Search Results (12,267)

Urban river networks face significant ecological challenges due to intensive urbanization. Traditional assessment methods focus mainly on individual rivers and overlook cross-scale connections. To fill this research gap, the study refined the Urban Riverscape Conditions-based Assessment for Management Needs (URBAN) framework and developed a dual-scale assessment system covering the entire river network and individual rivers. It evaluates hydrology, geomorphology, ecology, and the waterfront public service dimension. Taking the Qingxi area of Shanghai as a case study, this study integrated multi-source data and adopted field investigations, the analytic hierarchy process (AHP) and principal component analysis (PCA) to collect field data, calculate indicator weights, and extract dominant functional factors. The results show that the overall comprehensive health score of the study area is 59.39, classified as average; the river network scale scores 58.34, and the 21 monitored rivers achieve an average score of 61.80. The assessment identifies clear advantages in hydrological and geomorphological conditions, whereas waterfront public services and river morphological diversity are still deficient. Overall, this system demonstrates good operability and scientific validity, providing practical technical approaches for sustainable urban river network management and supporting refined watershed governance. Full article

Rapid urbanization has intensified inequalities in the distribution of urban green resources, making green equity a critical concern within the framework of the United Nations Sustainable Development Goals. This study examines Zhangdian District in Zibo City, China, a representative “Whole-Area Park City” pilot area. This study integrates 1 km population density grid data with GIS network analysis, space syntax, population-weighted service pressure assessment, and a location–allocation model. Using these methods, it evaluates four categories of urban parks from the perspectives of spatial distribution, road connectivity, and social equity. The results reveal that vehicle and cycling modes achieved nearly complete 15 min coverage, whereas pedestrian accessibility remained insufficient. Walking accessibility for comprehensive parks reached 77.69%, whereas that of community parks and petty street gardens was below 33%. Population-weighted analysis further suggests that more than 78% of residents, concentrated in dense central–western neighborhoods, are served by only 21% of total park area. The Gini coefficient of per capita park area reached 0.4765, indicating substantial inequality in park green space allocation. After optimization through the addition of 76 new parks, improvements in road connectivity, and construction of a slow-traffic system, the Gini coefficient decreased to 0.4053, representing a 14.9% reduction. Meanwhile, the population below the national standard declined from 78.09% to 40.64%. These findings reflect spatial accessibility and area-based equity, while actual park service value also depends on park quality, facilities, and user behavior. This study provides quantitative evidence for equity-oriented park planning and a replicable framework for sustainable urban green space planning. Full article

Stray-current corrosion from DC-electrified railways drives premature failure of buried metallic infrastructure (pipelines, foundations, tunnel reinforcement), causing resource waste, repair-driven carbon emissions and service disruptions that undermine the sustainability of urban transit corridors. Conventional impressed-current cathodic protection (ICCP) design relies on uniform-anode rules of thumb or closed commercial codes that cannot quantify the trade-off between protection uniformity, energy use and hardware cost. We present an open MATLAB framework that couples a custom 3D finite element method (FEM) solver with multi-objective particle swarm optimisation (MOPSO) and minimises three competing objectives simultaneously: total impressed current, RMS deviation from the protection target, and number of active anodes. A laboratory-calibrated coupling factor ($\mathrm{CF}=1.98$, consistent with the image-method prediction of 2 for a highly conductive pipe inclusion) absorbs the pipe–soil interface kinetics into a single direct FEM solve, and a pre-computed Green’s-function basis accelerates each MOPSO evaluation by more than two orders of magnitude. The solver is validated against an instrumented prototype with RMSE $=14.9$ mV across ten Cu/CuSO${}_4$ saturated reference electrode (CSE) measurements, and applied to a 500 m DC traction line. At an identical total current of 20.30 A across five anodes, the optimised design achieves an RMSE of 86.6 mV against the $-850$ mV NACE target, whereas a conventional uniform layout produces severe over-protection (RMSE $=1107$ mV)—a twelve-fold reduction. The framework is recommended as a transparent, reproducible engineering tool that simultaneously extends pipeline service life and reduces rectifier energy demand, supporting UN Sustainable Development Goals 9 and 11 for sustainable urban-rail infrastructure. Full article

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

Tourism drives economic growth but also intensifies environmental pressure at travel destinations, particularly by exacerbating local challenges in waste management. Rather than merely testing the theoretical validity of the norm activation model (NAM), this study utilizes its key constructs—specifically moral and accountability variables—as a strategic framework to examine the psychological drivers of waste reduction in the urban context of Vientiane, Laos. Data from 382 domestic tourists were analyzed using ordinary least squares regression. Ascription of responsibility (AR) (β = 0.219, p < 0.001) was the strongest predictor of intention, followed by personal norm (PN) (β = 0.173, p < 0.01) and actual waste management behavior (β = 0.160, p < 0.01). Notably, environmental knowledge and awareness of consequences—factors often emphasized in traditional environmental campaigns—had no significant influence. The findings demonstrate that, in addressing urban waste challenges in developing regions, fostering internalized moral sentiments (AR and PN) is far more effective than mere pro-environmental education. This study concludes that sustainable waste management may benefit from operationalized interventions that activate personal accountability rather than relying solely on general environmental awareness. Full article

