Search Results (2,133)

Amid rapid urbanisation and the associated environmental challenges, such as increased flood risk, the urban heat island effect, and ecosystem degradation, Blue–Green Infrastructure (BGI) has emerged as a vital sustainable development strategy. Some countries have successfully implemented BGI projects, shaped by their unique geographical conditions, socioeconomic contexts, and governance structures. Although the BGI concept is highly relevant worldwide, strategies for integrating BGI into urban environments vary significantly across regions and countries due to their distinct urban structures and spatial planning systems. This study provides a comparative study of BGI implementation into spatial planning systems of Ljubljana (Slovenia) and Kraków (Poland), as Central European cities, and Shanghai and Guangzhou, as Chinese cities. Through a systematic analysis of semi-structured interviews with key stakeholders, the study evaluates how different enablers, i.e., (1) guidelines, strategies, and actions, (2) land-use strategy for BGI, and (3) potential of factors for BGI implementation, including planning scale, financial, technical, and spatial, facilitate BGI implementation. This comparative study reveals contrasting yet complementary BGI paradigms, most notably related to top-down versus bottom-up implementation and different prioritisation of BGI functions. These varying paradigms are shaped by specific urban challenges, governance, and spatial planning systems. Full article

Preservation and revitalization of historic districts are critical for quality urban development and renewal. Accurately assessing what drives district vitality is essential for sustainable historic area development. Current research often uses cross-sectional data and single models, limiting understanding. This study uses Xigong District, Luoyang, and integrates multi-source data—street view imagery, points of interest, road networks, and nighttime lighting—from 2014 to 2021. MGWR and XGBoost models create a dynamic framework for analyzing how the built environment affects street vitality over time. Results: (1) Spatial effects: Physically, green exposure, functional mix, and road network access are highly spatially sensitive. Morphological indicators—commercial frontage, street continuity, complexity, and building texture—show reduced local variation over time. Perceptually, the influence of abstract color narrows each year, and subjective preference broadens. (2) Nonlinear effects: Green exposure and openness dominate but show negative inhibition and diminishing returns. Morphological, functional, and road network indicators have moderate explanatory power with clear thresholds. Perceptual importance shifts from abstract color to architectural texture, which now rises while color influence steadies. Renewal should go beyond basic greening and surface color. Instead, focus on refined, threshold-based control of form and function, and preserve authentic historic texture. This approach enables scientific, sustainable vitality. Full article

Free-floating bike-sharing (FFBS) systems play a valuable role in alleviating traffic congestion and reducing carbon emissions, making them vital to sustainable urban transportation. Although extensive research has investigated the relationship between the built environment and cycling behavior, the adverse effects of air pollution and its interaction with the built environment remain insufficiently understood. In this study, multisource data from Shenzhen are used, and an XGBoost–SHAP model is employed to comprehensively investigate the nonlinear associations among the FFBS trip volume, built environment, and air pollution while considering the spatial heterogeneity in interaction effects. The results indicate that population density, road density, building density, and PM2.5 are the most influential factors. In addition, significant temporal heterogeneity is observed between weekdays and weekends. The effects of the built environment variables and their interactions are more pronounced on weekdays than on weekends. More importantly, an interaction analysis reveals that the positive influence of compact urban development on cycling is conditional: in high-density areas with elevated pollution exposure, the health risks associated with air pollution can offset or even outweigh the mobility benefits of compactness. Overall, this study identifies the complex, spatially heterogeneous mechanisms through which the built environment and air quality jointly shape FFBS usage. These findings provide important evidence for integrating environmental health considerations into compact city planning and offer practical insights for promoting cycling and sustainable urban mobility in high-density cities. Full article

Robust tsunami casualty estimation is vital for Peru’s central coast. While static maps ignore evacuation dynamics, precise agent-based models (ABMs) are often too computationally demanding for rapid screening. To bridge this gap, we propose an efficient geospatial workflow coupling TUNAMI-N2 simulations with shortest-path routing. Evaluating four subduction scenarios across Chorrillos and Villa El Salvador, the model tracks census-block evacuation progress. By intersecting evacuation trajectories with tsunami arrival times, casualties are calculated using empirical depth-dependent fragility functions. Results highlight that delayed reaction times significantly increase mortality. Furthermore, a counterintuitive dynamic emerges in spatially constrained corridors lacking vertical evacuation: higher walking speeds can paradoxically increase fatalities by advancing evacuees into deeper inundation zones before being overtaken. This highlights that behavioral preparedness must be coupled with structural urban interventions. Ultimately, our scalable approach enables DRR (Disaster Risk Reduction) managers to rapidly map mortality hotspots and prioritize critical infrastructure improvements in highly exposed coastal zones. Full article

