervention in historic street patterns through trenchless construction for intercepting sewers, decentralized LID layout and underground storage tanks, avoiding large-scale road excavation while enhancing flood resilience. This study demonstrates that hybrid strategies can effectively balance flood resilience with environmental and cultural preservation in high-density historic districts. Full article