Search Results (192)

This paper examines the spatial integration of post-socialist churches and parish complexes within the modernist housing estates of Novi Zagreb. Constructed after 1990 in neighbourhoods originally planned without sacral programs, these buildings represent a specific form of post-socialist urban intervention. The study employs a qualitative, comparative approach, analysing five case studies through the parameters of urban context, volumetry, spatial composition, program, and public space interface. The analysis identifies a limited set of recurring typologies that define patterns of spatial integration within the existing urban fabric. The findings indicate that these complexes do not function as dominant urban elements, but instead adapt to the open, functionally organized structure of modernist planning. Their impact on public space remains limited, as they rarely generate new centres or clearly articulated urban nodes. At the same time, the results reveal a shift from singular religious buildings toward programmatically expanded parish complexes that incorporate social and community functions. However, this transformation remains largely internal and does not lead to a significant reconfiguration of the urban structure. The paper contributes to the understanding of post-socialist urban transformation by identifying typological patterns and interpreting religious architecture as a context-dependent urban actor. Full article

The transition to automated vehicles (AVs) introduces complex human factors and system-level challenges across Society of Automotive Engineers (SAE) Levels 0–5, with profound implications for the long-term viability of future transport infrastructure. Drawing on a synthesis of socio-technical, cognitive, and behavioural adaptation theories, this study develops an integrated framework to analyse the evolving relationships among driving automation, human behaviour, system risks, and urban sustainability. The findings demonstrate that human-factor risks are inherently nonlinear, meaning they do not decrease proportionally as technology advances; instead, risk profiles peak significantly at intermediate automation levels (SAE 2–3) due to supervisory fatigue and delayed takeovers, introducing severe traffic flow volatility and localised micro-congestion that directly compromise the environmental efficiency of sustainable transport systems. As these risks reconfigure into institutional and digital infrastructure dependencies at higher levels (SAE 4–5), the primary constraint shifts toward network readiness. Through an analysis of real-world AV deployment case studies and a structured narrative literature review, this paper identifies critical operational discontinuities and mixed-traffic complexities that threaten urban grid resilience. This study proposes a conceptual framework that translates these cross-level socio-technical insights into actionable deployment pathways, providing policymakers with adaptive governance models, transportation planners with mixed-traffic management strategies aimed at preserving network efficiency, infrastructure agencies with physical and digital readiness criteria for long-term asset sustainability, and AV developers with human–machine interface optimisation frameworks to secure human-centric safety within sustainable smart city networks. Full article

Unsustainable land-use transitions in peri-urban watersheds threaten both food security and ecological integrity. While Patch-generating Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models for ecosystem service (ES) assessment are commonly integrated, limited studies have simultaneously (i) accounted for multiple real-world spatial policies (e.g., ecological redlines) as hard constraints, (ii) targeted a comprehensive suite of ESs, and (iii) explicitly pursued synergies without relying on large-scale land conversion. To address these gaps, we developed a spatially explicit framework that integrates the PLUS and InVEST models to simulate four land-use scenarios and assess six ESs—grain yield, water yield, nitrogen export, phosphorus export, soil conservation, and carbon sequestration—in the Yuqiao Reservoir watershed, China, during 1990–2030. Against a backdrop of historical declines in cropland/grassland and key ESs due to construction expansion (1990–2020), the novel Comprehensive Development scenario—implementing slope-adaptive management and riparian buffers—synergistically increases grain yield (+0.55%) and carbon sequestration (+1.10%) while drastically reducing phosphorus export (−10.86%). It demonstrates that synergistic gains can arise from strategic spatial reconfiguration within a stable land-use area, advancing a paradigm from area-centric to configuration-centric optimization. This provides a quantifiable methodological basis and actionable policy reference for land spatial optimization in similar water-source watersheds. Full article

