Search Results (507)

Synthetic aperture radar (SAR) provides all-weather imaging but faces challenges in visual interpretation due to low contrast and coherent speckle noise. To address contrast deficiency and edge blurring in SAR-to-optical translation, we propose a Dual-Scale Aligned Network (DSAN) built upon Pix2PixHD. First, an asymmetric dual-prior architecture is designed: the global generator ingests low-resolution SAR images enhanced by histogram equalization to capture macroscopic structures, while the local generator utilizes original high-resolution SAR images to preserve microscopic details, alleviating the trade-off between contrast and fine textures. Second, a Dual-Scale Fusion Module (DSFM) coupling Large Kernel Attention and Collaborative Attention breaks scale barriers, enabling bidirectional cross-scale alignment and deep fusion. Third, a continuous differentiable soft-edge loss is formulated using logarithmic dynamic range compression to prevent highlights from dominating gradients and enforce boundary consistency across urban areas, water bodies, and farmlands. Experiments on the Nanjing and public SEN1-2 datasets demonstrate that DSAN outperforms state-of-the-art models—including Pix2PixHD, CycleGAN, MSTMNet, and ICMA—in perceptual distribution realism (FID) with the sharpest geometric boundaries. Ablation studies confirm the effectiveness of the asymmetric dual-prior design, DSFM, and the refined edge loss. Full article

Urban resilience is widely mobilised across built-environment research and practice, yet it remains conceptually contested, with definitions varying across disciplines and limiting translation into coherent planning and governance. This study examines how a multidisciplinary group of built-environment researchers conceptualise resilience and resilient futures, and how these understandings evolve through structured transdisciplinary engagement. Using an exploratory action research design, twelve academic staff and higher degree research candidates from a single built-environment school at the University of Technology Sydney in Australia participated in a two-day workshop combining individual reflection, facilitated group discussion, and engagement with the key resilience literature, followed by consolidation through collaborative writing. Thematic coding of participants’ definitions and discussions identified three primary framings: shocks and stresses, processes, and future outcomes. Participants shifted away from “bouncing back” narratives towards anticipatory preparedness, learning, adaptation, and, when needed, transformation. Cross-cutting themes highlighted the dual nature of disturbances, governance spanning formal and informal systems, multi-scalar interdependence, cultural identity and continuity through change. The study proposes a consolidated definition of urban resilience that makes these dimensions explicit and supports operationalising resilient futures. Given the single-institution sample, the definition is offered as a transferable starting point rather than a definitive interpretation. Full article

This study aims to systematically assess urban Chinese college students’ awareness and depth of understanding of the Sustainable Development Goals (SDGs), examine how digital media exposure and academic discipline shape SDG-related cognitive development, and provide empirical evidence to inform the design of sustainable development education in higher education institutions. A questionnaire survey was administered in China. Descriptive statistics, multinomial logistic regression, path analysis, and correlation analysis were employed to examine the relationships among digital media use, urban context, disciplinary background, and SDG cognition. The results are as follows. Digital media exposure and city tier were both associated with variations in SDG cognition, and a significant nonlinear threshold was observed at approximately two hours of daily media use. A clear threshold effect emerges, with students using digital media for more than two hours per day demonstrating markedly higher cognitive levels. Although overall awareness is relatively high, knowledge remains broad but superficial, with weaker understanding of ecological and collaborative goals. Disciplinary differences are evident—medical and agricultural students show stronger comprehension, while arts and humanities students lag behind—yet support for interdisciplinary collaboration is substantial. Participation in SDG-related learning activities significantly enhances attitudinal and behavioral change. This study advances the literature by integrating digital media exposure, urban hierarchy, and academic discipline into a unified analytical framework to explain variations in SDG cognition among Chinese urban college students. It identifies a significant media use threshold effect (over two hours per day) that enhances cognitive accumulation, revealing a nonlinear mechanism rarely examined in prior research. By uncovering disciplinary heterogeneity and the relative weakness in ecological and collaborative goal awareness, the study moves beyond descriptive assessments to provide targeted, evidence-based implications for curriculum design and interdisciplinary sustainable development education in higher education institutions. Full article

