Search Results (18,666)

Due to rapid urbanization, climate and socio-economic change, vernacular architecture in the Kara region of Togo is now facing mutations that threaten its existence. In the Kara region, new forms of housing, inspired by ancestral building practices and green technologies, are emerging as neo-vernacular architecture. This study aims to evaluate the overall performance of the CIDAP social hall, which is considered a model of neo-vernacular architecture. Through a series of both qualitative and quantitative tools, including the VerSus tool, the PTVA method and the calculation of the temperature difference ratio (TDR), the CIDAP social hall was analyzed regarding the criteria of durability, vulnerability to climatic hazards and thermal comfort. This work indicates that this building achieves a sustainability score of 88.33%. In terms of vulnerability to climatic hazards, the vulnerability index is around 0.392 for heavy rainfall, 0.389 for high heat and 0.309 for strong wind hazard. For thermal behavior, the TDR is of the order of 0.634. All these results reveal a satisfactory performance of the CIDAP social hall in terms of durability, vulnerability and thermal comfort. Full article

Heterogeneous airground robotic systems, which integrate unmanned ground vehicles and unmanned aerial vehicles, have shown significant potential in complex autonomous missions. However, when deployed in urban canyons, dense high-rise buildings impose severe communication constraints on ground vehicles, necessitating the introduction of aerial vehicles as relays to maintain reliable connectivity. The resulting cooperative trajectory planning problem is challenging for three reasons. First, the kinematic and communication constraints are tightly coupled. Second, the optimization landscape is highly non-convex and non-differentiable. Third, the planner must balance topological exploration with real-time efficiency. To address these challenges, we propose a hierarchical cooperative trajectory planning framework for an air–ground robotic system. Specifically, in the upper layer, a heuristic-search-guided reinforcement learning mechanism is employed to narrow the search space and circumvent the sparse reward problem, rapidly generating an initial solution. Subsequently, the lower-layer planner utilizes an optimization-based solver, together with a corridor-based constraint formulation method, to refine the initial solution into a kinematically feasible cooperative trajectory. Ultimately, this strategy improves real-time efficiency while improving the quality of feasible cooperative trajectories. Extensive ablation studies and comparative experiments with representative baselines demonstrate that the proposed framework improves collision avoidance, communication reliability, trajectory smoothness, and computational efficiency in the tested urban canyon scenarios. Full article

Over the past three decades, geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) have become essential tools for spatial analysis in urban, environmental, and land-use research. This scoping review systematically maps and synthesizes the global literature on GWR and MGWR published between 1996 and 2026, aiming to identify the research hotspots, evolutionary paths, and cutting-edge trends. Bibliometrics and CiteSpace visualization tools are used to conduct a multi-dimensional visual analysis of thousands of selected articles, including countries, institutions, core authors, highly cited keywords, and key documents. The results show that the current research focuses on spatial heterogeneity, multiscale analysis, GWR model optimization, non-stationarity characterization, and simulation of urban land-use change. Potential future directions include the construction of spatiotemporal integrated models, the integration of high-performance computing, and the expansion of interdisciplinary applications. The results of this study can help scholars fully understand the current research status and future directions, and provide a scientific spatial analysis framework for practitioners in urban planning, land resource management, and environmental assessment. Furthermore, the conclusions can provide theoretical support and a decision-making basis for the government to formulate intelligent and refined urban development policies. Full article

