Search Results (13,635)

Cropland abandonment is a critical challenge for food security and the sustainable use of land resources, especially in the hilly and mountainous regions of southern China. To characterize the spatiotemporal evolution and associated-factor patterns of cropland abandonment in these regions, this study uses Ji’an City, Jiangxi Province, as a case study and develops an integrated framework for abandonment identification and monitoring, predictive-association analysis, relative risk assessment, and zoning management. Using Landsat remote sensing imagery from 1990 to 2024, crop phenological features, and multisource topographic, soil, climatic, ecological, and socioeconomic data, we identified and evaluated long-term cropland abandonment. The results show that, after incorporating phenological features and temporal filtering, annual land-use classification evaluated with spatially separated testing samples achieved a mean overall accuracy of 95.27% and a mean Kappa coefficient of 0.931, and the overall accuracy of cropland abandonment identification reached 91.58%, with a Kappa coefficient of 0.83. Cropland abandonment in Ji’an City showed an overall accelerating trend, with the abandonment rate exceeding 15% during 2020–2021. Spatially, abandonment was more intensive in the west than in the east and more severe in mountainous areas than in plains. Paddy field abandonment was the dominant form of cropland abandonment across the city, whereas dryland abandonment was more limited in extent but showed stronger interannual fluctuations. The predictive-association analysis indicated that tree cover consistently showed high predictive importance for both paddy fields and drylands. Paddy field predictions were more strongly associated with topographic position, surface roughness, and soil conservation, whereas dryland predictions showed stronger associations with aridity and population density. From 1993 to 2023, the model-estimated relative abandonment risk increased, and high-risk areas expanded from deep mountainous regions to low-hill areas. By coupling relative risk levels with associated-factor patterns, we divided paddy fields and drylands into four management zones: core protection zones, dynamic warning zones, integrated improvement zones, and ecological fallow zones. Differentiated management strategies were then proposed for each zone. This study provides methodological support and decision-making evidence for cropland abandonment monitoring, cropland protection, and differentiated land management in the hilly and mountainous regions of southern China. Full article

Urban sustainability is a critical objective for rapidly growing cities in the Gulf region, particularly in balancing environmental protection, social equity, economic development, and effective governance. Riyadh has undergone extensive urban expansion, producing diverse neighbourhoods ranging from high-income, modern master-planned communities to older and denser middle to low-income areas. These socio-spatial shifts prompt questions about whether sustainability performance differs across neighbourhoods with different resident income profiles and whether wealthier neighbourhoods necessarily exhibit higher sustainability performance. This study investigates the relationship between resident income level and urban sustainability in Riyadh by comparing the sustainability profiles of high-income and middle-income neighbourhoods using a multidimensional framework. Quantitative indicators derived from international sustainability assessment models were applied to the Riyadh context. The methodology integrated expert-based weighting, neighbourhood-level indicator assessment, and Sustainability Index calculations to evaluate performance. The findings show that the high-income neighbourhood achieved a higher overall Sustainability Index, mainly due to stronger environmental and social quality. However, the middle-income neighbourhood demonstrated notable sustainability potential through economic resilience, civic engagement, and community participation. The study concludes that differences in neighbourhood sustainability profiles are associated not only with resident income level, but also with urban form, behaviour, governance, and resource-use characteristics. Full article

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

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

The coupling coordination of urbanization and urban resilience is a key issue for achieving sustainable urban development. Taking 49 prefecture-level and above cities in the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) —China’s three major coastal urban agglomerations—as research objects, this paper constructs an evaluation index system for urbanization and urban resilience, and employs the CRITIC–entropy weight composite method, the coupling coordination degree model and kernel density estimation to measure the evolutionary characteristics of coupling coordination between urbanization and urban resilience in the three agglomerations during 2013–2023, and further identifies the key influencing factors using a panel fixed-effects model. The results show that (1) the coupling coordination degree of the three urban agglomerations increased continuously, with the PRD taking the lead in 2023 (0.6650), the YRD ranking second (0.6315) and the BTH ranking third (0.5627); however, their coupling coordination paths diverged markedly, specifically manifesting as a catch-up convergence pattern in the BTH, a balanced advancement pattern in the YRD and a polarization-divergence pattern in the PRD. (2) Opening-up and digital economy development are robust positive drivers of the coupling coordination level, and their positive effects are largely universal across regions; urban population agglomeration and government intervention constitute significant negative constraints, among which the inhibitory effect of government intervention exhibits genuine regional heterogeneity, being most prominent in the YRD, followed by the PRD, while failing the significance test in the BTH; technological innovation fails to pass the significance test; the full-sample effect of spatial structure is insignificant, but its influence exhibits significant regional heterogeneity, with a significantly positive association in the PRD. This study systematically reveals the regional differentiation rules governing the synergistic evolution of urbanization and resilience in the three urban agglomerations, providing empirical support for differentiated policies to promote the deep integrated development of urbanization and urban resilience. Full article

