Search Results (526)

Under the growing threat of urban heat stress, street canyons play a critical role in shaping the pedestrian thermal environment. While street greenery is an effective mitigation strategy, its performance varies substantially with physical characteristics—such as aspect ratio, street width, and sidewalk width—highlighting the need for spatially adaptive design. This study evaluates the effects of sidewalk width, street orientation, and planting structure on thermal conditions in a humid subtropical climate in Daegu Metropolitan City, Republic of Korea. The analysis focuses on open low-aspect-ratio street canyons (H/W = 0.86 for E–W and 0.43 for N–S orientations). Using a validated ENVI-met (Version 5.6.1) model based on field measurements from Daegu, Republic of Korea, 56 street-greening scenarios were simulated by systematically varying sidewalk width, street orientation, planting rows, spacing, and planting structure. Results show that multi-row planting served as the primary structural framework governing thermal performance. Optimal configurations varied with sidewalk width, with two-row planting for 6 m sidewalks and three-row planting for 10 m sidewalks providing the most effective cooling. The greatest cooling (−2.02 °C) was achieved when optimized multi-row configurations were combined with multi-layer planting. Once optimal multi-row configurations were established, the presence of understory vegetation had a greater influence on thermal improvement than its specific composition, allowing flexibility in understory design. Clear spatial asymmetries were identified, with the highest thermal stress occurring on the north-side sidewalk in E–W streets and the west-side sidewalk in N–S streets. Targeted planting in these locations produced greater cooling benefits than uniform strategies. These findings provide a spatially grounded framework for climate-responsive street greenery and offer practical design guidance, highlighting the need for context-specific, optimized multi-row planting strategies adapted to local urban and climatic conditions. Full article

Building inclusive, high-density cities requires understanding vulnerable groups’ public space usage. While green exposure significantly impacts urban health, existing research frequently overlooks females’ specific needs regarding streetscape visual quality, green space structures, and daily travel experiences. To address this, the study investigates spatial disparities in Suzhou’s historic district. Utilizing multi-source data and mixed modeling strategies, including Partial Least Squares and Ordinary Least Squares (PLS-OLS) and eXtreme Gradient Boosting (XGBoost), the research analyzes how streetscape perceptions and green space characteristics affect female life satisfaction and expressed sentiment. Results indicate three main findings. (1) Streetscape visual features fundamentally drive subjective evaluations. Safe significantly enhances well-being, whereas boring and lively negatively impact life satisfaction, reflecting females’ acute sensitivity to environmental oppressiveness during daily travel. (2) Park diversity elevates expressed sentiment, while patch density positively influences life satisfaction, demonstrating the vital value of fragmented greenery for daily public space usage. (3) Boring precipitously diminishes life satisfaction after surpassing a specific threshold, while park diversity elevates expressed sentiment only after crossing a critical interval. The study establishes an integrated analytical framework linking visual perception, green space structure, emotional response, and satisfaction. These findings provide targeted strategies for enhancing inclusive urban design and optimizing green space allocation to improve streetscape safety and alleviate visual oppressiveness, thereby advancing gender social justice for vulnerable groups in historic districts. Full article

This pilot study examines how experimentally induced emotional states interact with the visual properties of urban environments to shape comfort perception. A controlled laboratory experiment was conducted with 17 participants assigned to one of four emotional conditions (Fear, Anger, Sad, Happy) through audio-visual induction. Participants evaluated 73 building façade and 42 pedestrian streetscape stimuli from three urban areas in Kitakyushu, Japan (Wakamatsu, Tobata, Mojiko) using a multi-method framework combining fractal analysis (D, Λ), six pedestrian visual metrics, webcam-based eye-tracking (Visual Attention Score, VAS), and self-reported comfort votes. Emotion induction was effective for Fear and Anger groups and partial for Sad and Happy groups, with the latter attributable to experimental fatigue. Cross-method correlation analysis revealed that fractal dimension D significantly predicted comfort vote consensus (Spearman r = 0.369, p = 0.013), while VAS showed no significant relationship with comfort votes (r = 0.097, ns) or with fractal dimension (r = 0.015, ns), confirming that visual attention and comfort preference are independent dimensions. For building façades, the ‘Complex but Organized’ fractal profile (D ≥ 1.70, Λ < 0.60) was the consistent comfort driver across all emotion groups. For pedestrian streetscapes, low spatial enclosure and spatially integrated tree canopy were the primary comfort predictors. Multi-method synthesis identified five empirical paradoxes and three design principles: (1) target D ≥ 1.70 with Λ < 0.60; (2) prioritize spatially integrated canopy over visible greenery quantity; and (3) leverage civic legibility as an independent comfort pathway. These findings support the development of emotion-independent frameworks for urban comfort evaluation. Replication with larger, more diverse samples is recommended. Full article