The application of traffic-calming measures (TCMs) constitutes an important preventive approach that improves road safety, particularly for vulnerable road users in urban environments. Due to economic considerations, the most commonly implemented measures are road humps (including speed humps, speed tables, and speed cushions), which significantly influence driver behaviour and contribute to speed reduction. Previous studies have demonstrated their considerable effectiveness; however, they remain limited and do not fully address certain important aspects, such as the relationship between speed reduction and the distance from a road hump, or operating speed as a function of road hump type while accounting for the influence of other contextual variables. This study considers three types of road humps installed on streets with a speed limit of 30 km/h in the city of Szczecin, Poland. To complement existing research, vehicle speeds were recorded using multiple speed measurement devices deployed along the analysed street sections. The placement of these devices on short street sections accounted for the influence of the following factors: street type, the presence of protective bollards, different parking conditions and arrangements near the analysed road humps, and their location relative to junctions. To ensure consistency and comparability of the analyses, each type of road hump was examined on the same street. Standard statistical analyses were performed for all speed datasets, with speed treated as the dependent variable and the aforementioned factors as independent variables. These analyses enabled the estimation of operating speed and the zone of influence for the three types of road humps, considering various determinants. The results indicate that vehicle speed is strongly dependent on the distance from a given road hump, its location within a street section between junctions, and the parking conditions in its vicinity. The outcome of this research is the development of a comparative framework for different types of road humps, with their corresponding operating speeds and zones of influence under specific contextual data. It may serve as a basis for design decision-making when planning road humps on short sections of residential streets (up to 250 m between junctions) located in suburban areas. The framework should be further supplemented and updated by other researchers as new empirical evidence and research experience become available. Full article

This case study aimed to benchmark the healthiness, equity, and environmental sustainability of a large, urban Australian university food environment through two audits conducted in 2022 and 2025. Two cross-sectional audits were completed at a large urban university campus using the Uni-Food tool, which assesses 68 best practice indicators across three components: policy, campus facilities, and food retail outlets. Four assessors independently conducted the audits with excellent inter-rater reliability (Cohen’s Kappa = 0.89). Final scores out of 100 were calculated using weighted domains. Descriptive and inferential statistics were used to compare changes over time. In 2025, the university achieved a score of 52%, up from 48% in 2022, indicating medium compliance with best practice standards. Findings highlight that scores differed modestly but there were persistent gaps in university food policy and practice. Specifically, the policy component remained low (48%), demonstrating strong overall planning but a lack in food retail policy and monitoring systems. The campus component scored moderately (63%), with various nutrition knowledge-building opportunities and environmental sustainability initiatives available but heavy promotion of unhealthy foods at campus events. The food retail component scored lowest overall (36%), especially as there was a lack of adequate nutrition information provided at food outlets. Continued investment in policy development, campus-wide strategies, and food retail innovation is essential to create healthier, more equitable, and environmentally sustainable food environments in tertiary settings. Full article

Decoration waste, because of its complex composition and the presence of volatile toxic and hazardous substances, has always been a difficult point in the management of urban construction waste. And with the continuous expansion of the town scale, the volume of decoration waste is gradually expanding, which constitutes a major challenge to the sustainable development of the construction industry. In order to solve this difficult problem, this paper took Henan Province as an example, and realized the accurate control of decoration waste based on GF-2 remote sensing images and a BP neural network model. The results of GF-2 remote sensing image interpretation and analysis showed that the spatial distribution of construction waste in the study area was extracted through a combination of manual visual interpretation and machine learning recognition, and as of 2021, the construction waste pile occupied a large proportion of the land area, of which the proportion of decoration waste was about 10%. Based on the trained BP neural network, the goodness-of-fit result was R = 0.95463. Selecting the research data from 2010 to 2021, the error of the predicted annual generation of decoration waste in Henan Province compared with the actual value was less than 15%, which had a high prediction accuracy. Based on the arithmetic sum of the projected figures for each year from 2022 to 2030, it is estimated that by 2030, the cumulative volume of construction and renovation waste generated in Henan Province will reach 49,827,200 tons. Visualization of spatial and temporal distribution characteristics was realized through ArcGIS, and the high production area of decoration waste was distributed from the beginning to the end of the distribution of multi-points to show the characteristics of a concentrated large area distribution, centrally located in southwestern and southeastern Henan Province, with the key cities of Zhumadian City, Luoyang City, Zhoukou City, and Xinyang City, which had obvious regional characteristics. At the same time, as the provincial capital, Zhengzhou has long ranked first in the province in terms of absolute case numbers and is therefore also a key focus of control measures. Uncertainty analysis indicates that the 95% confidence interval for the long-term forecast values is approximately ±12%. It is recommended to use the upper limit of this interval for the redundancy design of the absorption facilities to enhance the robustness of the decision. This study provides a theoretical basis and technical support for the governmental supervision of decoration waste during the development of national urban agglomerations, effectively solves regional urban planning and construction management problems, and promotes the sustainable development of the construction industry. Full article