Deep learning-powered Street View Imagery (SVI) analytics provides a critical mechanism for smart city perception within the framework of Sustainable Development Goal 11 (SDG 11), effectively bridging the gap left by traditional remote sensing in fine-grained street-level observation. Over the years, deep learning-based semantic segmentation of urban streetscapes has become the dominant paradigm. However, when scaling to megacity measurements, current research faces the dual bottlenecks of “computational redundancy” and the “geographical domain shift” caused by the blind application of pre-trained models based on Western datasets. To address these challenges, this study is the first to systematically quantify the performance trade-off between Multi-Task Learning (MTL) and Single-Task Learning (STL) in megacity scenarios. Using this as a baseline, we constructed and validated a “low-computation, high-robustness” framework for streetscape semantic perception and spatial measurement. Relying on an integrated ResNeXt101-FPN MTL architecture and an ultra-low-cost fine-tuning strategy to overcome geographical domain shift, we extracted and analyzed the spatial heterogeneity of five core semantic elements—vegetation, sky, building, road, and vehicle—across the road network within Beijing’s 5th Ring Road. The results indicate the following: (1) We explicitly defined the computation-accuracy trade-off of MTL and STL in megacity perception. While utilizing only 1/5 of the parameters of STL, the MTL framework achieved a 5.34-fold increase in inference speed with a negligible 0.1% loss in overall mean Intersection over Union (mIoU); however, a 27.13% decrease in boundary segmentation accuracy was observed. (2) We established a low-cost, localized correction paradigm to overcome domain shift. Utilizing a minimal annotation cost (only 200 local images) significantly improved cross-domain adaptability, boosting the overall mIoU by 8.92% and significantly mitigating the geographical domain shift problem. (3) Multi-dimensional measurement and spatial analysis revealed a significant spatial decoupling pattern in Beijing’s streetscapes. The visual proportion of vegetation exhibited a pronounced “north-high, south-low” spatial differentiation, whereas built environment elements (e.g., building and road) displayed a typical “center-periphery” concentric gradient. This objectively reflects the spatial inequality of urban street greenery resources and the monocentric development characteristics of the built environment. The proposed framework therefore serves as a low-cost, AI-driven computational paradigm for smart city perception in resource-constrained regions. Furthermore, the revealed spatial heterogeneity offers data-driven insights for formulating sustainable urban renewal policies aligned with SDG 11. Full article

Coastal cities are typical regions where economic growth, population agglomeration, and eco-environmental pressures are strongly coupled. Assessing the coordination between urban development and the eco-environment is therefore important for regional sustainability. This study selected seven representative coastal cities in China—Dalian, Qinhuangdao, Qingdao, Shanghai, Fuzhou, Xiamen, and Zhuhai—and integrated multisource remote sensing data with statistical yearbook data to construct a comprehensive evaluation system for urban development level (UDL) and eco-environmental quality (EEQ). An ecologically enhanced indicator system incorporating vegetation condition index (VCI), biological richness index (BRI), normalized difference vegetation index (NDVI), and dynamic habitat index (DHI) was developed. The coupling coordination degree (CCD) model was then used to evaluate urban sustainable development from 2014 to 2023. In addition, an EWM–MLP adaptive weighting strategy was applied to refine entropy-derived weights, and Random Forest was used to identify variables associated with CCD prediction. The results show that CCD values generally increased during the study period, indicating improved coordination between urban development and the eco-environment. However, the evolutionary pathways differed markedly among cities, and UDL and EEQ changes were not fully synchronized. The EWM–MLP strategy introduced adaptive numerical refinements to CCD values while maintaining the overall stability of coordination-level classification. Random Forest analysis showed that CCD prediction was mainly associated with a limited number of high-contribution indicators. For all indicators combined, approximately 7–10 top-ranked variables were generally required to exceed 80% of the total importance, whereas the UDL and EEQ subsystems reached this threshold with fewer indicators. UDL-related variation was mainly associated with land-use structure, population agglomeration, and economic activity, whereas EEQ-related variation was related to ecological conditions, land-cover composition, and environmental pressure. The high-importance indicators exhibited clear inter-city heterogeneity, suggesting the need for differentiated governance strategies. The proposed framework provides methodological support for sustainable development assessment and differentiated governance in coastal cities. Full article