This study measures construction waste management efficiency (CWME) in 27 EU member states (2016–2025) using a three-stage super-efficiency SBM-DEA model, constructs a spatial correlation network via a modified gravity model, and employs social network analysis and random forest to investigate network structure and driving mechanisms. Results reveal persistent cross-country heterogeneity and a widening East–West efficiency divide. The CWME network exhibits small-world characteristics, with CONCOR analysis partitioning member states into four blocks: Northern and Baltic states serve as the dominant Net Spillover bloc, whereas Southern periphery countries remain Net Beneficial recipients whose membership contracted from five to three by 2025. Random forest identifies government environmental protection expenditure, unit labour cost, and population density as the top three driving factors, with unit labour cost and government environmental protection expenditure exhibiting the strongest negative marginal effects on CWME, while urbanization rate shows a near-neutral relationship. These findings provide empirical support for policy interventions targeting the structural economic determinants of CWME. By integrating efficiency measurement, spatial network analysis, and machine learning-based driver identification, this study offers a comprehensive framework for diagnosing regional disparities in construction waste governance and informing cross-regional collaborative policy design. Full article

Urban green space supply (UGSS) is a core component of territorial spatial planning, and the advancement of the park city initiative has been temporally associated with a systematic transformation. Differentiation in UGSS is a comprehensive issue concerning ecological environment, public welfare, and high-quality urban development, and it is closely related to the achievement of United Nations Sustainable Development Goal (SDG) 11.7. This study employs a comprehensive approach combining spatiotemporal dynamic analysis (Mann–Kendall trend test and Theil–Sen slope estimation), differentiation measures (Gini coefficient and Theil index), and the explainable machine learning SHAP model to conduct a large-sample empirical analysis of 1760 towns in China from 2015 to 2024. The findings show the following: First, park city construction corresponds to notable spatiotemporal evolution of UGSS in China’s towns, with approximately 85% of towns showing a significant rise. Second, park city construction coincides with a reduction in differentiation in both the outcomes and processes of UGSS in China’s towns, with both the Gini coefficient and Theil index declining to varying degrees. An analysis of the Theil index further confirms that the observed changes in the Theil index are more pronounced in disadvantaged towns, and the differentiation in UGSS originates more from intra-regional disparities than from inter-regional gaps. Third, the differentiation in UGSS shows deep structural correlates, with the associations of socio-economic and natural ecological factors exhibiting various complex nonlinear associations such as inverted U-shape, arc shape, U-shape, and wave shape. These associations are specifically manifested as mixed directionality of associations, hierarchical intensity of associations, threshold-based evolutionary pathways, geographic spatial heterogeneity, and interactive relationships among factors. This study recommends that the policy design of park city construction and green space system planning should promptly establish a new model combining situational response, threshold management, and collaborative governance. The nonlinear and interpretable analytical paradigm constructed in this study holds significant value for achieving precise supply and equitable sharing of green space resources. Full article

This review examines how smart city technologies have influenced health equity in urban settings between 2019 and 2026, guided by a dual-lens framework that assesses both equity-related outcomes and the systemic factors enabling or constraining their realization. As cities increasingly turn to digital tools to strengthen healthcare delivery, it remains unclear whether these interventions narrow or widen existing health disparities. Drawing on interdisciplinary literature spanning public health, urban informatics, and digital governance, this synthesis finds that smart health initiatives have improved healthcare access for some underserved populations, but their overall effect on health equity remains modest, inconsistent, and highly dependent on local context. Persistent structural obstacles, including digital divides, socio-economic inequality, and fragmented governance, continue to limit equitable implementation, while institutional barriers emerge as the most widespread challenge. Conversely, people-centered design, participatory governance, inclusive digital infrastructure, and equity-sensitive policy frameworks stand out as critical enablers of more just outcomes. The review further identifies an underexplored link between environmental sustainability and smart city technology, showing that AI-driven tools addressing emissions and urban environmental quality can indirectly support more equitable health systems. Overall, the findings underscore that technological innovation alone is insufficient; realizing the equity potential of smart cities requires deliberate integration of social justice, environmental sustainability, and collaborative governance into digital health strategy and practice. Full article

