Search Results (2,209)

Urban heritage revitalization relies on public cultural cognition, yet the psychological impact of spatial morphology remains under-quantified. This study integrates space syntax with survey data to evaluate the relationship between five spatial metrics and six cultural dimensions, including authenticity, integrity, vitality, involvement, diversity, and identity, across three heritage cases. Correlation and clustering analyses reveal that spatial configuration dictates distinct cultural cognitions rather than universally positive effects. This study identified three spatial–cultural typologies: an authentic traditional revitalized area, where high visual entropy preserves authenticity but limits involvement; a high-quality hub, which utilizes high integration and connectivity to holistically enhance all cultural cognitions; and a functional and vital art area, where spatial control for modern vitality is maximized at the expense of historical identity. These findings demonstrate that morphological variables serve as active, quantifiable predictors of cultural impact, moving the discourse of space and culture from a metaphor to an empirical framework. This study provides actionable design strategies for balancing functional efficiency with historical preservation in sustainable urban (re)development. Full article

The tourism sector in the Sultanate of Oman is central to “Oman Vision 2040”, with a strategic focus of the government on its dynamic transformation. Coastal regions, vital to tourism, are affected by changes to the coastline due to flash floods, sea-water flooding, and erosion. Despite its implications for tourism and the economy, this topic remains relatively under-explored, especially as to use of Sentinel-1 satellite images. This study assesses water-level changes due to erosion in the urban coastal region of the Al-Batinah governorate via land cover classification. Using the Support Vector Machine (SVM) classification technique, the overall accuracy is found to be 97.7% and the Kappa coefficient value for the year 2018 is 1.0. Although, when using the Random Forest (RF) classification technique, the accuracy is nearly identical, there is varying precision for the water area. A critical observation is made, showing significant increase of the water area from 2.99% in the year 2017 to 12.36% in the year 2025, suggesting water encroachment. With fixed-effect and combined-effect size meta-analysis models, the confidence levels were identified as 95.0% and 0.37, respectively, indicating a consistent variation in water area that supports the outcomes of image classification. This study offers a valuable insight for policymakers as to managing coastal regions, along with providing assistance to vulnerable coastal communities. The study focuses on a particular governorate, given the satellite images, whereas a broader regional comparison would address the limitation of the generalizability of results. In the future, the research could integrate surveys from coastal communities and businesses for a comprehensive qualitative data perspective on the region’s tourism sector. Full article

New-quality productive forces provide an important conceptual lens for understanding how innovation-driven development, digital empowerment, and the green transition jointly support sustainable regional development. From a geographical perspective, this study develops a multidimensional evaluation system for new-quality productive forces based on the three elements of productive forces: laborers, means of labor, and objects of labor. Using panel data for 31 provincial-level administrative units in China from 2012 to 2022, we integrate the entropy weight method, standard deviation ellipse, exploratory spatiotemporal data analysis, the obstacle degree model, and the random forest model to examine the spatiotemporal evolution and influencing mechanisms of new-quality productive forces. The results show that: (1) China’s new-quality productive forces increased steadily during the study period, but their overall level remained relatively low and regional disparities continued to widen. Spatially, they exhibited a pronounced “high in the east and low in the west” pattern, with South China and East China maintaining leading positions and Guangdong and Jiangsu forming a dual-core growth structure. (2) The spatial center of gravity remained southeast of the Hu Huanyong Line, and its expansion direction was broadly parallel to this line, indicating a relatively stable spatial configuration. The ESTDA results further reveal significant positive spatial autocorrelation, strong temporal inertia, and marked path dependence in local spatial transitions. (3) High-tech talent supply, innovation and entrepreneurship vitality, and ecological governance capacity constitute the main internal bottlenecks constraining the development of new-quality productive forces. The analysis of external factors indicates that economic scale and population size are the primary predictors of NQPF development, whereas government intervention, openness, urbanization, and industrial structure exhibit varying degrees of nonlinearity and regional heterogeneity. These findings enrich the geographical interpretation of new-quality productive forces and provide empirical evidence for formulating differentiated regional innovation policies and productivity transformation strategies. Full article