This paper examines the evolution of urban transport policy in Saudi Arabia from a car-dependent paradigm toward sustainability-oriented planning and early implementation between 2000 and 2025. Using a longitudinal qualitative analysis of national strategies, municipal plans, and giga-project documents, this study traces shifts in policy discourse, governance arrangements, and delivery evidence across three phases: an expansionist phase (2000–2015), a vision transition phase (2016–2020), and a sustainability implementation phase (2021–2025). These phases were selected to capture the transition from pre-Vision 2030 automobile-oriented planning to the early implementation of sustainability-oriented transportation reforms. The findings reveal a clear transition from road-expansion-oriented planning—characterized by highway development, fuel subsidies, and limited public transport—toward system performance, decarbonization, and multimodal integration. Recent years have seen the rollout of metro and bus networks, expansion of rail systems, early electrification of vehicles and public transport, and fuel price rationalization. However, persistent behavioral lock-in, low-density urban forms, climatic constraints, and complex multi-level governance arrangements continue to limit modal shift and equitable mobility outcomes. The findings suggest that infrastructure investment alone cannot achieve substantial modal shift without integrated land-use planning, feeder systems, and demand-management measures. By linking policy ambition to implementation pathways over time, this study provides transferable insights for sustainable mobility transitions in oil-dependent and arid urban contexts. Full article

Urban regeneration processes are increasingly intertwined with participatory practices aimed at integrating local knowledge and civic engagement into design and planning decisions. However, public participation often fails to influence decision-making meaningfully or to anticipate the unintended consequences of proposed interventions. This paper presents a methodological framework developed during a participatory process for the restoration of Piazza Umberto I, a historic urban square in Bari, Southern Italy. The process was structured around seven online workshops held between March and May 2021, involving 45 registered participants and an average attendance of about 30 participants per session, including residents, civic associations, students, professionals, economic actors, and municipal representatives. Through a sequential funnel—problems, opportunities, visions, solutions, methodological principles, validation, and proposal—the process elicited and organized participants’ knowledge across five analytical domains and eight long-term vision categories: History, Nature, Education, Culture, Economy, Society, Experience, and Democracy. The validated workshop outputs were then translated into a fuzzy cognitive map and explored through cross-impact analysis to identify intended impacts, unintended effects, leverage points, and trade-offs among proposed solutions. Link weights were assigned through a semi-quantitative scale representing the direction and relative strength of influence, and a ±20% sensitivity analysis was conducted to test the robustness of the main ranking patterns. The results show that some proposals, such as ecological restoration, public art programming, and cultural or educational activation, operate as broad-spectrum leverage points, while others generate more selective effects or latent tensions, particularly between ecological preservation, economic activation, accessibility, and civic use. This paper does not propose a predictive or statistically inferential model; rather, it demonstrates how participatory knowledge can be operationalized into a transparent, exploratory, and semi-quantitative decision-support framework. By linking deliberation with systems-oriented reasoning, the study contributes to urban planning debates on participatory governance, anticipatory decision-making, and the management of unintended consequences in public-space regeneration. Full article