This paper investigates secure and low-latency communications in UAV-mounted simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted urban vehicular networks, where severe blockage, high vehicle mobility, eavesdropping threats, and delay-sensitive traffic services coexist. In the considered system, the UAV is used not only as an aerial carrier for the STAR-RIS but also as a mobile intelligent control node that can dynamically adjust its horizontal aerial position according to vehicle distribution, blockage conditions, and eavesdropping threats. First, a UAV-STAR-RIS-assisted vehicular communication system model is developed by jointly considering urban blockage, vehicle mobility, passive eavesdropping attacks, queueing dynamics, and UAV flight constraints. Then, a high-dimensional, non-convex, and strongly coupled dynamic optimization problem is formulated to maximize the long-term average secure and low-latency utility through the joint optimization of the UAV trajectory, the STAR-RIS transmission–reflection partition ratio, the phase-shift matrices, and the transmit power allocation. Furthermore, the problem is modeled as a Markov decision process with continuous state and action spaces, and a hierarchical constrained soft actor–critic (HC-SAC)-based joint control algorithm is proposed to enable adaptive UAV movement, STAR-RIS configuration, and power control in complex dynamic environments. Simulation results demonstrate that the proposed method outperforms DDPG and several structural benchmark schemes. In the representative evaluation, the proposed HC-SAC achieves an average delay of 10.85 slots and a secrecy outage probability of 0.7160, compared with 11.72 slots and 0.8501 for PPO, and 11.94 slots and 0.8599 for DDPG. Although PPO provides the highest average secrecy rate and successful service ratio, the proposed method still maintains a competitive secure communication capability and service reliability. A normalized composite utility analysis further shows that HC-SAC attains the highest utility value of 0.9254, indicating a more favorable security–latency trade-off in complex urban vehicular scenarios. Full article

This study examines how power transmission infrastructure expansion reshapes manufacturing agglomeration and regional industrial systems. Taking China’s ultra-high-voltage (UHV) transmission projects as a quasi-natural experiment, we investigate their impact on manufacturing agglomeration. Using panel data from 282 prefecture-level cities over the period 2006–2020, we adopt a comprehensive empirical strategy centered on a multi-period difference-in-differences (DID) framework, complemented by synthetic DID, propensity score matching, instrumental variable approaches, and double machine learning methods to ensure robust causal inference. The results show that UHV projects significantly promote manufacturing agglomeration, indicating a substantial reconfiguration of regional industrial systems. This effect operates through increased power supply in input areas, the release of resource advantages in output areas, and market scale expansion. Both input and output sides have significant positive effects, with a stronger impact from the input side. Moreover, government intervention and infrastructure development further amplify the agglomeration effect. Furthermore, the manufacturing agglomeration induced by UHV projects promotes economic growth, green development, and urban sustainability. These findings provide system-level insights into the role of power transmission infrastructure in energy–industrial integration and offer implications for the design and optimization of sustainable energy systems. Full article

Semantic segmentation of street-view imagery has become an important computational tool for urban morphological analysis and the evaluation of street spatial quality. However, existing methods still struggle in complex urban environments. Major challenges include large variations in building façade scales, degradation of boundary information, and severe class imbalance. These issues limit the ability of current models to capture structurally meaningful urban forms. To address these challenges, this study proposes a high-resolution street-view segmentation framework, termed HieraWaveSeg. The model aims not only to improve pixel-level segmentation accuracy but also to enhance the interpretability of urban morphology through structured representations of street space. Specifically, a Hiera Transformer backbone is employed to capture hierarchical spatial semantics. A Path Aggregation Network is further introduced to strengthen cross-scale feature interaction and improve structural consistency in complex scenes. In addition, a Wave Fusion module based on the Haar wavelet transform is incorporated to preserve fine-grained architectural details by enhancing high-frequency boundary and texture information during decoding. Unlike conventional segmentation approaches that primarily focus on object recognition, this study introduces a morphology-oriented semantic reconfiguration strategy. This strategy reorganizes original categories into functionally meaningful urban units. As a result, the segmentation outputs can be more directly linked to urban morphological indicators, such as façade continuity, spatial enclosure, and interface permeability, thereby improving interpretability in architectural and urban design contexts. To further address class imbalance, a composite loss function combining weighted cross-entropy and Dice loss is adopted, together with a median frequency balancing strategy. Experimental results on the CamVid and Cityscapes datasets demonstrate that the proposed method consistently outperforms several state-of-the-art baselines in both segmentation accuracy and structural preservation. Beyond quantitative improvements, the results indicate that the proposed framework generates more coherent and morphologically meaningful urban representations, supporting further quantitative analysis in urban morphology and architectural studies. Full article

