Search Results (835)

Promoting cycling is an essential component of sustainable urban transportation, particularly in developing countries where bicycle use remains limited. This study proposes a two-step machine-learning framework to identify the predictors associated with bicycle use and cycling popularity in Tehran, Iran. A questionnaire survey was conducted among 1027 respondents, of whom 971 valid responses were retained for analysis. In the first step, the entire sample, including cyclists and non-cyclists, was analyzed using Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN) models to predict bicycle use. In the second step, the analysis focused exclusively on existing cyclists. A Cycling Popularity Index (CPI) was developed and classified into three levels, and ten machine-learning algorithms were evaluated. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was incorporated into model development. The results showed that Random Forest achieved the highest predictive performance in the first step, with bicycle-sharing availability, access to private cars, traffic congestion, occupation, proximity to public transportation, and social norms identified as the strongest predictors of bicycle use. In the second step, KNN-SMOTE achieved the best overall predictive performance, while Permutation Feature Importance identified occupation, age, social norms, perceived cycling safety, and physical condition as the most influential predictors of cycling popularity. The proposed framework demonstrates the value of combining multiple machine-learning algorithms with class-balancing techniques for analyzing imbalanced transportation datasets and provides a transferable methodology for similar studies in developing cities. Full article

Urban agglomerations are increasingly exposed to shocks that extend across administrative boundaries through infrastructure systems, industrial chains, population mobility, and shared ecological spaces. Existing urban resilience research has predominantly assessed city-level capacity, while comparatively less attention has been paid to the relational structures associated with differences in resilience capacity and geographic proximity. This study examines the model-implied spatial correlation network of urban resilience across 41 cities in the Yangtze River Delta from 2013 to 2022. A multidimensional resilience index covering economic, infrastructure, social, and ecological dimensions was constructed using the entropy weight method and directed intercity interaction potentials were estimated using a modified gravity model and analyzed through social network analysis. The results show that overall resilience improved during the study period, although substantial cross-city disparities persisted. Under the baseline row-specific mean threshold, network density remained broadly stable, fluctuating between 0.2476 and 0.2506 and decreasing slightly from 0.2506 in 2013 to 0.2482 in 2022. The model-implied network remained fully reachable but relatively sparse, with persistent positional differentiation. Nanjing and Hangzhou consistently occupied leading total-degree positions, while Hefei, Nanjing, Hangzhou, Huangshan, and Chuzhou repeatedly exhibited relatively high betweenness. The block-model structure was also comparatively stable, with only three cities changing block membership between 2013 and 2022. Robustness analyses further showed that broad positional differentiation was more stable than exact density levels, outward-oriented rankings, and brokerage positions. Overall, improvements in city-level resilience did not translate into substantial densification or reorganization of the regional network, highlighting the need to distinguish internal resilience capacity from model-implied network position when designing differentiated regional coordination strategies. Full article

The Old City of Sana’a, a UNESCO World Heritage Site, remains morphologically unclassified at the urban block scale, with understanding still grounded in descriptive narrative rather than quantitative data—leaving conservation decisions without a measurable, reproducible spatial evidence base. This study introduces a numerical taxonomy of 115 historic urban blocks built from four standardized morphometric indicators—area, compactness, elongation, and rectangularity—together with axially encoded orientation, reduced through Principal Component Analysis (74.7% variance, three components) and partitioned by K-means into five morphologically distinct block types ($n=36,29,19,16,15$). Kruskal–Wallis tests confirmed significant differentiation across all types for every rankable indicator (all $p<0.001$; Dunn’s post-hoc: 28 of 50 pairwise contrasts significant). Qibla deviation—a culturally specific measure of angular proximity to Mecca, deliberately withheld from clustering—emerged as the strongest discriminator between types (${\eta }_H^2=0.714$), showing that shape and orientation alone recover a coherent pattern in which one type’s mean orientation axis falls within $4.5°$ of the Qibla axis. However, this statistical discriminator reflects the distinctiveness of a single type rather than a universal cultural organizing principle across the fabric. Types are distributed across all three historic zones rather than clustering spatially, and shape regularity shows no association with distance from the Great Mosque. Building on these signatures, a percentile-based screening instrument offers a reproducible, block-level morphometric baseline to help prioritize this UNESCO-listed site’s conservation under active conflict-related threat. Full article

