Search Results (6,046)

In the field of urban traffic management, optimizing traffic signals at intersections is crucial for enhancing traffic flow efficiency. Despite advances in intelligent traffic signal control strategies through deep reinforcement learning (DRL), practical deployment challenges persist, such as abrupt changes in signal phases and significant hardware costs. This paper proposes a novel Traffic Characteristics-Guided Progressive optimization (TCGP) method that builds on classical fixed-time traffic signals. It is based on the classic fixed-time and quickly optimizes the green time ratio of intersection traffic lights by integrating the relationship between green light duration and traffic flow. Then, it efficiently explores the traffic signal cycle duration of a single intersection. Using a progressive optimization strategy, TCGP addresses the “curse of dimensionality” problem caused by a large number of intersections. TCGP ensures compatibility with traditional control methods and offers performance comparable to state-of-the-art DRL approaches, with competitive stability and computational efficiency. Evaluations with public datasets and real traffic data from Zhengzhou, Henan, China, confirm TCGP’s competitive performance and adaptability. This contributes fresh perspectives to the modernization of urban traffic systems. Full article

Cape Coast is a prominent tourism destination in Ghana, distinguished by its historical landmarks, coastal ecosystems, and cultural heritage. Yet the city faces mounting threats from environmental hazards such as coastal erosion, flooding, extreme heat, and lagoon degradation, which directly compromise the sustainability of its tourism sector. Guided by the Sustainable Tourism Development Theory (STDT) and the Tourism Resilience and Adaptation Theory (TRAT), this study investigates the impacts of these hazards on tourism development, the effectiveness of current disaster risk reduction (DRR) strategies, and the roles of key stakeholders in building sectoral resilience. Using a qualitative research design, data were collected through in-depth interviews with eighteen stakeholders comprising four policymakers, six community leaders, five tourism business operators, and three representatives from non-governmental organisations, alongside documentary analysis of four institutional reports. The study contributes to the literature by demonstrating that fragmented, reactive DRR strategies and weak stakeholder coordination undermine Cape Coast’s tourism resilience, and by showing how urban natural assets, a dimension largely neglected in existing tourism–DRR scholarship, are central to both hazard exposure and adaptive capacity. The findings call for integrated, ecosystem-based DRR frameworks that align governance mechanisms with sustainable tourism imperatives. Full article

Egon Steinmann’s industrial architecture represents a significant yet insufficiently researched contribution to the development of post-war industrial architecture in Croatia. This paper examines his industrial projects designed between 1947 and 1965 within the context of post-war industrialization and modernization in socialist Yugoslavia. Based on archival documents, historical photographs, field observations, and comparative analysis, the paper first identifies Steinmann’s broader industrial work and then examines six selected industrial complexes in Zagreb. The case studies are compared in terms of their urban context, spatial organization, structural systems, production logistics, daylighting strategies, and architectural expression, highlighting differences between heavy industrial facilities and food-processing plants. A comparison of historical and contemporary orthophotos is further used to evaluate the long-term spatial transformation and adaptability of these industrial sites. The findings demonstrate that Steinmann’s designs were characterized by rational planning, large-span and flexible structures, integration of technological and transport requirements, and the capacity for phased expansion. The continued industrial use and preservation of many of these complexes confirm the lasting value of his architectural and planning concepts, contributing to a broader understanding of Croatian industrial architecture and socialist industrial modernism of the 1950s and 1960s. Full article