As China’s urbanization shifts toward quality-oriented development, urban regeneration increasingly prioritizes the perceived quality of public spaces to enhance urban vitality and advance sustainable urban living. This study takes Zhengzhou’s Dongfeng Canal, a revitalized urban core waterfront, as a case to develop a human–machine collaborative analytical framework for exploring nonlinear relationships between visual environmental features and human spatial quality perception. By integrating 779 geolocated panoramic images with volunteers’ subjective rating data, this study adopts deep learning-based semantic segmentation to quantify eight objective visual indicators (e.g., greenness, color diversity, spatial structure). A random forest (RF) model links these indicators to three perceptual dimensions: scenic beauty, safety, and recreational value. Adopting explainable artificial intelligence (SHAP and PDPs), the results indicate that: (1) greenness is positively associated with positive perceptions but exhibits a significant threshold effect; (2) color diversity and waterfront accessibility substantially improve user experience, while excessive uniformity and extreme openness negatively affect perceived spatial quality. These findings challenge the simplistic linear “more-is-better” assumption in urban design and highlight the value of balanced, context-sensitive spatial interventions. This study provides evidence-based, segment-specific strategies for urban waterfront regeneration, advancing people-centered planning that integrates ecological functionality, social inclusivity, and long-term sustainability via Geospatial Artificial Intelligence (GeoAI) and geospatial analytics. Full article

Coordinating air pollution control with carbon mitigation is a central challenge for urban sustainability. However, there is currently a lack of sufficient research on whether digital infrastructure can complement environmental regulations to enhance the synergy of pollution and carbon emission reduction (SPCER). Using the overlapping implementation of China’s Key Air Pollution Control Zones (KAPCZs) and Broadband China (BC) policies as an empirical policy setting, this study applies a partially linear Double Machine Learning framework to panel data for 282 Chinese cities from 2006 to 2023. The results show that the dual-policy pilots significantly improve urban SPCER, while a unified interaction test further provides statistical evidence of a positive synergistic effect between the two policies. Mediation analyses provide evidence consistent with Green Technological Innovation, industrial structure upgrading, and green finance development as potential transmission mechanisms. Formal cross-group tests reveal significant heterogeneity across regions and city characteristics, with larger effects in highly urbanized, low industrial development, non-old industrial base, central, and non-resource-based cities. Spatial Durbin Model estimates further indicate positive spillovers to neighboring cities. These findings demonstrate the potential value of coordinating environmental regulation with digital infrastructure and provide evidence for differentiated policy design and cross-regional collaboration in urban digital–green transitions. Full article

High-density school design has become an important challenge in rapidly urbanizing cities, where land scarcity, increasing educational demand, and evolving pedagogical models generate multiple and interrelated design constraints. Although a wealth of design experience has accumulated through the execution of numerous school planning projects, this knowledge remains fragmented across architectural publications and project narratives. Existing studies have primarily focused on evaluating built environments or individual cases, and limited attention has been paid to how dispersed architectural design reasoning can be systematically extracted, organized, and represented. This study was conducted to explore how AI-assisted semantic modeling can support the extraction and organization of architectural design knowledge from large-scale design discourse through a human–AI collaborative interpretation framework. Using a corpus of 330 documents reporting school design in Shenzhen published between 2017 and 2024, the proposed framework integrates BERTopic-based semantic modeling, scenario–strategy coding, network analysis, and document-based architectural interpretation to establish a continuous workflow from architectural discourse to structured knowledge representation and spatial interpretation. The results reveal a density-conditioned knowledge structure consisting of six interconnected design agendas, 25 recurrent design scenarios, 44 original design strategies, 17 core strategies, four strategy clusters, and four document-supported spatial response patterns. The findings demonstrate that high-density school design knowledge is organized through recurring problem–strategy relationships rather than isolated project solutions. Through human–AI collaborative interpretation, fragmented design narratives are transformed into hierarchical representations linking design concerns, scenarios, strategies, and spatial organizations. The aim of the proposed framework is not to automate architectural decision-making or generate implementation-ready design solutions but to provide a methodological foundation for AI-assisted architectural knowledge retrieval, knowledge representation, and future multimodal design intelligence systems. Full article