Post-earthquake fire, also referred to as fire following earthquake (FFE), can cause severe urban damage, particularly where detailed empirical fire-spread records are unavailable. This study derives a simulation-informed regional regression relationship between covering volume fraction (CVF) and fire-burned ratio for screening-level assessment in Pohang, South Korea, and integrates it into an existing static FFE risk-assessment framework. A total of 6604 dynamic fire-spread simulations were generated by varying the composition and assignment of four fire-resistance categories within the fixed GIS geometry of Region H. Building spacing, street form, wind direction, wind speed, relative humidity, and fire-spread duration were not independently varied; all calibration simulations used an NNW wind direction, a wind speed of 6.4 m/s, a relative humidity of 40%, and a fire-spread duration of 3 h. For the matched benchmark zones A, H, and J, the proposed relationship yielded relative differences of 0.21%, 19.31%, and 6.35%, respectively, relative to the TFD-based benchmark simulations. These comparisons are reported as simulation-informed matched-zone benchmarking within the same modeling framework and should not be interpreted as independent real-event or cross-city validation. From a sustainability perspective, the framework can support disaster-risk-informed urban planning by prioritizing districts for detailed analysis and mitigation, although environmental, social, and economic benefits were not quantified directly. Full article

Biochar is no longer considered merely a substitute for conventional fillers in asphalt materials; rather, it represents a multifunctional modifier that aligns with the goals of sustainable road design and urban mobility in smart cities. Its application now extends to the rheological modification of asphalt binders, mitigation of asphalt fume emissions, improvement in aging resistance and interfacial adhesion, and assessment of carbon sequestration potential. Biochar can improve the high-temperature stability, rutting and aging resistance, and asphalt–aggregate adhesion of asphalt materials in a suitable dosage, and at the same time reduce emissions of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), hydrogen sulfide (H₂S), and other fumes. However, the above effects are highly dependent on the biochar feedstock, production process, physicochemical properties, particle size, dosage and degree of dispersion. An excess amount or uneven distribution will reduce the crack resistance and fatigue life at low temperatures; phase separation may also occur and VOC emissions will increase. Therefore, the main problem in this area has shifted from whether biochar is effective to when it can be applied for particular pavement performance goals, what pollutant control targets are aimed for, and over what life-cycle periods. This review integrates evidence obtained at the binder, mastic, and mixture scales and critically evaluates the influence of biochar on pavement performance, fume emissions, aging, interfacial adhesion, and environmental safety. It also argues that empirical dosage selection should be replaced by coordinated optimization of biochar structure, material performance, emission mitigation, and life-cycle impacts. Verification of the low-carbon benefits and environmental safety of biochar-modified asphalt will ultimately require standardized assessment frameworks and consistently defined system boundaries. Ultimately, this work provides a foundation for integrating biochar-modified asphalt into eco-friendly and resilient road infrastructures, aligning with the goals of smart urban mobility and sustainable transportation. Full article

To alleviate the constraints of coastal saline-alkali soil on crop production and explore efficient and low-carbon planting patterns for vulnerable saline land ecosystems, a three-year continuous field experiment was carried out in the coastal saline-alkali farmland of the Yellow River Delta, Dongying City, Shandong Province, China. Using sole maize cropping (CM) as the control, this study systematically compared productivity, energy budget, economic benefit, carbon footprint (CF), and the carbon sustainability index (CSI) of maize–soybean intercropping (M/S) and maize–peanut intercropping (M/P), and further evaluated their comprehensive benefits based on the net ecosystem economic benefit (NEEB). The results showed that compared with CM, the three-year average economic yield of M/S and M/P decreased by 14.6% and 14.0%, with corresponding energy yield reductions of 12.0% and 9.1%. Notably, M/S and M/P significantly increased the maize equivalent yield by 9.4%. Relative to CM, the three-year average net income of M/S and M/P increased by 18.3% and 29.9%, respectively. For carbon-related environmental benefits, M/S and M/P reduced CF per unit maize equivalent yield by 14.0% and 18.1% and CF per unit economic benefit by 13.9% and 18.0%, while increasing the CSI by 6.0% and 8.4%, respectively. Comprehensive evaluation using the Z-score method demonstrated that M/P improved the NEEB by 9.4% and obtained a higher comprehensive score than CM, while M/S produced a marginally lower Z-score than CM. Overall, M/P exhibited the optimal multi-dimensional performance and represents a promising eco-friendly planting pattern for coastal saline-alkali regions. Full article

