Search Results (1,141)

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

Rough set methodology has gained broad acceptance as a potent mathematical apparatus for feature selection within data mining and machine learning. Yet, classical rough sets hinge on equivalence relations to partition the universe, thereby demanding strict reflexivity, symmetry, and transitivity conditions that are arduous to satisfy in realistic settings. Although fuzzy rough sets have been explored to mitigate this rigidity, the entropy-based uncertainty measures employed in fuzzy approximation spaces remain acutely sensitive to data quality and noise corruption, potentially inducing severe bias in feature evaluation. Moreover, the literature currently lacks noise-tolerant uncertainty measures capable of accommodating a controlled fraction of classification errors while safeguarding the discriminative strength of feature subsets. Inspired by these gaps, this study develops a feature selection framework grounded in variable precision fuzzy entropy within the fuzzy rough set context. To this end, fuzzy decision is adopted to portray the membership degree of samples relative to decision classes, thereby enabling more precise detection and elimination of redundant attributes during approximation. An uncertainty quantifier termed fuzzy relational entropy is then introduced to appraise the distinguishing power of fuzzy similarity relations generated by attribute subsets. Leveraging fuzzy decision, a portfolio of uncertainty measure variants, specifically the variable precision joint discriminant index, the variable precision conditional discriminant index, and the variable precision mutual discriminant index, is developed to counteract noisy data effects. These variable precision discriminant indexes sanction a regulated error proportion and afford a measure of noise resistance. Finally, knowledge reduction for fuzzy decision systems is attacked from the angle of discriminative capability preservation, and a heuristic feature selection algorithm is crafted around the variable precision conditional discriminant index. Evaluation on twelve public UCI datasets reveals that the proposed algorithm effectively prunes redundant features and delivers competitive results against three representative alternatives: classical rough set, neighbourhood-based discriminant index, and fuzzy rough set feature selection. Additionally, it sustains stable classification performance across an extensive sweep of the variable precision parameter. Full article

Dense tropical cities face increasing outdoor heat stress and require reliable microclimate modelling tools to support climate-responsive urban planning. However, the performance of these models remains insufficiently documented under tropical conditions. The objective of this study is to experimentally validate the performance of ENVI-met for outdoor thermal comfort assessment in a dense tropical neighbourhood on Reunion Island. Validation was performed using a network of 11 low-cost weather stations distributed across the study area, providing observations of air temperature, relative humidity, wind speed and globe temperature, from which mean radiant temperature (MRT) and the Universal Thermal Climate Index (UTCI) were derived. Model performance was evaluated through multipoint validation, error-propagation analysis and sensitivity experiments. Results show that ENVI-met reproduces air temperature and relative humidity with good accuracy (RMSE of 1.2 °C and 5%), while larger uncertainties are observed for wind speed (up to 4 m s⁻¹) and MRT (up to 8 °C), with strong spatial variability. Error-propagation analysis indicates that 62% of the UTCI error variance is explained by combined microclimate simulation errors, with radiative conditions emerging as the dominant contributor. Sensitivity analyses identify boundary wind forcing as the main source of modelling uncertainty. Overall, the proposed validation framework provides practical guidance for improving ENVI-met applications in tropical urban environments and supports more robust climate-responsive urban design. Full article

Traditional urban morphological analyses are structurally limited in terms of both systemic diversity and empirical scale due to reliance on manual methods. In contrast, decoding the complex fabric of rapidly growing cities necessitates data-driven, scalable approaches. To address this gap, this study proposes a multi-scale pipeline that classifies urban form systematically and reproducibly from open spatial data, and applies it comparatively to three Anatolian cities of contrasting typo-morphological character: Elazığ, Erzincan and Mardin. From street networks and building geometries, an integrated morphometric matrix was assembled by computing network topology and orientation metrics, space syntax configurational accessibility, morphological tessellation, coverage area ratio, building form–volume indicators, neighbourhood and adjacency measures, and Local indicators of spatial association (LISA) spatial autocorrelation. After transformation and standardisation, urban typologies were derived through Principal Component Analysis and grouped with spatially weighted k-means (Geo-KMeans). Three findings stand out. First, the cities trace a distinct morphological spectrum that runs from Mardin’s organic historical fabric to Erzincan’s relatively planned grid structure, with the radial polarised Elazığ occupying an intermediate, transitional position between the two. Second, accessibility and built density prove only weakly related (r = 0.05–0.25). Third, six, five and four morphological typologies emerged, triangulated against LISA hot spot clusters and space syntax maps. Overall, this reproducible framework offers planners a systematic, data-driven basis for exploratory morphological assessment rather than a definitive, universal typology. Full article