The 15-minute city (15MC) promotes compact and accessible urban environments where residents can meet their daily needs through active mobility. Research on the 15MC has predominantly used objective assessments, with less attention to residents’ perceptions of the urban environment. Drawing on a questionnaire survey in Bologna and Porto (N = 1438), this study examines how pedestrians prioritize and evaluate walkability determinants and attributes, explores their relationship with walking behavior, and interprets selected attributes through the conceptual framework of the 15MC. Data were analyzed using descriptive statistics, chi-square tests, Mann–Whitney U tests, and Spearman’s rank correlations. The results reveal broadly similar perceptions across both cities, with pedestrian infrastructure and proximity to community facilities receiving the highest evaluations. Through the 15MC lens, these priorities are mainly associated with proximity and connectivity. Respondents from Bologna reported more frequent walking, whereas those from Porto assigned greater importance to urban ambiance and access to other transport modes. Perceived walkability was only weakly associated with walking behavior. The findings provide comparative evidence on perceptions of walkability attributes associated with selected 15MC principles in two European cities, revealing broadly similar priorities alongside differences in the importance assigned to specific attributes. Full article

Chinese native-place association buildings are important public buildings and built heritage of overseas Chinese communities, organized around migrant subgroups. Taking Melaka, Penang, and Singapore as cases, this article constructs a diachronic H-GIS database through field investigations and documentary research, and applies kernel density estimation (KDE), the mean nearest neighbor index (MNI), and the intergroup proximity ratio (R) to examine the urban distribution of these buildings and intergroup spatial relationships. In all three cities, association buildings were long anchored in port-commercial spaces and historic districts yet followed different trajectories: single-core continuity with local expansion in Melaka, north–south dual-core continuity in Penang, and postwar relocation from Chinatown to Geylang in Singapore. In the nineteenth century, different dialect-based migrant subgroups exhibited varying degrees of spatial segregation. From the twentieth century onward, association locations no longer strictly followed early dialect-based districts, and cross-subgroup juxtaposition within the same urban areas increased. Comparison across the three cities identifies three main factors shaping these layouts: port-commercial nodes, changing dialect-group boundaries, and urban expansion and renewal. The findings indicate that the heritage value of Chinese native-place associations lies not only in individual buildings, but also in their role as an urban heritage system recording interactions among urban development, identity, and community organization over time in overseas Chinese society. Full article

Cities increasingly invest in social infrastructure—parks, plazas, libraries, and other shared environments—to foster connection and wellbeing. Yet proximity does not reliably translate into meaningful social interaction, thereby revealing a persistent gap in understanding how connection emerges in urban contexts. This paper advances a relational model of urban social wellbeing that shifts analytical focus from spatial provision to interactional process. Drawing on an integrative conceptual synthesis of urban studies, micro-sociology, and social psychology, the model specifies how environmental conditions shape patterns of engagement over time. Urban social life unfolds as a staged sequence of interactional dynamics that progress from co-presence and recognition through civil inattention, triangulation, acknowledgment, interaction, and repetition. Across these stages, perceived social risk operates as a probabilistic filter that shapes transition likelihoods and explains why interaction often stalls. The paper further introduces social fitness as a contextual and relational capacity that develops through repeated interaction. By distinguishing between relational capacity and relational outcomes, the model explains how social wellbeing emerges through relational layering, as individuals accumulate a portfolio of strong, weak, and invisible ties that support belonging and integration. Conceptualizing urban social life as a dynamic system, the model offers a framework for empirical investigation and positions urban design as the shaping of interactional conditions. Full article

Urban coastal cities face compounded flood hazards driven by sea-level rise, intense precipitation, and dense impervious surfaces. This study develops and demonstrates a cloud-native Python 3.12 GIS framework for flood susceptibility screening and critical facility exposure analysis in Miami, Florida, one of the most flood-exposed coastal cities in the United States. Defined here as a geospatial workflow that retrieves data dynamically from cloud-hosted APIs and executes entirely within a hosted computing environment, the framework integrates three open-source spatial indicators: terrain elevation from the USGS 3D Elevation Programme via py3dep; Euclidean distance to water bodies from OpenStreetMap via OSMnx; and building footprint density as an impervious surface proxy, also from OpenStreetMap. Indicators were standardised and combined using literature-informed MCDA weights (water proximity: 0.40; elevation: 0.35; building density: 0.25) into a continuous flood susceptibility index, classified at the 33rd- and 66th-percentile thresholds. In this proof-of-concept application, high-susceptibility zones cover 48.66 km² (34.0%) of the city, concentrated along coastal waterfronts and inland canal corridors. Overlaying critical facility locations on the classified surface indicates that 9 of 16 hospitals (56.2%), 61 of 244 schools (25.0%), and 5 of 17 fire stations (29.4%) fall within high-susceptibility zones; because this overlay uses centroid-based facility points that have not been cross-checked against official municipal or state facility registries, these counts should be read as indicative rather than definitive. Exact binomial testing shows that the school exposure deficit is statistically significant (p = 0.00), while elevated hospital exposure, although substantively notable, does not reach significance at the current sample size (p = 0.07). The susceptibility surface itself has not been quantitatively validated against external benchmarks such as FEMA flood maps or historical inundation records, the MCDA weights have not been sensitivity-tested, and spatial autocorrelation in the index has not been assessed; concrete protocols for each of these steps are specified as subsequent calibration work rather than as prerequisites for the architecture demonstrated here. The contribution of this paper is the reproducible, cloud-native workflow architecture and its proof-of-concept application, not a validated operational assessment tool; we present it explicitly as a methodological protocol and workflow demonstration, not as an evaluation of flood risk. The framework is fully reproducible, low-cost, and transferable to other US coastal cities. Full article