This paper presents a comprehensive review of the integration of Intelligent Transportation Systems (ITS) and Digital Twin (DT) technologies for intelligent traffic management. It examines the role of key enabling technologies, including the Internet of Things (IoT), machine learning (ML), deep learning (DL), reinforcement learning (RL), Graph Neural Networks (GNNs), vehicle-to-everything (V2X) communication, and edge computing. These technologies support real-time traffic monitoring, traffic prediction, and adaptive control in ITS. The review synthesizes recent research on conventional traffic control methods, optimization-based approaches, learning-based techniques, and DT-enabled traffic management solutions. Particular attention is given to the integration of DTs with intelligent traffic signal control, real-time synchronization, multi-intersection coordination, communication latency, sensing uncertainty, and scalability. The reviewed literature demonstrates the potential of DT-enabled ITS to improve traffic efficiency, reduce congestion, enhance transportation safety, and support sustainable mobility through data-driven decision-making. However, significant challenges remain regarding communication delays, sensor and data uncertainty, computational complexity, scalability, and validation under realistic urban conditions. Based on the reviewed literature, this paper identifies key research gaps and outlines future research directions toward scalable, reliable, adaptive, and real-time DT-enabled ITS architectures for next-generation smart cities. Full article

This study investigates how integrated smart urban systems enhance resource efficiency in Saudi Arabia’s rapidly urbanising cities. Despite growing global interest in smart cities, there remains a critical gap in empirical research that simultaneously examines smart energy, water, and waste systems within a unified analytical framework, particularly in emerging urban contexts, while the mediating role of governance efficiency remains underexplored. Adopting a quantitative survey design, this study employs Structural Equation Modelling (SEM) to analyse 384 valid data from 384 stakeholders across selected urban areas. A stratified sampling approach ensures representation of policymakers, urban planners, and infrastructure managers, and measurement constructs are adapted from validated scales to ensure reliability and validity. The study examines relationships between smart energy systems, smart water management, smart waste monitoring, governance efficiency, and resource efficiency outcomes, with governance efficiency conceptualised as a mediating variable enhancing the effectiveness of smart urban systems. The study hypothesises that integrated smart technologies significantly improve resource efficiency, with smart infrastructure as a key predictor; structural model robustness is assessed using standard SEM fit indices, with CFI (0.93), TLI (0.91), and RMSEA (0.052). This research contributes to theory by integrating smart urban systems and governance into a unified framework, extending smart city and circular economy literature, while offering practical insights aligned with Saudi Vision 2030 to support sustainable urban development. It is recommended that policymakers prioritise integrated smart infrastructure, strengthen institutional frameworks, and promote public awareness to maximise resource optimisation. Future research should adopt longitudinal designs, expand across multiple cities, and incorporate behavioural and policy variables to enhance generalizability and deepen insights into smart urban resource efficiency. Full article

Unmanned aerial vehicles (UAVs) are increasingly considered as enabling technologies for last-mile delivery, emergency medical response, and smart-city applications. However, drone-based logistics, emergency communication, sensing activities, and future aerial mobility are often addressed as separate research domains. This article proposes a four-dimensional planning framework for drone-enabled mobility, integrating goods, information, sensing, and human mobility within a unified conceptual structure. The framework is developed through a literature-informed conceptual analysis and previous applied research experiences related to drone-assisted logistics and emergency communication. Goods mobility includes parcel delivery, medical logistics, emergency supply transport, and hybrid operational models involving trucks, public transport, depots, and micro-hubs. Information mobility refers to the use of drones as mobile communication tools for emergency warnings, citizen interaction, drone-to-infrastructure communication, and infomobility services. Sensing mobility concerns traffic monitoring, environmental observation, disaster mapping, crowd monitoring, and infrastructure inspection. Human mobility is considered as an emerging extension related to urban air mobility (UAM), electric vertical take-off and landing (eVTOL) systems, and low-altitude aerial corridors. Cross-cutting issues such as energy autonomy, solar-assisted drones, multimodal integration, safety, communication, regulation, sustainability, and public acceptance are discussed. The proposed framework provides a structured basis for assessing drones as components of sustainable, resilient, and multimodal mobility systems. Full article

Open government data is a key institutional arrangement in market-oriented data factor reforms. Using the staggered rollout of city-level government data platforms in China as a quasi-natural experiment and panel data of listed manufacturing firms (2011–2024), we employ a staggered difference-in-differences design to examine the effect of open government data on firms’ resource allocation efficiency. We find that government data platforms significantly reduce resource misallocation, a result robust to propensity score matching, exclusion of concurrent policy shocks, and double machine learning. Channel-level tests do not find statistically significant transmission through government transparency, firm digital innovation, or fiscal subsidy reallocation. Directional identification shows that the effect operates primarily as a corrective force on capital-overallocated firms by curbing inefficient investment, rather than as a relief effect on constrained firms, and is more pronounced in high-digital-intensity industries, smaller cities, and regions with lower digital development. By reducing the wasteful use of capital, labour, and energy and improving the information environment in factor markets, open government data offers a low-cost, institutionalized instrument for reconciling productivity growth with sustainable resource use, with direct relevance to the United Nations (UN) Sustainable Development Goals (SDGs). Full article