Urban shrinkage has evolved from a localized phenomenon into a systemic challenge within China’s rapid urbanization, rendering traditional growth-oriented planning paradigms increasingly obsolete. However, existing research often treats shrinkage as either a passive outcome or an isolated shock, lacking a holistic perspective on how complex urban systems can adapt and reorganize under prolonged decline. This study constructs a coupling framework integrating urban shrinkage with Social–Ecological System (SES) resilience to bridge this theoretical gap. Drawing on a systematic literature review of 76 peer-reviewed articles following the PRISMA guidelines, we identify six core dimensions that drive this coupling. These dimensions consist of distinct physical and social elements. Our analysis reveals that the interactions between rigid physical environments and highly fluid social elements trigger nonlinear cascading feedback loops. While demographic contraction amplifies systemic risks, the subsequent structural release provides crucial spatial and institutional room for right-sizing. To translate these mechanisms into actionable governance strategies within the Chinese context, we propose a dual-track paradigm. Regionally, strategies emphasize collaborative risk monitoring, cross-boundary factor substitution, and industrial functional complementarity to mitigate vulnerability spillover. Locally, planning needs to pivot toward systemic downsizing and social empowerment, integrating proactive spatial reduction with agile service provision and community capacity-building. Ultimately, integrating structural reconfiguration with grassroots social learning enables shrinking cities to establish a new resilient equilibrium. While anchored in the Chinese context, this dual-track governance paradigm offers transferable insights for global shrinking cities seeking to overcome structural lock-in and foster adaptive SES resilience. Full article

This study analyzes domestic tourism mobility in Spain using aggregated and anonymized mobile phone data, with a particular focus on the outbound market of the municipality of Madrid and its territorial redistribution between September 2019 and September 2025. Using experimental statistics from the National Institute of Statistics (INE), a monthly series of origin–destination flows to all Spanish municipalities was constructed, harmonizing the municipal database and incorporating intensive indicators to improve inter-territorial comparability. The spatiotemporal dynamics were integrated into a Space–Time Cube (monthly resolution), and Emerging Hot Spot Analysis (EHSA) was applied to classify the persistence, intensification, or attenuation of high- and low-intensity clusters. Additionally, the grouping of time series allowed for the identification of seasonal patterns associated with coastal, urban, and nearby inland destinations. The results show: (i) a synchronous disruption in the spring of 2020 linked to COVID-19; (ii) a staggered recovery beginning in 2021, consolidating in 2023–2025; and (iii) a dual structural pattern, with a strong concentration of volumes in large urban and coastal hubs, along with high relative intensities in small municipalities in the ring surrounding Madrid. EHSA identifies intensifying hotspots in established coastal systems (Costa del Sol and Costa Blanca) and cooling or attenuated dynamics in parts of the inland region, consistent with the reconfiguration of the “tourism radius” following the pandemic. Limitations arising from statistical confidentiality and the representativeness of the source are discussed, and future research directions are proposed based on the integration of the information with expenditure and transportation data and on spatiotemporal modeling to support destination planning and management. Full article

To mitigate large-scale blackout risks in urban distribution systems under typhoon-induced extreme weather and to reduce post-disaster restoration costs, this study proposes a resilience-oriented spatiotemporal co-optimization framework integrating transportation networks, power grids, and distributed energy resources. First, a city-scale typhoon spatiotemporal model is established, integrating static wind field, dynamic evolution, and trajectory-based mobility with urban-geometry-driven wind speed correction to characterize the spatiotemporal progression of extreme wind hazards. Second, the time-varying failure rates of distribution network components are quantified by explicitly accounting for network topology correlations, while the spatiotemporal dispatchability and output characteristics of distributed resources under disaster conditions are systematically modeled. Third, a pre-disaster proactive deployment model is formulated to minimize load curtailment costs and resource allocation expenditures. The model integrates active network reconfiguration with coordinated placement of distributed generation (DG) and mobile energy storage systems (MESSs), enabling resilience-enhancing pre-positioning strategies. Subsequently, a post-disaster restoration scheduling model is developed with the objective of minimizing unserved load. By embedding traffic flow constraints and optimal path computation under disrupted transportation conditions, the proposed framework realizes spatiotemporal coordination among MESSs, DG, and electric vehicles (EVs), thereby accelerating system-level recovery. Finally, the effectiveness of the proposed strategy is validated on a 51-node urban distribution system located in eastern coastal China, demonstrating significant improvements in restoration performance and resilience enhancement. Full article