Transport decarbonization through electric mobility depends not only on how many charging stations are deployed but where, and whether expansion balances accessibility, grid readiness, land-use protection and regional equity. Türkiye, targeting net-zero by 2053 with electric car sales exceeding 10% of the market in 2024, shows a highly uneven charging network: provincial provision ranges from 9.0 to 155.6 points per 100,000 inhabitants, with the least-served half of the population holding only 22.3% of installed capacity (Gini = 0.311). This study develops a GIS-based multi-criteria framework treating charging expansion as a sustainability-constrained planning problem. Six criteria, namely population, GDP, transformer and transmission-line proximity, road-network proximity, and city-centre proximity, were harmonized to a 100-m grid via fuzzy membership functions, with an exclusion mask protecting sensitive land uses. Three weighting scenarios were compared: equal weights (EVCSI-A), Random Forest-derived weights (EVCSI-B), and expert AHP weights (EVCSI-C). Road accessibility (41.12%) and economic capacity (29.84%) dominated existing placement, explaining ~71% of feature importance, stable across algorithms and bootstrap replicates. National results reveal an efficiency–equity trade-off: EVCSI-B concentrates suitability in metropolitan corridors, EVCSI-A preserves broader coverage, and EVCSI-C reinforces metropolitan bias. Central and Eastern Anatolia remain underserved. We recommend sustainability-constrained screening followed by grid-capacity verification, positioning EVCSI as a transferable equity-monitoring tool supporting SDG 7, 9, 11 and 13. Full article

Autonomous vehicles (AVs) will operate alongside human-driven vehicles for an extended transition period, during which aggressive human driving may become a major source of risk. This study proposes an integrated safety-control framework that combines real-world-data-driven behavior modeling with deep reinforcement learning to design longitudinal AV control strategies for mixed traffic. Aggressive, general, and defensive driving patterns are calibrated from the CitySim dataset, and dynamic aggressiveness is incorporated into an improved car-following model. A proximal policy optimization algorithm with a Kullback–Leibler penalty is then used to learn multi-objective strategies balancing safety, efficiency, comfort, and fuel economy in freeway and signalized-intersection scenarios. The results show that the behavior-aware strategies exhibit different strengths across traffic environments. On the freeway, the defensive-threshold strategy maintains a larger time headway, reduces positive acceleration, and lowers system-level fuel consumption, whereas the default, aggressive, and general strategies preserve higher traffic efficiency. At the intersection, signal control narrows the differences among strategies and limits the influence of longitudinal threshold settings on most evaluated indicators. These findings provide a quantitative basis for selecting behavior-aware control thresholds and designing robust AV strategies for mixed-autonomy traffic containing aggressive human drivers. Full article

Background: Lead (Pb) exposure remains a significant public health concern, particularly among women of childbearing age, because of its adverse effects on maternal–child health. Although lead-glazed ceramics (LGC) for cooking or storing food are a well-recognized source of Pb exposure in Mexico, other environmental and household sources remain insufficiently characterized. Objective: To identify environmental and household factors associated with elevated blood lead levels (BLLs) among women of childbearing age participating in a community-based screening in Mexico City. Methods: We conducted a cross-sectional analysis of 158 women aged 18–40 years. Capillary BLLs were measured using the LeadCare^® II system. Participants completed a structured questionnaire assessing potential Pb sources of exposure. Elevated BLL was defined as ≥3.5 µg/dL. Associations between exposure sources and elevated BLL were evaluated using multivariable logistic regression adjusted for sociodemographic and lifestyle factors. Shapley decomposition was used to estimate the relative contribution of each exposure source to the model. Results: The prevalence of elevated BLLs was 31%. Women reporting both past and current use of LGC had higher odds of elevated BLLs than women who had never used LGC (adjusted OR = 9.43; 95% CI: 1.85–48.15). Living in or regularly visiting a recently remodeled home (adjusted OR = 3.21; 95% CI: 1.45–7.11) and living near a highway (adjusted OR = 2.41; 95% CI: 1.07–5.48) were also independently associated with elevated BLLs. LGC use was the largest contributor to the model performance (47.46%), followed by home remodeling (31.78%) and proximity to highways (20.76%). Conclusions: Our findings support LGC as an important source of Pb exposure while identify home remodeling and residential proximity to highways as additional sources associated with elevated BLLs. Together, these findings broaden the understanding of Pb exposure pathways among women of childbearing age and support the need for prevention and screening strategies. Full article