Regional landslide susceptibility mapping commonly relies on static conditioning factors, including terrain, geology, hydrology, land cover and human activity. These factors describe long-term instability settings but cannot directly represent recent or ongoing ground deformation. Interferometric Synthetic Aperture Radar (InSAR) can provide spatially distributed deformation information, yet mountainous InSAR evidence is affected by uneven observation availability, vegetation decorrelation, terrain-induced geometric distortion and confounding between observation support and static environmental conditions. These issues make it difficult to determine whether radar-derived variables represent deformation signals or mainly indicate where observations are reliable. This study develops a scale-sensitive and confounding-audited Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) evidence representation framework for regional landslide susceptibility mapping. In Pingwu County, China, a 1607-record landslide inventory was converted into 1579 unique 30 m landslide cells, with 1393 for training and 186 for inventory-concentration validation. Fourteen static factors formed the baseline model. Deformation evidence from 98 Sentinel-1A descending acquisitions was represented using point-based line-of-sight (LOS) variables, neighbourhood component descriptors, a compressed deformation-intensity and observation-availability index, and a separated deformation intensity (DI) plus observation availability (RI) representation. Results show that the static factors already provided a strong first-order baseline. Adding SBAS-InSAR evidence did not produce uniform paired improvements across models, metrics or neighbourhood scales. In 10 km spatial-block cross-validation, random forest models using static factors, 300 m component descriptors and 300 m DI + RI features achieved similar mean area under the receiver operating characteristic curve values of 0.948, 0.949 and 0.950, with mean Matthews correlation coefficient values of 0.791, 0.795 and 0.795. Broader neighbourhood representations may expand the attainable performance boundary, but only as diagnostic evidence. SBAS-InSAR-derived information should therefore not be treated as a simple additional conditioning factor; its value depends on jointly interpreting deformation intensity, observation availability and their confounding with static context. Full article

Complete neighbourhoods, places where residents can meet their daily needs on foot, have become a central component of healthy and sustainable urban planning. Yet most assessment frameworks are calibrated for dense metropolitan environments, leaving rural and peri-urban municipalities without operational tools suited to their territorial needs. This article presents MilieuxVie, an open-source, browser-based interactive mapping application developed for the Laurentides health region of Québec (76 municipalities, 11 land-based unorganised territories, 2 indigenous territories and 4 aquatic administrative units; 93 territorial units in total; ~680,000 inhabitants). The tool evaluates the spatial accessibility of 12 service categories drawn from the Vivre en Ville (2026) complete-neighbourhood framework and OpenStreetMap data, using 2026 residential parcels from the provincial property assessment roll as origin points and weighting results by number of dwelling units. Three adaptive radius tiers (dense, intermediate, rural), based on residential dwelling-unit density (dwellings per km² of residentially designated urban land), scale the distance standards to settlement density. Because thresholds are scaled to settlement density, scores express context-relative service proximity rather than a uniform pedestrian standard and should not be read as directly comparable absolute accessibility across rural, peri-urban, and urban settings. A dedicated urban perimeter mode further disaggregates analysis to sub-municipal built-up zones, aligning the tool with Québec’s provincial Government land-use planning guidelines (GLPG). Gap analysis outputs identify which service types fall below the 70% coverage target, helping elected officials and planners identify where to focus further analysis. Results illustrate the scope of accessibility deficits across the region and highlight the analytical limits of uniform distance thresholds when applied beyond metropolitan contexts. Scores differ significantly across different settings (Kruskal–Wallis p = 0.006); the adaptive radius tiers narrow but do not close the structural gap, with rural municipalities scoring significantly lower than dense ones. The tool is freely available and requires no software installation, making it directly deployable by local planning offices. Full article