Understanding how sustainable urban competitiveness evolves within megaregions has become a central concern in urban and regional studies, particularly under the pressures of carbon neutrality, spatial inequality, and network-driven urbanization. This study develops a multidimensional framework to assess the sustainable competitiveness of cities in the Beijing–Tianjin–Hebei “2 + 36” urban agglomeration and examines its spatio-temporal evolution and relational structure. Using a 30-indicator system grounded in factor foundations, economic performance, innovation capacity, openness, and environmental livability, we construct a composite competitiveness index through principal component analysis (PCA). Kernel density estimation reveals a pattern of overall improvement accompanied by widening disparities, characterized by selective agglomeration and the emergence of a pronounced high-value tail. Spatial autocorrelation consistently indicates significant spatial dependence, while LISA analysis identifies persistent low–low clusters and limited spillover absorption around core cities. A modified gravity model further uncovers a transition from a linear, corridor-based linkage structure to a more polycentric and networked competitiveness system, albeit with enduring peripheral weak nodes. The study contributes theoretically by conceptualizing sustainable urban competitiveness as a multidimensional nexus shaped jointly by territorial attributes and relational network structures. It demonstrates that competitiveness dynamics in megaregions emerge from the interplay of hierarchical consolidation, spatial divergence, and network reconfiguration—challenging the traditional assumption of simple core-to-periphery diffusion. The findings offer broader global implications, showing that the Beijing–Tianjin–Hebei case mirrors worldwide megaregional patterns, where proximity alone is insufficient to ensure functional integration, and where coordinated governance, network embeddedness and sustainability transitions increasingly determine regional competitiveness. This research provides a comprehensive analytical foundation for understanding and governing megaregional competitiveness in the era of sustainable development. Full article

As a policy-driven land use transition initiative bridging poverty eradication and sustainable development, China’s Poverty Alleviation Relocation (PAR) program exemplifies how state-led resettlement can reconfigure land use patterns while balancing immediate livelihood security with long-term community capacity development. The integration of large-scale PAR communities into new urbanization is a critical postrelocation task that is essential for consolidating poverty eradication achievements and enhancing endogenous development capacity. This study examined how the configuration of policy instruments shapes the endogenous development capacity of PAR communities during their transition to new urbanization. Employing a “tool–goal” analytical framework, we conducted a content analysis of 38 provincial-level policy documents (2021–present) using NVivo 20 software. The findings reveal that while local governments have established a preliminary policy system, structural imbalances persist: (1) uneven deployment of policy tools, (2) underutilization of demand-based policy tools, (3) tool–goal misalignment, and (4) insufficient market/societal participation in government-led measures. The discussion further reveals that the land use transition in the PAR program emphasizes the “living mode” (housing and public services) over the “livelihood mode” (productive resources and nonagricultural employment), creating structural dependency and leaving industrial land underutilized—as evidenced by weak policy support for industrial development (14.83%) and labour outmigration from resettlement areas. Drawing on the sustainable livelihoods framework, we further demonstrate how this exogenous-dominated policy mix disproportionately enhances physical and financial capital while constraining the accumulation of human and social capital—the very foundations of endogenous development capacity. To address these issues, we propose three key recommendations: (1) optimizing the policy mix to strengthen the endogenous development capacity of PAR communities; (2) realigning policy tools with objectives to achieve diversified yet coordinated goals; and (3) addressing implementation gaps to better leverage market mechanisms and social forces in promoting the sustainable urban integration of resettlement areas. Full article

In the digital economy era, Urban vitality has transitioned into an intertwined Virtual-Physical system. This study examines Changsha’s five urban districts through a dual-dimensional framework bridging physical (social, economic, cultural, and ecological) and virtual (video, social, and digital life) dimensions. Integrating Coupling Coordination Degree (CCD) and XGBoost-SHAP models, we elucidate the spatial patterns and nonlinear drivers of Virtual-Physical synergy. The results indicate that: (1) Urban Vitality exhibits a significant center-periphery gradient. Although the Coupling Degree between the two dimensions is high, the overall CCD remains relatively low, reflecting pervasive spatial mismatches. Notably, 55 units display a reverse pattern where Virtual Vitality surpasses Physical Vitality, suggesting that digital flows can reconfigure urban space by transcending traditional locational constraints. (2) Interactions within the built environment exert pronounced threshold effects. Structural elements require specific critical masses to activate synergy, beyond which marginal returns diminish, as exemplified by the U-shaped effect of the Green View Index and the inverted U-shaped effect of Spatial Enclosure on CCD. (3) Interaction analysis identifies building density as a multiplier, unlocking the synergistic potential of land-use mix and transport networks once critical thresholds are surpassed. Furthermore, the efficacy of population and transit relies on dense road networks and intersection, while functional diversity buffers against negative micro-environmental impacts. This study advocates for a shift from facility-increment to threshold-triggered precision strategies in urban regeneration, providing empirical support for human-centric planning in the digital twin era. Full article