Proximity-based planning frameworks such as the 15 min city and community life circle (CLC) are widely promoted to improve age-friendly access to essential resources, based on the assumption that enlarging spatial scale improves access. This assumption remains largely untested in high-density aging cities, where neighborhood-level deprivation may persist even as aggregate access improves. Using 3737 residential communities in central Tianjin, China, this study jointly evaluates food and physical activity environments across 5, 10, and 15 min walking thresholds. We apply a three-dimensional demand–matching–spatial association framework that combines health-weighted accessibility, location quotient matching, and bivariate spatial autocorrelation. Food access shows a continuous core–periphery gradient, whereas physical activity access is fragmented and facility-dependent. Supply–demand matching shows divergent scale responses across resource domains. Aggregate accessibility increased as the CLC scale expanded. However, 45.88% of communities classified as LL at the 10 min scale remained LL at 15 min, substantially exceeding the overall LL proportion of 18.70% at the 15 min scale. Only 5.42% of communities classified as HL or LH transitioned to HH. This divergence between aggregate accessibility improvement and persistent local disadvantage is defined as ineffective expansion. Eight diagnostic types reveal a clear divide between deprived peripheries and advantage-maintenance conditions in the urban core. These findings suggest that age-friendly CLC planning should move beyond uniform service-area expansion toward type-specific, place-based interventions. Full article

The COVID-19 pandemic triggered an unprecedented collective reflection on everyday urban life, reshaping how citizens perceived proximity, mobility patterns, and the sustainability of everyday transport systems. This article examines whether these pandemic-induced reflections resonated with the core principles of the 15-Minute City, understood not as a policy blueprint but as an emergent social imaginary. Drawing on a large-scale comparative survey conducted during the strictest lockdown phase in April–May 2020 (n = 9575), the study analyses survey respondents’ desires and expectations regarding post-pandemic urban change across nine Ibero-American countries: Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru, Portugal, and Spain. Using one-way ANOVA and Tukey post hoc tests, the results reveal a strong and widely shared normative orientation toward greener, more walkable, and more localized urban environments, all of which are key dimensions of sustainable urban mobility transitions, including reduced car dependence and a greater reliance on active transport modes such as walking and cycling. However, these aspirations are consistently accompanied by significantly lower expectations of implementation, resulting in a pronounced desire–expectation gap across all countries. This gap displays clear geographical variation and appears closely associated with perceived governance capacity and institutional trust, with European countries showing greater alignment between aspiration and expectation than their Latin American counterparts. The findings suggest that, even in the absence of explicit policy discourse, respondents expressed aspirational urban imaginaries displaying affinities with principles commonly associated with the 15-Minute City framework. By empirically capturing these bottom-up imaginaries, the study contributes to debates on sustainable urban transport and mobility transitions by highlighting the social foundations and governance constraints of proximity-based planning across diverse institutional contexts. Full article

Climate change adaptation in cities increasingly requires not only technical and spatial solutions, but also a better understanding of residents’ beliefs and expectations towards green infrastructure. This study aimed to identify the relationship between climate change knowledge and preferences for urban green infrastructure among Warsaw residents. The research was based on a CAWI survey conducted at the end of 2024 among 780 adult residents of Warsaw. Respondent segmentation was performed using hierarchical cluster analysis and k-means clustering, while differences between groups were assessed using the Kruskal–Wallis and chi-square tests. Four resident segments were identified: Climate Aware, Natural-Factor Oriented, Sceptics, and Uncertain. These groups were found to differ significantly in their climate change knowledge and beliefs, socio-demographic characteristics, motivations for using green areas, and preferences for specific green infrastructure elements. Climate-aware residents attached particular importance to multifunctional green and blue infrastructure, including large parks, trees, water elements, and proximity to natural areas. More sceptical residents tended to perceive green areas mainly through their recreational and sport-related functions. The findings indicate that climate-adaptive green infrastructure should be planned in a socially differentiated way, combining environmental, recreational, and tourism-related functions to strengthen both urban resilience and the attractiveness of Warsaw. Full article