Piezoelectric actuators are widely used in precision manufacturing, high-end equipment and aerospace fields due to their high precision, fast response and flexible structure. However, continuous smooth displacement output over a large travel range with high-torque requirement is still a problem that needs to be solved, which greatly limits their application scope. Therefore, this work proposes a smooth-motion walking-type piezoelectric actuator over a large travel range with high torque inspirited by the bipedal walking mechanism. The driving legs with high stiffness and large displacement of the actuator are divided into two groups; by imitating the bipedal walking gait of humans, the driving trajectories of the two sets of driving legs are alternately integrated to adjust the balance between the driving torque and the resistance torque, ensuring that the resultant force torque acting on the rotor is zero, thereby achieving smooth motion in a large travel range with high torque. The multi-objective optimization algorithm of the neighbourhood cultivation genetic algorithm (NCGA) is adopted to optimize the structure design of the driving legs by considering the stiffness and displacement, in order to achieve the balance of high stiffness and large displacement at the foot end of the driving leg. The linear fitting coefficients of the output displacements of the actuator all reach above 0.999, the resolution is 0.4 µrad, and the maximum output torque is better than 1.31 N·m. These performances will greatly expand the application fields of piezoelectric actuators, especially in deep space optical tracking scenarios. Full article

The novel Mehrobdan Chayon by Abdulla Qodiriy has been studied mostly as a historical, social and literary text, and its representation of motherhood and women as agents of cultural transmission has received little scholarly attention. This article suggests that Qodiriy presents motherhood not primarily as a biological relationship but as a cultural institution, in which Uzbek society is reproduced across generations in terms of literacy, religious and literary canon, comportment and marital expectation. The analysis, based on close reading of three figures, i.e., the neighbourhood girls’ teacher, Nigor oyim; the educated daughter, Ra’no; and the marital-futures-managing woman, Mohlar oyim, and an interdisciplinary cultural-studies approach, demonstrates that the maternal line functions as the novel’s mechanism of cultural continuity, transmitting both knowledge and social constraint. The article adds a Central Asian case to the study of motherhood and rethinks Qodiriy’s domestic scenes as the place where Uzbek womanhood is reproduced and reformed. Full article

Land use functions refer to the capacity of land systems to provide goods and services, either directly or indirectly. They reflect the intensity of land use and the demands of social development at different stages and serve as an important reference for future land use planning. This study establishes a land use allocation optimisation framework that integrates top-down and bottom-up approaches to enhance land use functions. At the bottom-up level, an artificial neural network (ANN) model is employed to evaluate land suitability based on neighbourhood rules and driving factors. At the top-down level, a multi-agent system (MAS) model is used to integrate trade-offs among land use functions with supply–demand relationships, thereby defining land use constraints during the allocation process. Subsequently, the two models were integrated into a cellular automata (CA) model to achieve the spatial allocation of optimised land use patterns. Xintai City, located in Shandong Province, was selected as the study area. The results indicate that, compared with the 2021 baseline, ecological functions exhibited the greatest improvement, increasing by 24.11%, whereas living and production functions decreased slightly by 4.35% and 0.87%, respectively, resulting in an overall comprehensive functional improvement of 9.32%. Regarding trade-off relationships among land use functions, the intensity of trade-offs between production and ecological functions, as well as between living and ecological functions, decreased significantly by 28.72% and 25.56%, respectively, whereas the trade-off intensity between production and living functions increased slightly by 1.68%. Regarding the supply–demand relationships of land use functions in Xintai City, the surplus of production functions decreased by 13.46%, the surplus of living functions increased by 16.67%, the deficit in ecological functions improved by 33.33%, and the comprehensive functional surplus increased by 23.53%. The proposed method demonstrates substantial effectiveness in enhancing land use functions, alleviating trade-offs among land use functions, and optimising their supply–demand relationships. Full article

The complete community paradigm, emphasising walkable, self-sufficient neighbourhoods, has gained significant global traction, yet the role of sports and physical activity spaces within such frameworks remains undertheorised, particularly in dense Chinese urban environments. This paper introduces the Chrono-Adaptive Sports Space Index (CASI), a preliminary evaluative framework whose diagnostic utility is demonstrated through three contrasting case studies. CASI integrates temporal usage dynamics, demographic composition, smart-city sensor data, and multi-generational programming flexibility to assess sports environments within China’s 15-Minute Complete Community (完整社区, Wánzhěng Shèqū) policy framework. Unlike existing frameworks that assess sports spaces through static metrics, CASI proposes that sports environments must be evaluated across four temporal dimensions: diurnal rhythms, weekly cycles, seasonal transitions, and demographic lifecycle shifts. The four sub-indices are weighted equally (25 points each) as a deliberate first-generation design choice reflecting the absence of pre-existing empirical benchmarks; this assumption requires empirical validation in future research. Through exploratory multi-case analysis of communities in Shanghai (Jing’an District), Chengdu (Tianfu New Area), and Beijing (Chaoyang District), this study provides preliminary evidence suggesting that temporally inert sports spaces may be associated with utilisation losses of 38–52% during off-peak periods and the systematic exclusion of elderly and child populations; these figures should be treated as indicative estimates pending broader empirical validation. A Chrono-Adaptive Design Protocol (CADP) is proposed as a conceptual, practice-informed protocol awaiting prospective empirical evaluation. This research is better characterised as a framework development and initial exploratory application study rather than a validation of a mature instrument. Its primary contribution is a new theoretical and diagnostic lens for complete community planning, together with an agenda for the empirical work needed to develop CASI into a broadly applicable assessment tool. The study’s limitations and a structured five-priority future research agenda are presented in a dedicated section following the Conclusions. Full article