The southeastern flank of Mt. Etna is affected by the presence of active faults capable of adapting to deformation through both seismic slip and aseismic creep, posing challenges for seismic microzonation and for land-use planning. Structural surveys in the urban area of San Gregorio di Catania revealed a ~1 km long, N–S trending secondary fracture zone with an extensional component, inducing progressive damage to buildings and infrastructure. To characterize this scarcely visible structure, passive seismic single-station surveys processed with Horizontal-to-Vertical Spectral Ratio (HVSR) tecnique were integrated with Multichannel Analysis of Surface Waves (MASW). The HVSR data enabled the mapping of the spatial distribution of resonance frequencies, tracking an anomalous trend in the seismic bedrock geometry and depth directly correlatable with the presence of the secondary fracture zone. Directional analyses exhibit systematic preferential orientations of resonance peaks near the fracture corridor, confirming a rigorous structural control and a tectonic origin for the recorded anomalies. Furthermore, reconstructed 2D impedance contrast sections show distinct discontinuities and a local westward dislocation of the main seismo-stratigraphic interface across the deformation zone. The lack of correlated instrumental seismicity supports the interpretation that the displacement is primary accommodated via aseismic fault creep. Methodologically, these findings demonstrate that the passive seismic method provides a highly effective, non-invasive approach for identifying hard-to-detect tectonic structures that remain unobliterated by dense urbanization. Ultimately, these results offer critical, actionable constraints for seismic microzonation and urban land-use setback zoning. Full article

Urban historic districts often present archaeological sites and historic buildings in a fragmented way, posing significant challenges for public understanding and enhancing heritage value. Solely physical conservation fails to fully communicate their cultural significance, while excessive commercialization often results in the erosion of cultural authenticity and the displacement of local communities. Drawing from cultural capital theory in sociology and cultural economics, this study redefines historical districts as sustainable urban cultural capital, comprising habituated, objectified, and institutionalized components. A Value Chain Model of Cultural Capital (VCMCC) is developed, consisting of three stages: cultural resource excavation, cultural asset cultivation, and cultural capital management. This model aims to empower heritage adaptive reuse and foster synergy between cultural heritage and economic development. Utilizing an embedded single-case design with longitudinal ethnography, the research focuses on the Western Han Archaeological Sites Historical District (WHAS HD) in Hanzhong, China. It involves multiple rounds of mixed-data collection from 2023 to 2025, on which design-based research is performed. This study operationalizes VCMCC through a series of spatially and socially grounded strategies. In the cultural resource excavation stage, superior resources are identified through a systematic review of historical archives, archaeological reports, and local gazetteers, along with surveys of architectural remains and spatial mapping. In the cultural asset cultivation stage, these resources are transformed into experiential and communicable cultural assets via a “one courtyard, one strategy” approach for activating courtyard functions, developing dual-theme heritage routes, and deploying digital interpretation tools. In the cultural capital management stage, a multi-stakeholder community committee is established, and binding institutional safeguards are integrated to ensure sustainable heritage adaptive reuse. Concurrently, a baseline indicator system covering three dimensions, cultural, social, and economic benefits, is developed to provide benchmarks for future post-intervention benefit evaluation and verification. The proposed and implemented VCMCC model translates cultural capital theory from an abstract explanatory framework into an actionable pathway for heritage adaptive reuse, offering theoretical and methodological guidance for the adaptive reuse of similar small and medium-sized historic districts. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

Smart cities increasingly rely on distributed sensing and edge intelligence to support urban planning, mobility management, environmental monitoring, and critical infrastructure operation. However, large-scale urban Internet-of-Things deployments are constrained by heterogeneous device capabilities, limited energy availability, variable communication conditions, and data-governance requirements. Federated learning offers a data-locality-preserving alternative to centralized model training, but conventional federated learning strategies often assume full, random, or fixed client participation, which can lead to unnecessary energy consumption, communication overhead, or client starvation in resource-constrained urban environments. This paper proposes an Energy- and Communication-Aware Federated Learning strategy, termed ECA-FL, for smart city sensing systems. The main novelty of the work lies in the joint use of residual device energy and communication conditions to guide adaptive client participation and local training effort, providing a tunable resource–performance trade-off rather than an accuracy-maximizing strategy alone. The framework is evaluated through a controlled simulation-based study using a synthetic multi-class urban sensing proxy task distributed across 100 federated clients under strongly non-IID conditions. Compared with full-participation FedAvg, ECA-FL reduces cumulative energy consumption by 82.9% and communication overhead by 64.7%, while maintaining a final accuracy of 0.8124 compared with 0.8319 for FedAvg-full. Compared with rigid fixed-participation strategies, ECA-FL avoids severe learning degradation by adapting participation dynamically instead of excluding clients according to a static rule. A sensitivity analysis further shows that the trade-off parameter controls the balance between learning performance and resource conservation, allowing the framework to be adjusted according to different deployment priorities. The results support the hypothesis that adaptive energy- and communication-aware participation can substantially reduce operational cost while preserving acceptable learning performance within the adopted simulation setting. The study provides practical design insights for sustainable, communication-conscious, and data-locality-preserving federated learning in smart city sensing infrastructures. Full article