Understanding the complex relationship between the built environment and urban vitality is essential for evidence-based urban renewal. However, most existing studies rely on linear regression models that fail to capture the non-linear threshold effects inherent in urban systems and depend on costly proprietary datasets that limit reproducibility. This study proposes a scalable, open-data-driven framework to decode the non-linear mechanisms governing population-based urban vitality in Zhengzhou, a rapidly regenerating metropolis in Central China. Using Areas of Interest (AOIs) as functional spatial units to mitigate the Modifiable Areal Unit Problem (MAUP), we construct a multidimensional built environment indicator system (5D+S: Density, Diversity, Design, Distance to Transit, Destination Accessibility, and Surroundings) from multi-source open data, including 100 m WorldPop population grids, OpenStreetMap building vectors, Points of Interest (POIs), and transit station data. An explainable machine learning approach combining XGBoost with SHapley Additive exPlanations (SHAP) is employed to identify the relative importance of built environment factors and quantify their non-linear threshold effects on population-based urban vitality (operationally defined as residential population density derived from WorldPop 100 m grids). Across 3920 AOIs, XGBoost (R² = 0.846, RMSE = 0.104) substantially outperforms Ordinary Least Squares regression (R² = 0.634), confirming pervasive non-linear relationships, with stable 5-fold cross-validated R² = 0.713 ± 0.115. SHAP analysis reveals four dominant drivers: Distance to Commercial Core (DistCBD), Bus Station Density within 500 m (BusDen500), Green Coverage Ratio (GreenRatio), and Building Density (BD). Critical thresholds are identified: vitality contributions decay sharply beyond approximately 4.3 km from the CBD; at least 4 bus stations within 500 m are required for meaningful transit benefit; building density delivers positive returns within a 2–30% range; and excessive green coverage above 8.5% within 500 m is associated with declining population-based vitality, a finding that reflects spatial competition between ecological land use and residential density rather than a negative effect of greenery per se. These findings provide quantitative design guidelines for precision urban renewal, moving beyond “the more, the better” planning assumptions to identify optimal intervention ranges. Full article

Deep learning-powered Street View Imagery (SVI) analytics provides a critical mechanism for smart city perception within the framework of Sustainable Development Goal 11 (SDG 11), effectively bridging the gap left by traditional remote sensing in fine-grained street-level observation. Over the years, deep learning-based semantic segmentation of urban streetscapes has become the dominant paradigm. However, when scaling to megacity measurements, current research faces the dual bottlenecks of “computational redundancy” and the “geographical domain shift” caused by the blind application of pre-trained models based on Western datasets. To address these challenges, this study is the first to systematically quantify the performance trade-off between Multi-Task Learning (MTL) and Single-Task Learning (STL) in megacity scenarios. Using this as a baseline, we constructed and validated a “low-computation, high-robustness” framework for streetscape semantic perception and spatial measurement. Relying on an integrated ResNeXt101-FPN MTL architecture and an ultra-low-cost fine-tuning strategy to overcome geographical domain shift, we extracted and analyzed the spatial heterogeneity of five core semantic elements—vegetation, sky, building, road, and vehicle—across the road network within Beijing’s 5th Ring Road. The results indicate the following: (1) We explicitly defined the computation-accuracy trade-off of MTL and STL in megacity perception. While utilizing only 1/5 of the parameters of STL, the MTL framework achieved a 5.34-fold increase in inference speed with a negligible 0.1% loss in overall mean Intersection over Union (mIoU); however, a 27.13% decrease in boundary segmentation accuracy was observed. (2) We established a low-cost, localized correction paradigm to overcome domain shift. Utilizing a minimal annotation cost (only 200 local images) significantly improved cross-domain adaptability, boosting the overall mIoU by 8.92% and significantly mitigating the geographical domain shift problem. (3) Multi-dimensional measurement and spatial analysis revealed a significant spatial decoupling pattern in Beijing’s streetscapes. The visual proportion of vegetation exhibited a pronounced “north-high, south-low” spatial differentiation, whereas built environment elements (e.g., building and road) displayed a typical “center-periphery” concentric gradient. This objectively reflects the spatial inequality of urban street greenery resources and the monocentric development characteristics of the built environment. The proposed framework therefore serves as a low-cost, AI-driven computational paradigm for smart city perception in resource-constrained regions. Furthermore, the revealed spatial heterogeneity offers data-driven insights for formulating sustainable urban renewal policies aligned with SDG 11. Full article