Rapid urbanization along transportation corridors is a key driver of land transformation and landscape homogenization in developing mega-cities. This study analyzes land use and land cover (LULC) change within a 5 km buffer, from Gulberg to T-Chowk, along the Islamabad Expressway, Pakistan, from 2010 to 2024, using multi-temporal Landsat imagery (2010, 2015, 2020, 2024) and landscape metrics. Built-up area increased by 190.8% (51.02 to 148.34 km²) between 2010 and 2024. The expansion is accompanied by sharp declines in vegetation (−36.0%; 89.17 to 57.06 km²), barren land (−93.8%; 63.88 to 3.94 km²), and water bodies (−64.2%; 8.20 to 2.93 km²). All class-area estimates were derived from the R landscapemetricspipeline and independently verified against visual inspection of the classified rasters, confirming correct class labelling throughout. Landscape structure shifted towards homogenization, with Shannon’s Diversity Index decreasing from 1.19 to 0.74, Patch Density from 74.39 to 21.08 patches per 100 ha, and Edge Density from 219.65 to 99.78 m/ha. LULC maps achieved an accuracy greater than 96% ($\kappa >0.96$) for each classification year, and metric estimates showed cross-platform agreement between R and FRAGSTATS within ±5%. A distance-zone analysis across four successive 1.25 km bands from the Expressway showed that this expansion was pervasive rather than confined to the roadside, with the urban share of classified land rising by 43.6–47.7 percentage points in every band. A complementary 300 m × 300 m fishnet-grid multivariable logistic regression ($n=2162$ cells classified as non-urban in 2010) identified proximity to existing 2010 built-up land and location within a formal housing scheme as the strongest independent correlates of conversion to urban land (AOR = 1.88 for housing-scheme proximity; 95% CI: 1.38–2.56), with acceptable model discrimination (AUC = 0.739). These findings indicate rapid corridor-scale consolidation associated with infrastructure-led growth, reducing landscape heterogeneity and potentially weakening ecological resilience. Unlike previous city-scale studies in the Islamabad–Rawalpindi region, this study adopts a transportation-corridor perspective, combining descriptive landscape ecology with spatially explicit statistical modelling to quantify both the pattern and the spatial drivers of infrastructure-led land transformation. The study underscores the necessity for integrated, corridor-scale land-use governance—including transit-oriented development and landscape-metric-based ecological zoning—to balance urban expansion with ecosystem sustainability. Full article

Proximity-based urban models, including the widely discussed 15 min city, aim to bring everyday destinations within a short walk, cycle, or shared-mobility trip, with promising benefits for well-being, public health, local economies, and low-carbon mobility. While the appeal of proximity is widely shared, far less is known about how to deliver and govern such neighbourhoods so that these benefits are realised, durable, and embraced by residents across the full range of their mobility needs. Implementation, public acceptance, and governance therefore remain comparatively under-examined. This article contributes an enabling governance approach for proximity-based, accessible neighbourhoods, centred on co-creation and on a rich, attractive menu of mobility options. Through a cross-disciplinary synthesis organised by the CalmMobility paradigm, a governance-posture lens that emphasises co-creation, sequencing, and readiness, it integrates evidence on proximity, accessibility, active travel, shared mobility, well-being, and low-carbon outcomes. The article argues that proximity and shared mobility widen the range of convenient and attractive options for everyday trips, and that this supports health, quality of life, and lower emissions. It also argues that these benefits are more likely to last under calm, co-created governance, which builds good options first and respects the freedom of residents to choose among all modes, including the car. To put the paradigm to work, the study introduces the Governance Compass and applies it to Paris, Barcelona, and Melbourne. The Compass was applied through a qualitative document analysis carried out by one analyst. It is offered as an exploratory tool that aims to make the reasoning open to inspection, not as a validated measuring instrument. Results are reported as ordinal bands, from Absent to Exemplary, and a 0 to 100 index is kept only as an illustration. The three cases show different patterns. In Paris and in the early Barcelona work, the documents set ambitious proximity goals but say much less about how change is paced, how residents shape it, and how choice is preserved, and these dimensions fall in the lower bands. In Melbourne, whose programme is still a pilot, the pattern is the reverse. The process dimensions are stronger there, but proximity itself is less developed. These bands describe the documents examined, not a fixed ranking of the three cities. Positioned as a constructive complement to the proximity-city agenda rather than a critique of it, the article closes with a cross-disciplinary research agenda spanning planning, transport, public health, and policy. Full article