Post-conflict reconstruction concentrates institutional fragility, supply-chain disruption, and weak regulatory enforcement at the moment when long-term resilience trajectories are being set. Myanmar’s housing sector, operating under prolonged civil conflict and post-earthquake reconstruction pressure, exemplifies these conditions. This research adapts Singapore’s Buildable Design Appraisal System (BDAS) and Constructability Appraisal System (CAS) to Myanmar’s post-conflict housing context and translates the empirical findings into a Knowledge-Based Decision Support System (KBDSS). An integrated framework combining Value Chain Analysis (VCA), the Technology Acceptance Model (TAM), and Scott’s Institutional Framework (IF) underpins the study. A questionnaire survey (n = 139) of Myanmar building professionals is analysed using Partial Least Squares Structural Equation Modelling and Necessary Condition Analysis. The model explains 57.9% of the variance in framework adaptation; competitive advantage, perceived usefulness, perceived ease of use, and the post-conflict/disaster context emerge as both sufficient and necessary conditions, while regulative support dominates among the three institutional pillars. These findings underpin the inference logic of a prototype KBDSS for resilient housing reconstruction. This research contributes empirical evidence on operationalising urban resilience under institutional fragility in the Global South. Full article

Urban heat stress is intensifying under climate change, particularly in outdoor public spaces where conventional mechanical cooling is impractical. This study develops a climate-driven, system-level numerical framework to evaluate the pre-deployment feasibility of modular, solar-powered spray cooling canopies across 110 cities in Türkiye. Hourly Typical Meteorological Year (TMYx) weather files, representing a single typical year constructed from 2009 to 2023 source data, are used to estimate photovoltaic (PV) energy yield, electrical load, feasible misting duration, water demand, and PV-to-load autonomy under summer daytime conditions. The misting operation is governed by a rule-based adaptive control strategy based on air temperature, relative humidity, and plane-of-array irradiance. To support transferable comparison, the cities are classified into six summer climate-archetype zones using k-means clustering of standardized climate variables, including temperature, humidity, irradiance, wind speed, and summer precipitation. Results show that evaporative cooling feasibility is governed primarily by humidity rather than temperature alone. Hot–Dry Inland cities exhibit the longest mean misting duration (501.90 h) and highest water demand (30,152 L per module), but the lowest PV-to-load autonomy ratio (1.55) because of high pump-driven electrical demand. In contrast, Humid Black Sea cities show minimal misting duration (11.43 h) and water use (465 L per module), but the highest autonomy ratio (39.68) due to very limited system activation. Thus, high autonomy does not necessarily indicate high cooling usefulness. The proposed framework provides a reproducible screening tool for identifying where PV-powered spray cooling canopies are climatically suitable, where water and PV sizing become limiting, and where alternative outdoor heat-mitigation strategies may be more appropriate. Full article