Perceived street vitality directly reflects residents’ assessments of the attractiveness of the street environment; it is not only an important focus of urban vitality research but also closely related to human-centred sustainable urban development. However, limited data availability and the complexity of urban environments have constrained fine-grained spatial analysis at the city scale. To address this issue, this study quantified perceived street vitality by collecting street-view imagery, extracting streetscape features, and integrating these data with questionnaire survey results. After comparing multiple models, a geographically weighted machine learning model was employed to identify key visual predictors, model-estimated marginal associations, interaction patterns, and spatial heterogeneity related to perceived street vitality. The results show that areas with high perceived street vitality are mainly located along street segments with abundant greenery and open spaces, whereas low-value areas are concentrated in densely built and enclosed environments. Among the various streetscape elements, buildings, vegetation, and sky are the key visual elements most strongly associated with perceived street vitality. A model incorporating these elements accounted for 67.2% of the variance in perceived street vitality. Notably, the strength of these associations varied significantly across different areas. This study provides empirical evidence and evidence-based support for sustainable urban renewal, the optimisation of street-space layouts in high-density urban areas, and the improvement in street environmental quality. Full article

Background/Objectives: Although urban greening interventions are increasingly implemented to improve livability, environmental quality, and adaptation capacity in cities, their evaluation still predominantly relies on physical outputs rather than validated, resident-centered outcomes. This study examined whether the five-item attachment dimension of the Urban Green Attachment Scale (UGAS) can reliably indicate the social integration of newly introduced greenery in an SDG 11-oriented evaluation context. The present adaptation of the UGAS captures the perceived importance of the planting, its contribution to well-being, anticipated loss, willingness to protect it, and aesthetic appreciation. Methods: Data were collected through two independent face-to-face surveys conducted among residents of the same housing estate shortly after a greening intervention in May 2025 (n = 150) and September 2025 (n = 191). The first sample was used for exploratory factor analysis (EFA) and the second for confirmatory factor analysis (CFA). Reliability was assessed using Cronbach’s α and McDonald’s ω; inter-item associations were estimated using Kendall’s tau-b; and construct validity was examined through known-groups comparisons with theoretically relevant appraisals and stewardship-related indicators. Results: The adapted UGAS demonstrated high internal consistency, low floor and ceiling effects, and moderate to strong inter-item associations. Exploratory factor analysis supported a unidimensional solution with high loadings and 65.7% explained variance, and confirmatory factor analysis corroborated this structure after minor, theory-guided localized refinements. Higher UGAS scores were consistently observed among residents who reported stronger calming and home-related effects, perceived healthier local conditions, expressed willingness to help care for the plants, and demonstrated a readiness to cooperate in improving the area. Conclusions: The results support the five-item UGAS attachment score as a compact, psychometrically adequate measure of residents’ attachment to newly planted urban greenery. Rather than replacing official SDG indicators, the UGAS can complement them at the project level by determining if urban greening becomes socially meaningful and accepted and if it supports stewardship. In this sense, UGAS offers municipalities a practical tool for linking physical greening outputs with resident-centered outcomes relevant to inclusive public spaces, participatory urban development, and the long-term social durability of urban greening interventions. Full article