Digital literacy (DL) is a cornerstone of sustainable digital transformation in education, yet its systemic cultivation among pre-service teachers in resource-constrained regions remains critically under-theorized. This study develops and validates a contextualized DL measurement framework grounded in the “triple identity” of pre-service teachers as citizens, learners, and future educators. Employing a multiphase mixed-methods design, this systemic framework was refined via Delphi consultation and rigorously validated through exploratory (n = 287) and confirmatory factor analyses (n = 1462) across 24 universities in Southwest China. The newly validated framework, comprising five core dimensions and 41 specific indicators, demonstrates robust psychometric properties and systemic structural validity. Findings reveal a moderately high overall DL (M = 3.44) but highlight a significant “skills-awareness” gap, where operational proficiency exceeds conceptual cognition, particularly in comparison with findings reported in other Chinese regions. Hierarchical regression indicated that structural variables added substantial explanatory power beyond individual demographic characteristics, with institution type emerging as the strongest predictor and urban-rural background making an additional significant contribution. These results underscore the paradox between DL’s inherent malleability and the rigid constraints of structural inequality. The study offers a validated measurement tool and an evidence-informed roadmap for policy interventions aimed at bridging the digital divide in underdeveloped teacher education systems, advocating for a shift from technical training toward systemic equity. Full article

Whether compact urban development can achieve a spatial balance in the supply and demand of ecosystem services remains unclear amidst rapid urbanization. Understanding this relationship is critical for territorial spatial planning. Using Guanzhong Plain Urban Agglomeration as a case study, we applied local spatial autocorrelation to reveal spatial trade-offs and synergies, and employed ordinary least squares and geographically weighted regression models to analyze the underlying mechanisms. Results demonstrate that urban compactness is significantly negatively correlated with supply–demand gaps for carbon storage (r = −0.66), habitat quality (r = −0.58), recreation services (r = −0.60), and water yield (r = −0.63), while positively correlated with gaps for grain production and soil conservation. The GWR model outperformed the ordinary least squares model, with improvements in adjusted R² ranging from 0.0019 to 0.13. Land use intensity and GDP emerged as the dominant drivers of spatial heterogeneity in the ecosystem service supply–demand ratio, accounting for 66.21% and 51.08% of the variance, respectively. These findings provide a scientific basis for integrating compact urban form with ecosystem management in sustainable landscape planning. Full article

Rural land art festivals serve as an important practical vehicle for integrating urban and rural culture and tourism. They constitute a crucial component of rural tourism in China and play a key role in the sustainable development of rural areas. However, in practice, these festivals are generally confronted with the dilemma of superficial tourist participation and insufficient sustainability. This study aims to uncover the intrinsic psychological evolution mechanism underlying tourists’ responses to external stimuli and their value co-creation. The S-O-R model and the two-factor theory are integrated to construct an analytical framework: “external stimulus–psychological sequence–behavioral response.” Using “Modern Fields” as the case study and 437 valid data points, an empirical analysis is conducted with PLS-SEM and artificial neural networks (ANNs). The results indicate that tourist participation is directly driven by destination quality. Content stickiness exerts an indirect influence through perceived value. Perceived value facilitates value co-creation only when it is fully mediated by tourist participation. The path from participation to co-creation is significantly strengthened by restorative environmental perception. A multi-group analysis further reveals that inexperienced tourists exhibit a “stimulus-driven” characteristic, whereas experienced tourists follow a “value internalization” path. The ANN analysis further shows that the strongest nonlinear predictive power for co-creation behavior is held by restorative environmental perception. A significant direct nonlinear effect is also exerted by destination quality. The evolutionary nodes and boundary conditions of tourists’ psychological sequence during this process are revealed. The boundary effect of restorative environmental perception as a catalyst for rural art tourism is demonstrated. A theoretical basis and practical insights are thereby provided for the segmented operation and sustainable development of these activities. Full article