Population ageing is reshaping the use and evaluation of everyday urban green spaces, especially in old urban districts where nearby public spaces support walking, resting, exercise, and social contact. Conventional age-friendly assessments often emphasise whether formal infrastructure is provided, but facility provision alone does not ensure experiential fit with older adults’ functional capacities, daily routines, and social practices. This exploratory multiple-case study examines user-initiated informal adaptations in three neighbourhood-scale green spaces in Gulou District, Nanjing, China. Facility audits, approximately 30 h of non-participant observation, semi-structured interviews with 36 older users, and 220 valid questionnaires were combined through cross-case coding and qualitative triangulation. Three adaptation types were identified: supplementary, modifying, and appropriative adaptations. These practices were interpreted as context-dependent behavioural signals potentially associated with safety and convenience, ergonomic support and material-thermal comfort, social accessibility and spatial accommodation, and social support. Adaptation patterns varied descriptively across sites and age groups in relation to facility conditions, spatial organisation, activity intensity, and user characteristics. The findings suggest that, when interpreted alongside facility audits, interviews, and site context, older adults’ everyday adaptations may help identify possible mismatches between formal provision and actual use, offering a low-cost interpretative perspective for inclusive, incremental, and socially sustainable green-space renewal. Full article

Crime prediction in urban environments is a complex and pressing challenge driven by the intricate interplay of spatiotemporal dependencies, hierarchical geographic patterns, and socio-environmental determinants. We propose a multi-scale geo-temporal crime embedding (MSG-TCE) framework, which hierarchically models these dynamics via three novel components: a hierarchical residual temporal encoder (HRTE), a periodic transformer Encoder (PTE), and a hyperbolic spatial pooler (HSP). The HRTE captures multi-scale temporal trends by combining dilated convolutions with residual connections, while the PTE explicitly encodes periodic crime patterns using self-attention conditioned on cyclical positional encodings. The HSP maps spatial crime hotspots into hyperbolic space to better represent their inherent hierarchical structure, spanning city–district–neighbourhood–street-segment scales, and aggregates neighbourhood information via graph convolutions. These components are fused through a gated cross-attention mechanism, yielding a unified embedding for crime prediction. Experiments on real-world datasets from Chicago, Los Angeles, and New York City demonstrate that MSG-TCE achieves consistent improvements over five competitive baselines across RMSE, Precision@20, and DTW metrics, with statistically significant gains at longer prediction horizons. Ablation studies confirm the contribution of each component. Spatial visualisation maps, robustness analyses, and an exploratory covariate-augmented variant further substantiate the empirical validity of the framework. This paper also discusses limitations, including data reporting biases, the need for full covariate integration, and ethical considerations, pertaining to algorithmic fairness in crime prediction. Full article