Rapid urbanisation and climate change intensify heat, drought, wind exposure, and salinity risks in arid coastal cities, while simultaneously increasing dependence on trees for microclimate regulation and public-space quality. However, integrated evidence linking taxonomic concentration, spatial structure, tree dimensions, and current vitality remains scarce for Central Asian cities on the Caspian coast. This study characterised 13,951 trees across 10 green spaces in Aktau, Kazakhstan, belonging to 10 species, 10 genera, and 7 families, using a comprehensive inventory and an integrated taxonomic, spatial, and vitality framework. Stand density ranged from 27.1 to 510.3 trees ha⁻¹. Ailanthus altissima and Platycladus orientalis accounted for 42.74% and 23.13% of all trees, respectively, and together formed 65.87% of the inventory. Two species, two genera, and one family exceeded the indicative 10/20/30 diversification thresholds. The Shannon index ranged from 1.19 to 2.00, Pielou evenness from 0.52 to 0.87, and the share of the dominant species from 24.2% to 63.2%. Of all trees, 12,205 (87.48%) were classified as in good condition, but three sites accounted for 83.0% of all satisfactory or unsatisfactory trees. Maclura pomifera and Gleditsia triacanthos had the highest proportions of trees in good condition (96.3% and 94.2%), whereas Catalpa speciosa had the lowest (66.0%). The inventory, therefore, reveals a favourable current condition, but limited taxonomic redundancy and localised management hotspots. The findings provide a baseline for climate-resilient urban landscape planning based on gradual diversification, site-specific irrigation and soil management, control of invasive recruitment, and repeated monitoring of condition, growth, and mortality. Full article

Urban waterfronts are important components of urban blue-green infrastructure, supporting ecological functions and public activities. However, existing assessments often examine waterfronts from separate perspectives, limiting an integrated understanding of waterfront experience. Building upon existing research on waterfront environments, this study develops an integrated socio-ecological framework that incorporates multiple environmental and spatial attributes to assess the Public Experience of Waterfronts (PEW) across four dimensions: amenity, comfort, experiential diversity, and access equity. By applying this framework to river segments in central Shanghai, the study examines spatial variations in PEW and its spatial coordination with surrounding urban vitality within 15 min living circles. Results reveal clear differences across river groups and spatial locations. Large rivers generally exhibit higher PEW levels, while medium and small rivers show relatively lower performance. High PEW areas are mainly concentrated along major waterfront corridors, whereas urban vitality is stronger in inner urban areas and declines outward. The coordination between PEW and urban vitality follows similar spatial patterns, with large rivers showing higher coordination levels and smaller rivers more frequently experiencing spatial mismatches. These findings highlight the importance of integrated assessment of waterfront qualities and surrounding urban contexts, providing practical insights for differentiated waterfront planning and sustainable urban development. Full article

Digital street-view imagery delivers computationally enabled fine-grained quantitative perception of urban landscape, supporting the refined assessment of urban spatial quality, ecological livability, and socio-economic externalities for socio-environmental sustainability. Taking Shanghai as the research area and 500 m × 500 m grid cells as basic analytical units, this study adopts the Segformer machine learning segmentation algorithm to accurately extract visual features of urban green infrastructure from massive Baidu street-view images. Combined with visitor volume and real estate transaction data, this paper systematically explores vitality effects and sustainable economic compensation of Green View Index (GVI) via the spatial hedonic model. Multi-model comparison verifies that the double-logarithmic framework is optimal for street-view visual data. Two empirical models are constructed to eliminate multicollinearity and differentiate effects of integrated built environments and segmented visual elements. The results indicate that Shanghai’s vitality presents a polycentric agglomeration pattern, while GVI shows a scattered spatial distribution, with strong spatial correlation in urban cores and weak linkage in suburbs. GVI acts as a determinant of block vitality, outperforming land use diversity and commercial density. A 1% increase in the GVI improves block vitality by 6.21% in C gradient, with positive effects concentrated on outer-ring green belts and inhibitory impacts in remote suburbs. Multi-scale analysis from 500 m to 5000 m confirms green optimization brings stable residential premiums, generating sustainable economic compensation to offset urban renewal costs. This study proposes a digital-imagery-based paradigm for GVI benefit evaluation and provides empirical evidence for the planning of ecologically sustainable communities. Full article