This study examines how institutional pressures influence the adoption of social sustainability practices in habitat systems within the construction sector. Drawing on Institutional Theory, the research analyzes the differentiated effects of coercive, mimetic, and normative pressures, as well as the mediating role of organizational awareness. Data were collected through a digital survey administered between February and March 2026 to 102 professionals linked to construction and habitat development projects in Mexico, including architects, civil engineers, valuators, and related specialists. The proposed model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that coercive pressures constitute the only statistically significant institutional mechanism affecting organizational awareness ($\beta$ = 0.310; p = 0.043), while mimetic and normative pressures do not exhibit significant effects. Furthermore, organizational awareness strongly explains the adoption of social sustainability practices ($\beta$ = 0.739; p < 0.001), which, in turn, is strongly associated with sustainable habitat outcomes ($\beta$ = 0.711; p < 0.001). The model achieved moderate predictive power, with $R^2$ values of 0.449 for awareness, 0.546 for adoption, and 0.505 for sustainable habitat systems. The findings contribute to institutional theory by demonstrating that institutional mechanisms operate asymmetrically in emerging contexts and that organizational awareness functions as a key explanatory mechanism linking external pressures with sustainability outcomes. The study also provides practical implications for urban governance, regulatory design, and socially sustainable habitat planning. Full article

Traffic noise adversely affects residents near expressways, calling for sustainable noise mitigation solutions. This study developed three eco-friendly sound-absorbing panels from sand, industrial slag, and microporous ceramics. By optimizing aggregate gradation, the influence of porosity and flow resistivity on absorption coefficients was analyzed to determine optimal mix ratios. The panels were integrated into perforated metal noise barriers and evaluated through reverberation room and sound insulation tests. Field simulations using SoundPLAN for a residential project in Taizhou validated real-world performance. Results showed that slag panels achieved a Noise Reduction Coefficient (NRC) of 0.70, while sand and ceramic panels both reached 0.55. All configurations maintained a weighted sound reduction index (R_w) of 25–26 dB. Empirical simulations confirmed that a 2.5 m high barrier keeps noise levels within the 60 dB limit. Compared with traditional glass wool, these inorganic panels offer comparable noise reduction, superior non-combustibility, and better weather resistance, making them effective for frequency-specific noise control in urban engineering applications. Full article

Rapid urbanization has intensified congestion, environmental pressures, and transport inequities, thereby increasing interest in Smart Urban Mobility (SUM) as an approach that combines digital technologies, sustainable transport strategies, and data-informed decision-making to respond to these challenges. However, the evaluation of SUM remains fragmented due to the absence of harmonized assessment frameworks and the diversity of methodologies applied across smart city contexts. This study presents a systematic literature review of evaluation approaches and indicator architectures for SUM in smart city contexts. Using a PRISMA-guided screening process, 33 eligible studies were selected from 412 retrieved records. Three main methodological groups were identified: quantitative approaches, multi-criteria decision-making methods, and qualitative or participatory frameworks. A total of 273 indicators were organized into eight factor categories, confirming the multidimensional nature of smart mobility assessment while also revealing limited consistency in indicator selection and application across studies. Across the selected studies, current evaluation practices are increasingly linked to project prioritization, planning, and decision support; however, their effectiveness remains constrained by data inconsistencies, governance fragmentation, and insufficient user inclusion. These findings highlight the need for assessment frameworks that are sufficiently comparable to enable cross-city learning, yet flexible enough to reflect local contexts and institutional realities. Full article

This study investigates the relationship between weather conditions (temperature, humidity), air pollutants (PM_2.5, PM₁₀, and CO), and photovoltaic (PV) degradation characteristics using location-specific machine learning frameworks. A data augmentation technique was employed to enhance the predictive modeling datasets. The research evaluates four machine learning models: AdaBoost, Gradient Boosting, Decision Tree, and Random Forest. We found strong regression analysis values using the addressed machine learning models. Furthermore, feature importance analysis reveals that PM_2.5 has the most significant impact on PV module degradation. Full article