Grocery shopping remains a heavily car-dependent activity in urban areas, even for short-distance trips within residential neighbourhoods. A primary barrier to shifting toward active travel (walking or cycling) is the physical burden of carrying heavy or bulky goods. This study investigates whether a retailer-managed home delivery service could encourage consumers who currently rely on motorised modes for grocery shopping to shift towards active travel while preserving the in-store shopping experience. The analysis focuses on urban Italian consumers who currently use motorised modes for grocery shopping. Using a Stated Preference (SP) experiment and a Mixed Logit (MMNL) model (n = 88), we analyse the conditions under which such a service may encourage the adoption of active travel modes and support proximity-based shopping patterns. Given the exploratory nature of the study and the small, non-representative sample, the findings should be interpreted as preliminary evidence for urban motorised grocery shoppers rather than as representative of the Italian population. The results indicate a substantial willingness among respondents to adopt the proposed service configuration. Delivery time, service cost, and the availability of delivery time-window selection emerge as critical factors influencing consumers’ choices. Acceptance of the service is also influenced by perceptions of walking and cycling infrastructure quality, trust in the integrity of delivered groceries, preferences for local products, and concerns regarding the working conditions of delivery personnel. Additionally, the model reveals significant heterogeneity in preferences regarding delivery by drone/autonomous vehicle and a 100% reduction in greenhouse gas emissions relative to conventional motorised transport. Younger respondents exhibit a more favourable attitude towards automated delivery technologies, while differences in the valuation of environmental benefits emerge between male and female respondents. The findings suggest that retailer-managed home delivery may represent a promising mechanism for encouraging active travel among current motorised grocery shoppers, while maintaining consumers’ relationship with neighbourhood retail services. These results provide retailers and urban policymakers with valuable insights, suggesting that appropriately designed delivery services may support more sustainable and proximity-oriented shopping behaviours. Such services could potentially contribute to maintaining the accessibility and vitality of neighbourhood retail activities, particularly in ageing urban contexts. Full article

This article examines how memory, knowledge, and lived experience become embedded within material environments and continue to shape engagement with historic wooden neighbourhoods. Drawing on the WoodiSH project (Wooden Cities: Memory, Sustainability and Craft in Historic Neighbourhoods), the article develops the concept of terroir as a framework for understanding historic built environments as material ecologies of memory. The analysis combines perspectives from material culture studies, phenomenology, Tim Ingold’s concepts of meshwork and wayfaring, and theories of embodied cognition. While the WoodiSH project provides the empirical context through studies of historic wooden neighbourhoods in Trondheim, Pori, and Vilnius, the article is primarily conceptual and uses observations from heritage environments and craft education as analytical entry points. The article argues that memory is not located solely in individual minds but remains materially present through traces of repair, maintenance, adaptation, and everyday use. Observations from the WoodiSH project and educational activities in traditional building crafts suggest that such traces enable residents, craftspeople, and students to recognise how previous actions and practical knowledge remain embedded within materials and places. Historic wooden neighbourhoods are therefore understood as terroirs of memory: environments in which knowledge and experience continue to be enacted through ongoing engagement with material traces. The article contributes by extending terroir beyond its traditional association with viticulture and by demonstrating how material memory becomes accessible through embodied engagement with historic environments. It further proposes a pedagogy of material sensitivity in which learning develops through observation, participation, repair, and practical involvement with heritage environments. Full article

Walkability measurement has expanded from a small set of generic neighbourhood-level proxies into a heterogeneous field of indices, scored audits, perceived-environment scales, route-based instruments, and context-specific assessment instruments. This expansion has improved the sensitivity of walkability research, but it has also made it increasingly difficult to judge which instruments are appropriate for different users, walking purposes, and urban or environmental contexts. This review addresses this problem by comparing operational walkability instruments through an adapted walking-needs framework derived from the Expanded Hierarchy of Walking Needs (HoWN). Publications from 1990 to 2025 were identified through a structured search and screening workflow covering general walkability measurement, population-sensitive instruments, purpose-specific instruments, climate- and exposure-sensitive instruments, and urban-form-specific instruments. After eligibility assessment and consolidation, 46 walkability instruments were retained for comparative analysis. For this review, the framework is adapted from a behavioural hierarchy into an instrument-level comparative structure, with feasibility re-specified as basic environmental passability. The instruments are then compared across five tiers: feasibility, accessibility, safety, comfort, and pleasurability. The review shows that walkability measurement remains strongly concentrated in lower-order and functionally measurable dimensions, especially pedestrian infrastructure, destination access, connectivity, and traffic safety. By contrast, comfort, pleasurability, environmental exposure, personal security, and user-specific constraints are less consistently formalised and often appear only in specialised instruments. Population-, purpose-, climate-, and urban-form-sensitive instruments do not merely add indicators; they alter which walking needs become foundational in specific assessment scenarios. This review contributes a fit-for-purpose comparative logic for walkability measurement. It shows how a shared walking-needs framework can be used to diagnose coverage imbalance, identify scenario-specific threshold conditions, and guide the selection, adaptation, and transfer of instruments across different users, walking purposes, environmental exposures, and urban forms. Full article