This study examines how spatial design, particularly lightscape interventions, operates as a behavioral nudge associated with collaborative participation intention in urban environments. Drawing on nudge theory, place attachment, and cultural heritage literature, we analyze data from a questionnaire survey of 720 urban residents across major metropolitan regions in Japan using structural equation modeling (SEM). The results indicate that urban development and cultural heritage assets are positively associated with lightscape interventions, which in turn show a strong positive relationship with collaborative participation intention. While urban development exhibits both direct and indirect relationships with participation intention, the influence of cultural heritage assets operates primarily through lightscape interventions as a mediating mechanism. These findings suggest that cultural heritage alone does not automatically stimulate civic participation; rather, its social value is activated when heritage resources are translated into meaningful spatial and visual experiences. Lightscape interventions thus serve as an effective non-coercive mechanism linking spatial and cultural resources to civic engagement intentions. This research offers valuable insights for urban planners and policymakers seeking design-based, non-coercive strategies to enhance citizens’ place attachment and willingness to contribute to community activities. Full article

Disaster governance in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) spans multiple administrative regions, institutions, and platforms, and hazards such as typhoons, storm surges, and urban waterlogging generate strong cross-boundary spillovers that no single city can manage alone. To explain the persistent problems of stakeholder hesitation, underinvestment, and free-riding, this study treats collaborative disaster governance as a multi-actor system and develops a tripartite evolutionary game model linking the regional coordinating regulatory authorities, local emergency management actors, and social participation actors. Static, linear dynamic, and nonlinear dynamic reward–punishment regimes are embedded into the payoff matrix and examined through stability analysis and numerical simulation. The results show that, without incentives, the system settles into an imbalanced “regulatory authorities-driven, weak collaboration” equilibrium; static mechanisms improve targeted behavior but erode the regulatory authorities’ willingness to lead; and linear dynamic mechanisms induce strategy oscillations in cross-regional settings. Under a parameter-adjusted nonlinear dynamic mechanism that combines incremental incentives with progressive constraints, the tested system converges toward “active leadership–proactive collaboration–active participation” under the assumed cost, benefit, and initial-condition settings. These findings provide a basis for designing differentiated subsidies, performance-based rewards, and liability recovery in GBA disaster governance. Full article

Against the backdrop of deepening global climate governance and the ongoing advancement of the dual carbon goals, clarifying whether climate risk management can effectively drive improvements in urban green energy efficiency holds significant importance for synergistically advancing climate adaptation and green transition. This study employs data from 284 prefecture-level and above cities in China spanning 2012–2023, utilising the climate-resilient city pilot policy as a quasi-natural experiment. By integrating dual machine learning models with spatial lag models, it systematically examines the causal effects, transmission mechanisms, and spatial spillover characteristics of climate risk governance on urban green energy efficiency. Findings reveal: ① Climate-resilient city development significantly enhances local green energy efficiency through three pathways: green finance development, green technological innovation, and industrial structure upgrading; ② The impact exhibits pronounced spatio-temporal heterogeneity, characterised by delayed and amplified effects, particularly pronounced in inland, central cities, and non-resource-based cities; ③ The impact exhibits a pronounced positive spatial correlation, not only catalysing local green transitions but also generating positive spatial spillovers to neighbouring regions, indicating potential for regional collaborative development. Additionally, green finance itself possesses positive cross-regional spillover effects. This study provides empirical evidence and policy recommendations for optimising climate adaptation policy design, strengthening green finance coordination, and advancing regionally linked green transitions. Full article