To address the critical requirements for electromagnetic spectrum orchestration in complex ultra-dense communication environments, this paper proposes an Expert Knowledge-Guided improved NSGA-III framework to solve large-scale frequency assignment problems efficiently. which is built upon the standard NSGA-III architecture as the algorithmic backbone. Traditional multi-objective evolutionary algorithms often struggle with slow convergence and insufficient local search capabilities when navigating high-dimensional, strongly constrained search spaces. In this study, we first introduce a Conflict Graph-based Intelligent Initialization strategy to generate high-quality initial populations by constructing an interference conflict graph based on network topology. Second, a Knowledge-Guided Mutation operator is designed to precisely identify and reconfigure conflicting communication nodes using physical layer indicators. Furthermore, a Best-individual Guided Double-Scale Mutation mechanism is incorporated to dynamically balance global exploration and local exploitation. Experimental results on complex multi-node datasets demonstrate that EKG-NSGA-III significantly outperforms the standard NSGA-III and other baseline algorithms in terms of Hypervolume and Inverted Generational Distance. Specifically, for the 200 nodes scenario, the proposed method achieves a 25.7% improvement in IGD and a 4.2% increase in HV compared to the standard NSGA-III. The proposed algorithm provides a robust and efficient solution for spectrum management in complex urban electromagnetic environments, such as future smart city infrastructures. Full article

The increasing electrification of urban transportation has formulated a tightly coupled energy-mobility nexus. Under extreme disaster events or grid faults, rapidly restoring power supply capacity and re-dispatching shared electric vehicle (EV) fleets are critical for enhancing system resilience. Existing co-optimization methods face the curse of dimensionality when dealing with high-dimensional discrete grid reconfigurations and continuous spatio-temporal EV queuing dynamics. While multi-agent deep reinforcement learning (MADRL) offers real-time responsiveness, it inherently struggles to satisfy strict physical constraints, frequently generating infeasible and unsafe actions. To bridge this gap, this paper proposes a heuristic-guided safe multi-agent reinforcement learning (Safe-MADRL) framework for the resilient dispatch of the energy-mobility nexus. Instead of relying solely on black-box neural networks, the framework structurally embeds physical models and heuristic solvers into the learning loop. A quantum particle swarm optimization (QPSO) algorithm acts as a heuristic action refiner to ensure that grid topology actions strictly comply with non-linear power flow and voltage constraints. Simultaneously, a mixed-integer linear programming (MILP) model coupled with a single-queue multi-server (SQMS) model serves as a safety projection layer. This layer mathematically guarantees EV battery energy continuity and accurately quantifies spatio-temporal queuing delays at charging stations. Case studies on a coupled IEEE 33-node distribution system and a regional transportation network demonstrate that the proposed Safe-MADRL framework achieves zero physical violations during training and significantly outperforms traditional mathematical optimization and pure learning-based methods in computational efficiency, system power loss reduction, and overall operational economy. Full article

Outdoor music festivals (OMFs) increasingly operate as a form of temporary land use that activates urban stock land, yet how such land-use reconfigurations unfold across uneven urban–rural geographies remains insufficiently examined. Taking China’s OMFs from 2013 to 2024 as a case, this study applies the Geodetector model within a spatial justice framework to analyze fifteen indicators organized along the distributional, procedural, and recognition dimensions. The results show a pronounced “market-sinking” trend accompanied by westward expansion, and the seasonal clustering gradually moderated. The three dimensions jointly shape OMFs’ diffusion through distinguishable pathways, with the procedural dimension exhibiting the highest explanatory power through institutional steering and industrial coordination, followed by the recognition dimension through demographic foundations and digital visibility, and the distributional dimension through material and infrastructural accessibility; interaction detection further indicates that their joint presence produces amplified effects. These mechanisms align with international land-use and territorial-governance studies, while reflecting the state-led coordination distinctive to China. The findings point to an emerging form of collaborative co-creation in which governmental, market, and community actors jointly shape the spatial production of cultural events, extending the classical core–periphery account and informing debates on the territorial governance of event spaces in non-metropolitan regions. Full article