Traditional urban landscape evaluations have primarily relied on either objective spatial metrics, such as the Green View Index (GVI), or subjective human surveys, often failing to capture the complex mechanisms of human environmental perception. This study proposes a novel Explainable Artificial Intelligence (XAI) framework that integrates objective physical configuration with subjective cognitive assessment to predict human landscape preference. Utilizing 159 urban landscape images, we extracted physical features via semantic segmentation (SegFormer) and psychological perceptions via a zero-shot vision-language model (CLIP). Our hybrid Random Forest model successfully bridged these dimensions, achieving moderate yet promising predictive performance (Rsquare = 0.442). SHAP (Shapley Additive exPlanations) analysis revealed that psychological perceptions—specifically Safety (0.104), Fascination (0.096), and Tranquility (0.080)—outperformed traditional objective metrics like GVI (0.067) in determining overall preference, while sub-model interpretation linked these psychological responses to specific physical elements such as buildings, sky openness, low vegetation, and water bodies. The findings suggest that urban green space design should move beyond maximizing greenery quantity and instead prioritize spatial compositions that induce psychological security, visual interest, and restoration. The proposed framework offers a scalable and interpretable tool for human-centered landscape assessment, while acknowledging limitations related to sample size, cultural generalizability, pretrained model bias, and reliance on static two-dimensional imagery. Full article

Urban heat stress is a growing challenge in hot semi-arid cities, where neighbourhood urban design influences microclimate and outdoor comfort. This study evaluates the effect of neighbourhood spatial layout in Erbil city, using ENVI-met simulations. Five neighbourhoods with varying layouts were modelled under standardized conditions, including uniform building height, surface characteristics, and meteorological forcing. Hourly outputs of air temperature, relative humidity, wind speed, surface temperature, mean radiant temperature, universal thermal climate index, and sky view factor were analyzed after excluding the spin-up period. Results indicate that, while all neighbourhoods exhibited similar diurnal timing of thermal extremes, a key distinctive finding is the identification of a neighbourhood that behaves differently across seasons. The Pavilion neighbourhood remained cooler during summer conditions, while maintaining warmer thermal conditions during winter. This dual seasonal behaviour contrasts with the other neighbourhoods, which generally exhibit a trade-off between reduced summer heat stress and winter cooling. The Pavilion neighbourhood is distinguished by the presence of integrated water lagoons, suggesting that the blue infrastructure, in combination with spatial openness and greenery, can moderate thermal extremes. Overall, the study highlights the importance of neighbourhood-scale spatial design in mitigating urban heat and provides evidence to support the development of sustainable neighbourhoods. Full article

This study developed a comprehensive framework integrating ecosystem services (ESs), ecological adaptability, and ornamental value to guide tree species selection in historic cities constrained by soil salinization and subsurface heritage conservation. Taking Kaifeng, Henan Province, as a case study, we employed field surveys, i-Tree Eco, the Analytic Hierarchy Process, and K-means clustering to evaluate trees across protective, park, attached, and square green spaces. Results showed that carbon-related services dominated Kaifeng’s urban ES profile, with carbon storage (CS) and sequestration (CSE) value densities of 9.09 ¥·m⁻² and 0.84 ¥·m⁻²·y⁻¹, respectively. Air pollutant removal (AR) (0.21 ¥·m⁻²·y⁻¹) and P (0.009 ¥·m⁻²·y⁻¹) values remained comparatively low. Camphora officinarum Nees ex Wall delivered the highest annual ES value per tree (33.24 ¥·y⁻¹). Plaza greenery outperformed other space types in overall service provision, and deciduous broadleaf species generated greater ES value than evergreen conifers. Cluster analysis identified four functional groups: stress-tolerant pioneers, balanced adapters, high-efficiency carbon sinks, and ornamental specialists—each suited to specific green space contexts. This integrated framework offers a transferable approach for evidence-based tree selection in saline historic cities, supporting nature-based solutions in urban green space (UGS) planning. Full article

Urban nature and nature-based solutions are increasingly promoted to enhance public space experience and urban climate resilience. In Public and semi-public indoor settings, biophilic design is considered beneficial for stress reduction and mental health restoration through the introduction of natural elements such as plants. However, research focusing on the specific visual features of plants and the underlying mechanisms remains limited. Based on 200 indoor greenery images and their multi-dimensional feature vectors, and combined with questionnaire data from 253 valid participants, this study developed a quantitative framework of plant visual features and adopted a two-level analytical approach. At the image level, linear mixed-effects models (LMMs) were used to identify how plant features influenced immediate responses. At the group level, partial least squares structural equation modelling (PLS-SEM) was employed to examine how cumulative restorative experience translated into affective states, perceived restorativeness, and behavioural intention. The results showed that Green View Index (GVI) and species richness were the most stable positive features, while plant health status, certain planting modes, and spatial layer-related features also showed significant effects. Restorative experience influenced behavioural intention mainly through positive affect and perceived restorativeness. These findings provide evidence for biophilic design, offering quantitative support for incorporating indoor public space into broader urban nature and public space framework. Full article