Neighbourhood-scale sustainable urban mobility assessment requires analytical tools that evaluate walking, cycling, and public transport together rather than as separate modes. Existing studies often rely on single-mode indicators or aggregated urban-scale measures, which limit their ability to reveal micro-scale spatial inequalities and multimodal performance imbalances. This study addresses this gap by developing an integrated Geographic Information Systems (GIS)–Analytic Hierarchy Process (AHP)–correlation–clustering framework for six sample areas in Kayseri, Türkiye. The framework evaluates three main criteria—walkability, bikeability, and public transport accessibility—through ten sub-criteria. In addition, seven land-use and urban design variables are used to examine built environment relationships. A 100 × 100 m grid-based spatial database was created; criteria weights were determined using AHP; mobility scores were examined through correlation analysis; and spatial mobility typologies were identified using K-means clustering. The findings indicate that development density and land-use diversity support walkability. However, similar density patterns do not automatically improve cycling performance or public transport integration. The clustering results reveal persistent modal imbalances, even in areas with medium-to-high overall performance. The study demonstrates that density alone is insufficient for multimodal sustainability and offers an adaptable decision-support framework for context-sensitive neighbourhood planning. Full article

Decommissioned airfields are increasingly recognized as strategic sites for ecological regeneration, climate adaptation, and the creation of new public spaces. However, research on their transformation has predominantly focused on the environmental performance of Nature-based Solutions (NBS), often overlooking the role of inherited spatial morphology in structuring regeneration processes and outcomes. This paper proposes an AI-assisted, morphology-based proto-ontological framework for analyzing and designing post-airfield architecture. The framework was developed through the inductive and comparative analysis of a corpus of 32 urban post-airfield regeneration projects, from which recurrent inherited morphologies, transformation actions, spatial devices, and NBS were identified and structured into a relational sequence. The framework was then applied to two contrasting case studies: Maurice Rose Airfield Park (Frankfurt) and Xuhui Runway Park (Shanghai); these were selected for their different transformation logics. The results show that similar airfield morphologies can generate markedly different climatic, ecological, social, and memory-related outcomes depending on how they are transformed and linked to NBS. The study demonstrates that inherited airfield morphologies are not passive remnants but operative spatial structures, and that NBS should be understood as spatially embedded and form-generating design components. The proposed proto-ontology offers a transferable analytical model and a basis for future computational and generative design applications. Full article

Multi-criteria group decision making (MCGDM) under linguistic uncertainty remains a fundamental challenge in applied mathematics, where decision makers seldom assign crisp numerical evaluations and frequently exhibit heterogeneous risk attitudes shaped by behavioural factors. An integrated mathematical framework, hereafter PLR-3WBC (Probabilistic Linguistic Regret-driven Three-Way Bayesian Consensus), is developed to systematically integrate four methodological components that have each been individually validated in the MCGDM literature: representation of decision information with explicit probability mass on linguistic terms; quantification of decision-maker regret and rejoice psychology under linguistic uncertainty; classification of alternatives into three actionable decision regions rather than a single-valued ranking; and group consensus reaching with credal weight aggregation. Each component has demonstrated its effectiveness in its respective domain; the present framework capitalises on their complementary strengths by embedding them within a single pipeline equipped with formal guarantees, an integration that has not been previously reported. The framework integrates five methodological components: probabilistic linguistic term sets (PLTS) for information representation; the Bayesian best–worst method (BBWM) for credal criterion weighting; a regret–rejoice value function adapted to the linguistic domain for behavioural evaluation; three-way decision (3WD) thresholds derived from a loss-function model for actionable classification; and a distance-based consensus reaching process with feedback mechanism for group convergence. A case study on age-friendliness evaluation of twelve aging urban residential communities under an indicator system of five dimensions and eighteen criteria, with four expert decision makers, demonstrates that PLR-3WBC delivers an actionable three-way classification, recovers a transparent group consensus, and produces rankings broadly consistent with classical TOPSIS, VIKOR, PROMETHEE-II, and BWM-TOPSIS (Spearman rank correlation exceeding 0.97), thereby confirming that the integrated framework preserves the ordinal reliability of these established methods, while additionally delivering three outputs that arise from the methodological integration: an actionable three-way classification enabling discrete budget-aligned decisions, credal weight intervals quantifying the depth of expert agreement on criterion importance, and a behavioural reordering of borderline non-dominated alternatives that reflects the loss-averse psychology of the decision panel and would remain hidden under single-method deployment. Sensitivity analyses with respect to the regret aversion coefficient, the loss function parameters, and the consensus threshold confirm that the qualitative classification is stable across a wide parameter envelope, supporting the practical deployment of PLR-3WBC in age-friendly community renewal programmes. Full article