In the context of temporary urban environments such as festivals and construction sites, acoustic discomfort inside textile-based party tents remains a critical yet under-addressed issue. This study, developed in collaboration with industrial partners from the construction and textile sectors, aimed to design and assess lightweight, flexible sound-absorbing solutions capable of improving acoustic comfort while reducing environmental impact. A set of nine composite textile samples were fabricated using combinations of recycled and technical materials. Their acoustic behavior was characterized through standardized laboratory tests (ISO 10140-2 and ISO 354:2004) and full-scale prototypes under simulated real-world conditions. Simultaneously, a Life Cycle Assessment (LCA) was conducted according to ISO 14040:2006 and EN 15804:2020 standards to quantify environmental impacts from cradle to gate. The results demonstrate that it is possible to achieve an effective balance between acoustic performance and environmental sustainability. Integrating both types of assessment into the material selection process enables more informed, responsible design decisions for temporary textile structures, aligning construction practices with growing demands for functional and sustainable solutions. Full article

Rapid urbanization and climate change have intensified environmental pressures and social inequalities, making the integration of urban resilience and sustainable development a critical global challenge, with Nature-based Solutions (NbS) emerging as a promising pathway; however, the knowledge structure, collaboration patterns, and evolutionary trends of NbS research remain fragmented and insufficiently understood. This study conducts a comprehensive bibliometric analysis of 1261 publications from the Web of Science Core Collection (2005–2025), employing tools including VOSviewer 1.6.20, CiteSpace 6.4.R1, and Bibliometrix 4.1.3 to map publication trends, collaboration networks, knowledge bases, and thematic evolution. The results reveal a rapid expansion of NbS research since 2013, characterized by strong interdisciplinarity and a multicentric yet uneven geographical distribution dominated by China, the United States, and Europe. Four major research clusters are identified, encompassing policy governance, environmental benefits, ecosystem services, and social equity, reflecting a shift from ecological performance to integrated socio-ecological frameworks. Additionally, thematic evolution indicates growing emphasis on governance mechanisms, public health, and environmental justice. Overall, NbS research is transitioning toward a multi-scale, multi-objective, and governance-oriented paradigm. These findings highlight the need for strengthened international collaboration, standardized evaluation frameworks, and inclusive policy design to enhance the effectiveness and global applicability of NbS in advancing urban sustainable development. Full article

With the acceleration of urbanization, wind environment problems in high-density blocks have become increasingly prominent. Most existing studies only focus on the identification of influencing factors, lacking a complete closed loop from “diagnosis” to “design verification”. This study takes 174 blocks along the Qingnian Street Metro Line in Shenyang as research objects, uses PHOENICS (2019) software, and clarifies the seasonal distribution characteristics of the wind environment in high-density blocks through field measurement and simulation verification. The XGBoost-Shap method is employed to identify key morphological factors and their nonlinear influence mechanisms. The K-means clustering method is adopted to construct the typology of calm wind zones, which are classified into three categories: Type A (narrow street canyon-comprehensive resistance type), Type B (high-density enclosed type), and Type C (high-rise obstruction type). Multi-scenario simulations are conducted for each type, and differentiated optimization schemes are designed accordingly. The results show that under specific CFD boundary conditions representing typical cold climate urban environments, eight indicators, including enclosure degree (ED), sky visibility (SVF), and windward area ratio (FAI), have significant seasonal sensitivity effects on wind environments. The effect of multi-strategy collaborative optimization is significantly superior to that of a single intervention. This study verifies the effectiveness of the typological approach in bridging wind environment mechanism identification and spatial optimization design. Thresholds for indicators such as enclosure degree (ED), sky visibility (SVF), and building density (BD) can be used as preliminary design-screening tools, providing a reference for ventilation improvement design ideas along high-density subway lines in actual urban construction. Full article