Sustainable urban logistics requires infrastructure that can support routine low-carbon freight delivery while maintaining emergency supply capacity under disruptions. However, existing underground logistics system studies mainly focus on routine freight efficiency and network feasibility, whereas emergency logistics research is largely based on surface transport systems. Limited attention has been paid to the integrated design and operational validation of dual-use underground logistics networks under uncertain routine and emergency demand. To address this gap, this study proposes a dual-use underground logistics system (DULS) framework that combines robust layout optimization with dynamic simulation. A multi-echelon network consisting of supply centers, primary nodes, secondary nodes, and demand points is constructed. Candidate primary nodes are screened using an entropy-weighted TOPSIS method, and a Wasserstein-based distributionally robust optimization model is formulated to jointly determine node location, resource allocation, and freight paths under demand uncertainty. A hybrid heuristic is developed to solve the model, and an AnyLogic-based discrete-event simulation model is used to evaluate operational performance under different demand-generation patterns and train operation strategies. In the Nanjing case, the optimized DULS includes 19 primary nodes and 72 secondary nodes, achieves an emergency-demand fulfillment rate of 84.84%, and keeps the average end-to-end emergency supply time within 4 h. Cross-station operation performs better than the all-stop mode in both transport time and deprivation cost. An ex-post operational emission comparison further indicates that the DULS can reduce road-based freight emissions by 60.20% under routine operations. The proposed framework provides methodological support for planning sustainable dual-use underground logistics infrastructure serving both routine freight delivery and emergency supply. Full article

As urban–rural integration deepens, the growth of suburban integrated villages, as the key link between urban–rural factor flow and coordinated development, is affected by the asymmetric reciprocal symbiosis between urban and rural areas. Utilizing urban–rural integration and sustainable development theories, this study selected twenty-four suburban integrated villages in the Daoli District of Harbin as its research object. It concentrates on the township–village micro-symbiotic unit, formulates a two-dimensional evaluation framework of “village endogenous + township linkage,” and utilizes quantitative methodologies, including the coupling coordination degree model, the obstacle degree model, and sensitivity analysis, to identify the factors hindering the expansion of these villages and propose targeted strategies according to villages’ coordination levels. The results show that 79% of samples exhibit imbalanced coordination; although spatial constraints are the primary hindrances to village systemic coordination, balanced development of spatial, economic, social and ecological subsystems remains essential; the developmental constraints of the samples stem from weak village developmental foundations and insufficient township–village radiation linkages. This study enhances the township–village symbiosis micro-research framework and functions as a reference for the classification planning of suburban integrated villages and the sustainable amalgamation of urban and rural development. Full article

Intensifying climate change poses a major challenge to biodiversity conservation by weakening the ability of protected area systems to support species movement and ecological processes. However, protected area network planning has paid limited attention to the integration of climate connectivity and network resilience. Taking the highly urbanized Yangtze River Delta (YRD) as a case study, this study developed an integrated framework for climate-connected protected area network optimization. Specifically, climate refugia potential and species distribution probability were integrated to identify source areas, climate connectivity corridors were delineated by coupling landscape resistance with temperature gradients, and complex-network-based resilience analysis was applied to evaluate network responses under multiple disturbance and recovery scenarios. The results showed that: (1) climate stability, climate heterogeneity, and species distribution probability generally exhibited a south-to-north decreasing pattern, and 205 source areas were identified, mainly concentrated in the western and southern mountainous regions; (2) 459 climate connectivity corridors were extracted, forming a network backbone in the western and southern mountains, whereas corridors were relatively sparse in the plains and highly urbanized coastal areas; and (3) the network was highly vulnerable under critical-node-targeted, human-pressure-oriented, and climate-risk-oriented attack scenarios, while critical-node-priority recovery was the most effective strategy for restoring network function. These findings provide scientific support for cross-regional coordination, restoration prioritization, and long-term adaptive management in climate-connected protected area network planning. Full article