Perceived street vitality directly reflects residents’ assessments of the attractiveness of the street environment; it is not only an important focus of urban vitality research but also closely related to human-centred sustainable urban development. However, limited data availability and the complexity of urban environments have constrained fine-grained spatial analysis at the city scale. To address this issue, this study quantified perceived street vitality by collecting street-view imagery, extracting streetscape features, and integrating these data with questionnaire survey results. After comparing multiple models, a geographically weighted machine learning model was employed to identify key visual predictors, model-estimated marginal associations, interaction patterns, and spatial heterogeneity related to perceived street vitality. The results show that areas with high perceived street vitality are mainly located along street segments with abundant greenery and open spaces, whereas low-value areas are concentrated in densely built and enclosed environments. Among the various streetscape elements, buildings, vegetation, and sky are the key visual elements most strongly associated with perceived street vitality. A model incorporating these elements accounted for 67.2% of the variance in perceived street vitality. Notably, the strength of these associations varied significantly across different areas. This study provides empirical evidence and evidence-based support for sustainable urban renewal, the optimisation of street-space layouts in high-density urban areas, and the improvement in street environmental quality. Full article

Rapid urbanization has intensified the need for vibrant, walkable, and socially sustainable urban environments, particularly within mixed-use and commercial districts. The way buildings and streets are spatially configured in these districts plays a critical role in shaping pedestrian movement, spatial accessibility, commercial vitality, and social interaction within these environments. This paper investigates the role of spatial configuration in shaping the resilience and sustainability of urban commercial districts through a comprehensive review of recent space syntax applications. The review synthesizes methodological approaches for examining spatial structures, urban morphology, spatial accessibility, and urban activity patterns, including segment-based spatial analysis, visibility graph analysis, agent-based modeling, and predictive spatial simulation. This study consolidates recent methodological developments in spatial analytics and identifies key analytical trends that clarify how spatial configuration contributes to urban vitality and sustainability in commercial districts. Particular attention is given to the methodological evolution of space syntax research and its increasing integration with complementary datasets and analytical frameworks for evaluating urban vitality. Across the reviewed studies, highly integrated and spatially accessible street networks were consistently associated with higher pedestrian flow, greater commercial density, stronger land-use clustering, and improved walkability, particularly within compact, mixed-use urban districts. Movement-based metrics such as integration and Normalized Angular Choice (NACH) repeatedly emerged as dominant predictors of pedestrian movement, land-use intensity, and commercial concentration. Despite significant methodological advances in spatial analysis, a persistent gap remains in linking configurational metrics with lived human experience and broader social sustainability outcomes. Overall, the findings demonstrate that spatial configuration is a fundamental driver of walkability, commercial vitality, and socio-spatial interaction, reinforcing the growing role of space syntax as a framework for evidence-based and sustainable urban design. Full article

Lake Villarrica, located in southern Chile, is a vital freshwater resource whose ecological status requires continuous evaluation. Chlorophyll-a (Chl-a) is a key indicator of phytoplankton biomass and estimating it using satellite sensors enables efficient and large-scale monitoring. This study compared the performance of different empirical models based on reflectance data obtained from atmospherically corrected satellite images using ACOLITE software (Generic Version 20231023.0), calibrated with in situ measurements of Chl-a collected during the spring and summer seasons between 2014 and 2024. For each sensor, the best combination of spectral bands was selected, and retrieval models were generated using a bootstrapping procedure with 1000 iterations to obtain robust regression coefficients; the final models were defined using the median of these coefficients. The top-performing model for Landsat-8 and 9 was based on a blue-red band combination (R² = 0.79, RMSE = 2.1 µg·L⁻¹, MAE = 1.2 µg·L⁻¹, n = 74). In contrast, the optimal model for Sentinel-2A utilized green and blue bands, yielding higher precision (R² = 0.75, RMSE = 0.8 µg·L⁻¹, MAE = 0.72 µg·L⁻¹, n = 112). In general, the results obtained through remote sensing reveal a gradual increase in Chl-a levels over the last decade, reflected in recurrent summer biomass increases primarily along the shoreline near the urban area of Pucón and in the vicinity of the Pucón River inflow into Lake Villarrica. These results support the development of an operational satellite-based monitoring framework for inland lake water quality assessment. Full article