Landfill tire fires are complex environmental disasters generating toxic pollutants with severe health risks. This study quantified emission dynamics and toxicological consequences of a large-scale tire fire in an urban ecosystem. A comprehensive source-to-receptor approach was applied, integrating Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) atmospheric dispersion modeling with comparison against air quality monitoring data. Soil samples collected from the fireground and surrounding urban allotment gardens were analyzed for tire-specific tracers (Zn) and 16 priority polycyclic aromatic hydrocarbons (PAHs). Human health risks were assessed using Incremental Lifetime Cancer Risk (ILCR), Toxic Equivalency Quotient (TEQ), and Mutagenic Equivalency Quotient (MEQ) metrics. Fire emissions were dominated by particulate matter (PM₁₀: 1.34 t) and PAHs (17.7 kg). Soil at the fire site showed severe contamination (Σ PAHs: 148.9 mg/kg), with benzo[a]pyrene as the primary carcinogen. The cumulative ILCR for children reached 9.7 × 10⁻⁴, exceeding the commonly used upper regulatory benchmark of 10⁻⁴. Dermal contact was identified as the dominant exposure pathway for pyrogenic PAHs. Elevated risk levels persisted at distal residential sites (ILCR: 10⁻⁵–10⁻⁴), indicating long-term environmental contamination Ecological risk quotients (RQ) exceeded unity for PAHs across all fire-impacted locations and for Zn and Cu in the immediate vicinity of the fire scene. These findings demonstrate that acute tire fire events can evolve into persistent terrestrial health hazards, highlighting the critical role of dermal exposure in PAH uptake and the need for long-term environmental monitoring and adaptive land-use management strategies to mitigate chronic health risks in urban populations. Full article

Climate change is intensifying water scarcity in the Mediterranean region, placing the Antalya province of Türkiye at significant risk due to declining water availability, rapid population growth, and intense tourism activities which increase seasonal demand. This study forecasts population and urban water demand until 2050 and evaluates several water loss reduction scenarios for the city’s drinking water distribution network. In developing the forecasted water demand, the analysis incorporates several water loss reduction scenarios. These include a baseline scenario maintaining current water loss levels, a moderate improvement scenario aligned with Türkiye’s national regulatory targets, and an advanced scenario achieving international best practices. Results show that reducing water losses, caused mainly by aging infrastructure, pressure fluctuations, and leaks, can substantially decrease total water demand. Improved network efficiency is therefore essential for maintaining long-term water security and supporting climate change adaptation efforts in Antalya. Full article

Conventional standards for evaluating the Korean Highway Capacity Manual (HCM) and U.S. HCM often inadequately represent the localized macroscopic traffic dynamics inherent in complex urban networks. To address this limitation, this study proposes an adaptive branching framework for level of service (LOS) reclassification, guided by the empirical identifiability of fundamental diagrams (FDs) and vehicular density distribution patterns. The methodology classifies traffic states into four categories: (a) FD-based LOS, (b) segmented FD-based LOS, (c) single-state LOS, and (d) empirical free-flow speed-based LOS. These categories redefine LOS criteria based on the temporal and spatial conditions prevalent in urban environments. The proposed reclassified LOS framework, applied to twenty-eight urban corridors across four distinct urban typologies using a reference free-flow speed, effectively captures region-specific performance variations. Ultimately, this research establishes a robust, data-driven methodological framework for localized LOS recalibration, thereby significantly enhancing the realism of urban traffic evaluation. Full article