This article presents the results of a field study conducted in 2022 on groundwater outflows located at the edge of the Kashubian Lake District and the Reda-Łeba Proglacial Stream Valley in northern Poland. The recharge of numerous springs was found to occur from the first aquifer, locally supported by a deeper aquifer connected to the first one near the bowl of Lubowidzkie Lake. Groundwater drainage occurs by gravity. It is relatively abundant for young glacial areas and averages 82 dm³·s⁻¹, making the springs capable of acting as a drinking water reservoir. This assessment is based on major ions and nutrients only; microbiological and trace-organic/metal analyses are required before any drinking-water designation. Spring water is important in the lake’s supply, accounting for 18.0% of the total inflow to the basin. The hydrochemical characteristics of these waters keep the lake in ecological balance. The waters from the springs are characterized by little variation in chemical composition, with the Ca-HCO₃ hydrochemical type. They represent young infiltration waters associated with direct recharge from precipitation (the average age of the water is 60 years). Currently, low nitrate and chloride suggest limited agricultural and urban influence, but phosphate levels and observed human activities warrant caution. Forest management is gradually developing in its catchment, which may result in a reduction of the spring yield and a deterioration of their quality in the future. This may result in a disturbance of the hydrological balance of structures hydraulically connected to spring recharge and to groundwater inflow (river, lake). Although the springs studied are local hydrological phenomena, their functioning and the need for protection are closely linked to global challenges in the field of sustainable development. This primarily concerns the protection of groundwater-dependent ecosystems and, more broadly, water security and increased resilience to climate change. Full article

Digital innovation constitutes the core determinant of sustainable digital transformation and functions as a pivotal driver of regional high-quality economic development. As a strategic node in China’s urban agglomeration framework, the Guangdong–Fujian–Zhejiang Coastal Urban Agglomeration plays a critical role in regional synergistic high-quality development. This study examines how digital innovation impacts the coupling coordination of high-quality development in the urban agglomeration. The results show: (1) Synergistic high-quality development shows a steady downward trend in the research region with substantial coordination potential. (2) “Gradient disparity” exists, primarily driven by inter-regional Gini coefficient contributions. (3) Overall coupling coordination remains at the antagonistic stage with significant convergence tendencies. (4) Lack of robust central city and centripetal force hinders effective spatial radiation. Driven by the core-periphery spatial differentiation, the short-run dominance of digital innovation’s polarization effect undermines the coordination level of urban agglomerations through scale expansion, structural optimization, and technological empowerment. It requires vigilance against Yangtze and Pearl River Delta siphoning effects. This study provides theoretical and practical implications for promoting digitally driven, synergistic, sustainable, and balanced high-quality development, as well as for optimizing policy frameworks in the new era. 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

Landslides are a recurrent geohazard in Andean urban environments, where weak soils, intense seasonal rainfall, and unplanned urban expansion combine to increase slope vulnerability. In such settings, sustainable hillside management requires stabilization strategies that are both technically effective and environmentally compatible. This study evaluates the effect of root reinforcement by vetiver grass (Chrysopogon zizanioides) on slope stability in two representative soils from Loja, Ecuador: sandy silt (SM) and sandy clay (SC). A reduced-scale physical model with 30 days of root development was established, and consolidated–drained direct shear tests (ASTM D3080/D3080M-23) were performed to determine the shear strength parameters under bare and vetiver-reinforced conditions. These parameters were then incorporated into numerical slope stability analyses using Slide and PLAXIS 2D, considering three slope angles (30°, 45°, and 50°), six root-positioning configurations, and hydraulic conditions with and without a water table. Vetiver increased effective cohesion by 22.7% in sandy silt and 19.0% in sandy clay, while the internal friction angle increased by 21.8% and 12.2%, respectively. Across all modeled scenarios, vetiver produced a consistent improvement in the factor of safety. The most critical case, corresponding to sandy silt at 45° with a water table, increased from FS = 0.841 in the control condition to FS = 1.309 under the full-coverage configuration. Parametric sensitivity analysis yielded coefficients of variation between 4.97% and 7.03%, indicating a stable model response under controlled parameter perturbations. These findings support vetiver as an experimentally grounded and environmentally sustainable Nature-based Solution for slope stabilization and provide relevant evidence for sustainable management of hazard-prone urban hillsides in vulnerable Andean settings. Full article

Tourism development can both support and strain regional sustainability. Sustainable tourism matters especially in highly urbanized metropolitan areas, where resident mobility and tourist demand jointly use transport systems. This study evaluates transport infrastructure adequacy and quality under tourism pressure in regions containing Russia’s largest urban agglomerations. Because official tourist-flow statistics are available at the regional rather than agglomeration level, the analysis uses an exploratory regional proxy approach. The methods combine comparative analysis, correlation and regression analysis, index analysis, and sensitivity checks. Tourist flows show the strongest statistical associations with absolute indicators of bus infrastructure. Rail transport, especially commuter rail, also shows a stable positive association, which matters for large metropolitan areas and regions with intensive intermunicipal mobility. Overall, tourist flows in the studied regions correlate primarily with the scale of the existing passenger transport system. Therefore, the results represent diagnostic associations rather than causal estimates of tourist transport behavior. The study proposes a comparative index of tourism transport infrastructure adequacy that characterizes how well the selected territories’ transport systems can absorb tourist traffic under data limitations. The index reveals pronounced differentiation among the Moscow, Saint Petersburg, and Kaliningrad cases. Full article