Heritage-led urban redevelopment is increasingly adopted to advance cultural continuity and social vitality; however, its long-term sustainability is often compromised due to the absence of user-oriented assessment methods. Conventional Post-Occupancy Evaluation (POE) approaches are limited in their ability to capture experiential, social, and participatory dimensions of architectural and urban spaces. This study examines the potential of Virtual Reality (VR) as a participatory POE tool for sustainable heritage redevelopment through the case study of Souq Al Muharraq in Bahrain. A convergent mixed-method approach is employed, integrating immersive VR 360-degree walkthroughs, structured questionnaires, qualitative semi-structured interviews, and expert evaluation. The findings reveal significant discrepancies between design intentions and lived experience, specifically in thermal comfort, circulation, social usability, and informal spatial practices. The study demonstrates that VR supports a user-centered and experiential approach aligned with Sustainable Development Goals (SDGs) 9, 11, and 16. It further proposes a sustainable and cost-efficient framework for architecture and urban projects’ evaluation by enabling early and post-user-centered evaluation of projects to reduce costly revisions and the creation of inclusive, adaptive, and resilient architecture and urban spaces. Full article

As urbanization picks up pace and the public demand for security keeps climbing, video surveillance systems have emerged as a vital tool for maintaining social stability and safeguarding public safety. Person Re-Identification (Re-ID), as one of the core technologies in intelligent monitoring, mainly aims to accurately match pedestrian identities across cameras without overlapping fields of view. However, in practical applications, occlusion remains a primary challenge that severely degrades Re-ID performance. Especially in high-density crowds, pedestrians are often partially or completely obscured by other objects or individuals, resulting in incomplete image information and impaired feature representation, which significantly reduces recognition accuracy and reliability. Aiming at the problems of excessive reliance on external pose estimation models and asymmetric information matching in occluded Re-ID, this paper proposes a transformer-based pedestrian background decoupling network. The algorithm achieves foreground–background separation and multi-scale feature matching through the synergy of three modules. Meanwhile, a two-stage training strategy is adopted: the first stage optimizes the decoupling module to ensure clean feature separation, while the second stage jointly fine-tunes the correlation module to enhance matching accuracy. Extensive experimental results show that the proposed algorithm outperforms existing methods. Full article

Traffic assignment is crucial for urban traffic regulation and management. Based on this background, this study proposes a heterogeneous graph neural network that integrates Transformer-based multi-head self-attention for traffic assignment in urban road networks. The model builds a heterogeneous graph with both physical road links and virtual origin–destination links. It features a dual-encoder structure: the V-Encoder and the R-Encoder. The V-Encoder employs Transformer multi-head self-attention to capture long-range spatial relationships between origin and destination nodes. In contrast, the R-Encoder aggregates local topological features to characterize the transmission of flow across road segments. A combined loss function that includes flow conservation constraints is designed to ensure predictions are both accurate and physically realistic. Experiments on the Sioux Falls and EMA networks demonstrate that the method outperforms baseline models under various congestion conditions, exhibiting high accuracy and efficiency. Ablation tests show that Transformer multi-head self-attention is vital for performance enhancement. The approach also remains robust under abnormal conditions, such as in the case of incomplete OD demands, making it a practical solution for efficient, low-carbon, and sustainable traffic management. Full article

The rapid expansion of e-commerce has transformed market access in developing economies, yet its impact on the spatial structure of market participation remains insufficiently understood. While existing studies primarily examine welfare outcomes such as income growth and consumption smoothing, few investigate how digital platforms reshape the balance of market entry between urban and rural areas. Drawing on New Economic Geography and platform economics theory, this study proposes that e-commerce development rebalances urban–rural market vitality through three associative pathways: alleviating rural capital constraints, improving rural innovation environments, and promoting agricultural-industry agglomeration. Using county-level panel data covering 2725 Chinese counties from 2011 to 2022, we employ a Double Machine Learning (DML) framework to examine the association between designation as an “E-commerce into Rural Comprehensive Demonstration County” and changes in the urban–rural market vitality balance (URMAR). The results indicate that demonstration county designation is associated with a statistically significant reduction in urban–rural market disparity, as measured by both the Theil index and the absolute difference in new enterprise registrations. The directional URMAR indicator further reveals that this convergence is driven primarily by accelerated rural enterprise formation. Subsample analysis confirms that the rebalancing interpretation holds across counties with different baseline market structures. Mechanism analysis provides suggestive evidence consistent with all three proposed associative pathways. Heterogeneity analysis further reveals that these effects are stronger in economically developed eastern regions, in counties linked to higher-tier cities, and in secondary and tertiary industries. These findings advance a market-structure perspective on digital development that complements existing welfare-based approaches and offer policy insights for fostering balanced regional development through targeted digital and complementary investments. Full article