Construction waste management (CWM) is vital for enhancing resource utilization, ecological civilization, and high-quality development. Technological innovation is the cornerstone of efficient CWM, driving waste reduction, reuse, and recycling practices. Understanding the relevance of CWM technological innovation across different regions is an important foundation for the scientific formulation of CWM policies and a key entry point for achieving a circular economy. This study employs patents to reflect CWM technological innovation, uses social network analysis (SNA) to explore its spatial network characteristics, and adopts a quadratic assignment procedure (QAP) to verify its influencing factors across Chinese provinces. Results demonstrate significant overall network characteristics in CWM technological innovation, though technological innovation in CWM exhibits low spatial correlation among provincial regions of China. The analysis reveals a pronounced polarization in the CWM innovation networks across Chinese provinces, demonstrating a distinct core–periphery structure. Although spatial clustering in China’s CWM technological innovation is evident, correlations mostly exist within blocks, indicating a need to enhance inter-block correlations. The greater the disparity in living standards and the smaller the differences in economic structure, educational development, and urban construction, the more likely provinces are to establish spatial associations, thereby increasing the probability of forming a spatial correlation network of CWM technological innovation. This study contributes to the growing literature on construction waste management by providing a spatial network perspective for understanding regional technological innovation and its driving mechanisms. The findings inform regional coordinated strategies for sustainable CWM practices. Full article

Against the background of China’s large-scale, fast-paced, and uniformly constructed urban renewal, Lingnan arcade buildings are confronted with unprecedented conservation challenges, a contextual feature that endows this research with unique academic value in the international arena. Drawn from the authors’ practical participation in a government-led arcade conservation project in Zhao’an, three pragmatic research gaps unaddressed by existing theories are identified. Through a systematic comparative analysis of conservation and sustainable renewal models, as well as specific adaptive reuse cases of arcade buildings in four representative Lingnan cities, Macao, Hong Kong, Guangzhou and Shantou, three targeted recommendations corresponding to the aforementioned dilemmas are proposed to inform future practices: 1. Arcade conservation practices should not be restricted to superficial facade restoration. Instead, a well-defined intervention framework shall be established prior to the implementation of any conservation works. 2. Sufficient emphasis shall be placed on the material and structural authenticity throughout the design and construction phase. 3. A sustainable long-term operation mechanism shall be formulated post restoration to facilitate the revival of the inherent vitality of arcade buildings. Full article

The sustainable regeneration of industrial heritage in cold regions is constrained by severe winter climates, pronounced seasonal shifts in behavior, and declining spatial vitality. However, existing studies have not sufficiently explained how cold-climate conditions reshape catalyst effects and regeneration performance in industrial heritage districts. This study proposes a digital shadow-enhanced and digital twin-enabled analytical framework for the sustainable regeneration of cold-region industrial heritage. Using the Youfang Street industrial heritage district in Harbin, China, as an exploratory case, the framework integrates multi-source data to construct a dynamic assessment system linking climatic constraints, spatial structure, and human activity patterns. The climate correction coefficient is further operationalized through normalized climatic variables, including air temperature, wind speed, snow-cover condition, and thermal-comfort indicators. The results indicate that winter conditions substantially weaken traditional catalyst mechanisms by reducing outdoor interaction, disrupting movement continuity, and increasing dependence on indoor transitional spaces. Simulation results further demonstrate that climate-responsive interventions, including enhanced indoor connectivity, mixed-use functional integration, and seasonal activity optimization, can improve regeneration performance and spatial resilience. The framework is presented as an exploratory single-case analytical model that requires further multi-city and multi-year validation. By combining digital shadow-supported simulation with sustainable urban regeneration theory, this study provides a transferable analytical framework and practical decision-support tool for industrial heritage revitalization in cold-region cities. Full article