Children’s everyday routes to school are increasingly recognised as important environments shaping physical and mental well-being. Yet, their emotional dimension remains insufficiently integrated into health-oriented urban design research, particularly in cities without formalised School Street policies. This study examines how children in Belgrade perceive and emotionally experience their everyday school routes and how such evidence can inform context-sensitive urban design. A mixed-method, child-centred participatory approach was applied with primary school pupils, combining participatory evaluation boards, cognitive route mapping, photo documentation, and facilitated classroom discussion. The material was analysed through qualitative coding, triangulation, and a health-oriented reinterpretation of the SCORELINE framework (h_SCORELINE). The findings reveal recurring stress nodes associated with traffic-dominated streets, complex crossings, obstructed sidewalks, and poorly legible route segments, which children linked to fear, discomfort, and insecurity. By contrast, greenery, recognisable landmarks, visually calm environments, and wider pedestrian spaces emerged as joy nodes associated with comfort, enjoyment, and emotional ease. These patterns suggest that children’s emotional-spatial evidence can enrich the assessment of school-route environments beyond conventional traffic indicators alone. By linking children’s lived experiences with health-oriented urban design, the study provides evidence-based support for the gradual introduction of School Streets in Belgrade. It offers a transferable framework for integrating child-centred experiential knowledge into healthier street design. Full article

In the context of urban renewal, the spatial interface of historic commercial districts functions as both a carrier of historical character and a key setting for commercial activity, public life, and local cultural expression. To address the limitations of conventional studies that rely heavily on field observation and qualitative description, this study takes Xiaohe Zhijie in Hangzhou as a case and develops a multi-level street-view recognition framework for the quantitative analysis of spatial interface characteristics. Based on street-view image collection and standardized preprocessing, a sample database was established at the sampling-point scale. Semantic segmentation, automated commercial object detection, and manual interpretation were combined to identify interface elements, including buildings, sky, greenery, pavement, vehicles, pedestrians, and commercial objects, while commercial content was assessed in terms of locality and homogenization. The results show that Xiaohe Zhijie exhibits a building-dominated and relatively enclosed interface pattern, with greenery and pavement forming the basic environmental ground, weak vehicle interference, and localized enhancement of vitality through commercial objects and pedestrian activities. Significant differences were found among street segments in openness, commercial coverage, and local expression. Three interface types were identified: commercial–cultural composite, local life-oriented, and waterfront landscape–cultural composite. The main challenge lies not in commercialization itself, but in stronger visual locality than content locality and increasing homogenization, resulting in a pattern of “localized form but homogenized content.” 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

Vertical greenery systems (VGS), including vertical gardens (VG) and green façades (GF), are increasingly promoted as nature-based solutions for sustainable urban development. Despite their environmental benefits, economic evaluation remains fragmented, particularly within a life-cycle cost (LCC) perspective. This study conducts a systematic literature review to examine the structural configuration of cost-related research on VGS within an LCC framework. Following the PRISMA protocol, 136 peer-reviewed articles published between 2021 and 2025 were identified through a structured search of the ScienceDirect database and retained as the analytical dataset. Bibliometric mapping, thematic classification, and co-occurrence analysis were applied to assess publication patterns, the distribution of cost components, and reporting structures. Five principal cost categories were identified: Installation and Operation, Maintenance, Consumables, Materials and Manufacturing, and Design. The results reveal a pronounced concentration on installation and maintenance costs, while design-phase economics and comprehensive LCC integration remain marginal. Most studies address only one or two cost categories, indicating structural fragmentation. In addition, heterogeneous reporting units and inconsistent contextual descriptors constrain cross-study comparability and cumulative synthesis. Collectively, the findings demonstrate that although cost research on VGS is expanding, it has not yet achieved methodological maturity within a standardized LCC framework. Advancing harmonized cost-reporting protocols and integrated life-cycle modeling is therefore essential to support robust economic evaluation and informed implementation of VGS in sustainable built environments. Full article