While multilane roundabouts follow geometric design standards, they often overlook motorcycle-dominated traffic behavior. This study evaluates lane-reduction strategies to create safer and more inclusive urban corridors in mixed-traffic conditions, focusing on a case study in Southern Thailand. High-resolution unmanned aerial vehicle (UAV) trajectory data were analyzed using the Macroscopic Fundamental Diagram (MFD), Cell Transmission Model (CTM), and Time-To-Collision (TTC) frameworks under three configurations: full lane availability, partial inner-lane closure, and full inner-lane closure. Results indicate progressive deterioration in performance under restricted-lane conditions. Under full closure, total flow decreased by 31%, and average travel time increased by 43%. The MFD curve shifted toward higher critical densities, indicating earlier congestion onset, while CTM results revealed longer discharge times, queue spillback, and increased merging friction. Conversely, safety outcomes (TTC) improved significantly: extreme rear-end conflicts were reduced by 48%, and severe lane-change conflicts were nearly eliminated (99%). Behavioral evidence suggests that full closure constrains motorcycles to a single circulating path, reducing erratic filtering and promoting more stable interactions. Overall, this study identifies a systemic trade-off between safety and efficiency, highlighting how geometric interventions catalyze behavioral adaptation. The findings highlight how geometric constraints shape collective behavior in motorcycle-dominated roundabouts and demonstrate the value of an integrated UAV-based framework as a vital tool for inclusive urban management, providing the granular data needed to balance safety and mobility in complex traffic landscapes. Full article

Precise assessment of commercial service facilities (CSFs) is a vital pillar for megacity governance. However, existing evaluations rely on static population and 2D metrics, overlooking behavioral heterogeneity and 3D spatial supply at the micro scale. This study constructs a “3D Supply–Group Demand–Matching” framework at the community level. On the supply side, a Building Coupling Entropy (BCE) model integrates 3D volume and morphology to characterize service capacity. On the demand side, a dynamic behavioral model measures multi-group needs. Mismatch patterns are identified using the Entropy-modified Spatial Disparity Ratio (ESDR). Using Guangzhou as a case, the results reveal three paradigms: (1) Core districts exhibit rigid path dependency, where first-tier sub-districts rose from 48 to 51, and elderly service shortages in old areas plummeted by nearly 80% via micro-regeneration; (2) Growth poles show spatial fragmentation, with core labor demand spilling over but infrastructure lagging, creating a fast production–slow urbanism mismatch; (3) Far-suburban areas reduced extreme-shortage sub-districts from 38 to 34, identifying resource islands besieged by residential demand. Overall, the framework elucidates the shape–flow mismatch mechanism and provides a transferable basis for precision zonation governance, supporting a shift from static quantity-based allocation to dynamic quality-oriented provision in high-density megacities. Full article

Fine-scale urban underground exploration is vital for geological safety and hydrogeological protection. In spring-rich cities like Jinan, shallow structures—such as sedimentary layers and fault systems—act as critical regulators of groundwater migration and spring formation. Yet, traditional seismic methods are often hindered by high costs and complexity. While Distributed Acoustic Sensing (DAS) offers a solution, its effectiveness is frequently limited by the poor coupling and coherent signal loss of existing cables in pipes. This study proposes an efficient alternative using mobile, unburied surface fiber-optic cables. Ten temporary DAS experiments were conducted along a 23 km line in Jinan, accompanied by nodal seismometers. Stable dispersion curves along the line can be extracted by subarray ambient noise interferometry with short-duration urban traffic noise DAS recording, and finally a high-resolution 2D S-wave velocity profile was mapped. The result shows that the profile has pronounced subsurface lateral heterogeneity, characterized by the alternation between two uplift zones and two grabens, which is highly consistent with H/V results from nodal seismometers. This confirms that mobile surface-cable DAS provides a rapid, reliable, and cost-effective imaging solution for characterizing complex urban subsurface structures, providing essential data for both geohazard assessment and the protection of groundwater transport pathways. Full article

As the inner driving factor of space vitality, environmental perception can be expressed in many ways. Given the current lack of in-depth research on related perceptions, the study integrated theoretical origin and empirical study methods to clarify the role that preference played as the common foundation of different expression ways of environmental perception. The study also explored the interaction mechanism of different preference expression ways in the “quality-to-vitality” pathway and significant environmental characteristics of them, so as to realize the transformation from landscape design to urban vitality. Key findings indicate that: (1) Three environmental preference expressions—emotion, satisfaction, and behavioral preference—collectively lend credence to a significant chain mediation pathway (“emotion → satisfaction → behavioral preference”) in the quality-to-vitality process; (2) Pedestrian safety infrastructure (e.g., traffic barricades, well-maintained pavements) could ensure perceived security and walking activities; (3) Cultural/recreational facilities mean complementary legibility-enhancing elements (appropriate spatial enclosure, pleasant color schemes, architectural coherence) to evoke positive affect; (4) Streetscape diversity and visual interest might mitigate monotony induced by excessive block length, serving as vital vitality catalysts in some degree. Full article