The formation mechanisms of Urban Vitality have been constrained by the limitations of traditional linear driving hypotheses, and the fragmented analysis of subjective and objective factors. Integrating the explainable machine learning model XGBoost-SHAP with multi-source geospatial data, this study constructs a systematic analysis framework at the community scale, comprising 275 community units across five administrative districts in Changsha. It constructs a systematic analysis framework that unifies objective environmental conditions and subjective perceptions—a deliberate departure from the fragmented approaches dominant in previous vitality research. Through this objective-subjective integrated lens, it explores the spatial patterns, non-linear driving mechanisms, and variable interaction effects of Urban Vitality. The XGBoost model achieves a cross-validated R² of 0.794 and an RMSE of 0.031, ensuring interpretative reliability for exploring non-linear mechanisms. The results indicate that Urban Vitality exhibits a spatial pattern characterized by “high-value aggregation in the core, gradient decay in the periphery, and local fragmentation,” with a significant siphon effect observed in the core area. Partial Dependence Plot (PDP) analysis reveals that the impacts of variables on vitality can be categorized into four patterns: continuous upward, threshold leap, inverted U-shaped, and weak or sample-concentrated. Univariate dependence plots further delineates fine-grained threshold effects, including “threshold triggering, nterval suitability, high-value suppression, and co-occurrence signals.” Furthermore, bivariate interactions reveal four synergistic mechanisms: Building Density must match road network support; Functional Aggregation should synergize with locational value; transportation nodes must integrate with activity-support capacity; and Street View quality and human demand mutually regulate each other. The conclusion asserts that urban stock renewal must transcend the mindset of single-factor maximization and shift towards a precision governance approach of “threshold activation, synergistic matching, and zoning intervention,” thereby providing a quantitative decision-making basis for human-oriented, fine-grained urban regulation. Full article

As global urban development shifts towards stock upgrading and cultural tourism consumption, historic and cultural districts have become crucial spatial carriers for reshaping local identity and driving urban regeneration. Although the literature explores cultural value, current research remains limited to macro-scale assessments, leaving a gap in micro-scale, quantitative identification of spatial narrative capacity. To address this, the concept of ontological narrative is introduced, and a three-dimensional framework integrating physical space, functional formats, and historical events is constructed. Using event space as the unit of measurement, a mixed-methods approach combining spatial syntax, kernel density estimation, and the Analytic Hierarchy Process is applied to Chaozong Street in Changsha. The findings indicate that narrative intensity exhibits a spatial pattern of main-axis agglomeration and deep-alley attenuation. High-value nodes concentrate along primary streets with high accessibility. Conversely, narrative efficacy declines in branch alleys and functionally deficient zones. Furthermore, a four-quadrant diagnosis reveals widespread structural decoupling, such as high historical value paired with low vitality. This shows that historical assets require functional activation to become effective narratives. This research provides a precise analytical tool, grounded in node diagnosis, to counter homogenized urban renewal by fostering differentiated cultural expression. Full article

Decarbonising domestic heating stands as one of the primary climate challenges, positioning net-zero building technologies as the vital technical response. Wastewater source heat pumps (WWSHPs) serve as a thermally stable solution for household heating. Scaling this system up to an urban network level requires balancing maximum heat extraction against the risks of biological damage to downstream treatment systems from excessive temperature drops. To resolve it, this study couples a quasi-steady-state model, driven by dynamic, 30 min time-series inputs, with a Genetic Algorithm (GA) to optimise a 41-pipe sewer network in Belgium. Significant results demonstrate that the GA configuration enhanced potential heat recovery by 51.7% relative to unoptimised baselines, elevating yields from 29 MW to 44 MW. Furthermore, this research identified a mass compensation effect in winter that effectively counterbalanced seasonal drops in wastewater temperature, resulting in nearly identical winter and summer average heat recovery capacities (17.409 MW vs. 17.492 MW, a variance under 0.5%). From these findings, it can be concluded that while network-scale thermal potential is exceptionally robust year-round, a profound seasonal mismatch exists between available supply and localised consumer heating requirements, which drop to a minimum of 712 kW in July but exceed 51 MW in winter. Full article

The King Abdulaziz Public Transport Project in Riyadh is one of the massive undertakings that could transform mobility and quality of life in the Saudi capital. However, a full grasp of its many-sided consequences is still hard to obtain. The project is expected to deliver several positive outcomes, including decreased traffic congestion and better air quality, as well as increased mobility; however, it remains vital that the impact of this development on different aspects of urban life is studied using modern spatial analysis methods. This research seeks to address this gap by delving into the project’s influence on land use patterns, transportation behaviors, economic development, urban growth, environmental conditions, population dynamics, and road network efficiency. Using these techniques, some of the achievements and struggles of the project are identified in terms of service coverage, travel times, and how well it fits within Riyadh’s sustainability objectives to reduce car dependency and increase ridesharing. In conclusion, the study aims to contribute knowledge that supports urban planning, policy formulation, and future infrastructure projects so that the King Abdulaziz Public Transport Project is better aligned with the needs of this growing city for a workable, sustainable Riyadh. The King Abdulaziz Public Transport Project is a significant step towards improving Riyadh’s transportation system and achieving environmental, economic, and social sustainability goals. It will contribute to alleviating traffic congestion, improving air quality, boosting economic growth, and enhancing the quality of life for residents. Sustainable landuse planning around the stations, with the allocation of green spaces and public facilities, is essential. Full article

Urban greenbelts are vital for biodiversity and ecosystem services but face threats from urban expansion. This study assessed the population structure and identified potential threats to woody plants in Arusha city’s greenbelts (nature areas and riparian forests). Woody plants were sampled across 53 grid cells (200 m × 200 m) using stratified random sampling and the Braun-Blanquet relief method. Remote sensing processed 2015 and 2022 satellite images. ArcGIS 10.8.2 software facilitated field data collection coordinates, the satellite imageries and spatial analyses. Standard plot sizes of 400 m² were systematically selected for data collection. Significant differences in tree species diversity and abundance were observed within nature areas (t = 18.6, p = 0.001; t = 5.48, p = 0.001) and riparian forests (t = 21.4, p = 0.001; t = 13.8, p = 0.001). No significant differences were found between eastern and western nature areas (t = 1.06, p = 0.338; t = −1.55, p = 0.181) while within riparian forests, only species diversity differed significantly (t = 2.66, p = 0.011). However, tree species abundance differed significantly between nature areas and riparian forests (t = −2.97, p = 0.01) with riparian forests having higher abundance of native trees compared to nature areas and with significant abundance of native trees compared to non-native trees (t = 14, p = 0.001). These findings emphasize the conservation of Arusha’s greenbelts, aligning with SDGs 3 (well-being), 6 (water quality), 11 (sustainable cities) and 15 (ecosystem conservation). Full article

Resource-exhausted cities face intertwined economic, social, and ecological pressures during transition, yet the dynamic evolution and pathway-specific responses of their socio-ecological resilience remain insufficiently understood. Using Jiaozuo, China, a nationally designated resource-exhausted coal-mining city, this study develops an interpretable-machine-learning framework that integrates resilience assessment, XGBoost-SHAP interpretation, spatial statistical validation, scenario simulation, and sensitivity analysis. A multidimensional resilience index was constructed for 2012–2022, and alternative development pathways were projected for 2030 and 2035. The results reveal stage-dependent resilience evolution, with model-explained drivers shifting from economy- and policy-related factors in 2012–2017 to a more ecology-oriented and multidimensional structure in 2017–2022. SHAP dependence and interaction analyses further identify nonlinear response patterns and conditional interactions among key social, economic, and ecological indicators. Scenario simulations show that green transformation produces the strongest model-predicted gains and remains the highest-ranked pathway under alternative subsystem-weighting schemes. These findings suggest that resilience enhancement in resource-exhausted cities depends on coordinated ecological restoration, industrial upgrading, economic vitality, and social adaptive capacity. The proposed framework provides a transferable approach for diagnosing resilience evolution and comparing transition pathways in resource-exhausted urban systems. Full article