This study examines the relationship between the financial sustainability of local government units (LGUs) and their investment capacity, focusing on differences between municipalities and cities with county rights in Poland. It investigates how operating surplus, debt-servicing costs, and revenue autonomy are associated with investment capacity and whether these relationships differ across LGU types. The analysis uses data for Polish municipalities and cities with county rights for 2018–2024 obtained from the Local Data Bank of Statistics Poland. Various panel regression specifications were employed, supplemented by descriptive Pearson correlation analysis. The results indicate a consistent positive tendency in the relationship between operating surplus and investment capacity, whereas higher debt-servicing costs were significantly associated with lower investment capacity. Cities with county rights exhibited higher investment capacity than municipalities, although the strength of the evidence varied depending on the measure used. Revenue autonomy, in contrast, was found to be negatively associated with investment capacity. This study provides a comparative assessment of the relationship between financial sustainability and investment capacity, offering implications for local fiscal policy and future research. Full article

In the context of the global implementation of the United Nations 2030 Sustainable Development Goals (SDGs), urban green development serves as a core practical pathway to advance SDG8 (Decent Work and Economic Growth), SDG11 (Sustainable Cities and Communities), and SDG15 (Life on Land). This study constructed a three-dimensional evaluation framework encompassing the green economy, green ecology, and green society, and utilized panel data from 282 Chinese prefecture-level cities from 2009 to 2021. By integrating the CRITIC weighting method, spatial autocorrelation, the Standard Deviational Ellipse (SDE) approach, and the Dagum Gini decomposition, we systematically quantified multi-scale spatiotemporal evolution and disparity patterns at the national scale, as well as across four major economic zones and five core urban agglomerations. Nationwide, the composite green development index rose from 0.422 to 0.522 (+23.70%), while the overall Dagum Gini coefficient declined from 0.072 to 0.053 (−26.39%), with the spatial center of gravity gradually shifting toward the southwest. Eastern China persistently maintained the highest development level; Western China achieved the fastest cumulative growth (26.43%), and Northeastern China lagged behind with the lowest growth rate (20.10%). Among five major urban agglomerations, the Yangtze River Delta (YRD) and Pearl River Delta (PRD) shared an identical average score of 0.582, whereas the Chengdu–Chongqing (CC) agglomeration recorded the highest growth of 33.07%. This research contributes multi-scale empirical evidence for localized SDG implementation in China and provides differentiated policy insights for cross-regional green transition governance. Full article

Urbanisation has become a significant driver of ecological transformation, resulting in the degradation of urban green and blue spaces (UGSs and UBSs) and a subsequent decrease in ecosystem services (ESs). It is imperative to evaluate the spatio-temporal dynamics of UGS and UBS in order to develop sustainable urban planning strategies, particularly in the swiftly expanding cities of the Global South. In the Siliguri Planning Area (SPA), India, this study examines the long-term variations in UGS and UBS and their associated ecosystem service values (ESVs) from 1991 to 2021. The Normalised Difference Vegetation Index (NDVI) and Modified Normalised Difference Water Index (MNDWI) were employed to delineate UGS and UBS using multi-temporal Landsat imagery, respectively). The benefit transfer method was employed to quantify ESV, and sensitivity analysis was conducted to assess the valuation’s reliability. Also, adjusted value coefficients were employed. The findings indicated that landscapes such as tea garden (58.74% reduce) and agricultural land (46.09 increase) have undergone a substantial transformation as a result of urbanisation, with the built-up areas increasing from 5798.61 ha in 1991 to 8500.23 ha in 2021 (46.59% increase). Simultaneously, UGS decreased (by 40.26%) from 12,533.04 ha (47.81% oftotal area)in 1991 to 7486.29 ha (28.55% oftotal area) in 2021, while UBS decreased (by 79.47%) from 255.69 ha (0.94% oftotal area) in 1991 to 52.48 ha (0.19% oftotal area) in 2021. Subsequently, the ESV of UGS and UBS fell significantly from 1183.05 crores (INR) to 706.67 crores (INR) and 34.72 crores (INR) to 7.12 crores (INR), respectively. This confirms the elasticity of the valuation estimates, as the sensitivity coefficients remained below one. The study contributes to understanding the crucial role of urban planners, private property owners, and builders in promoting green–blue infrastructure conservation, wetland restoration, and ecological zoning. Such ecosystem service-based planning is essential for achieving sustainable development in rapidly urbanising regions and enhancing urban ecological resilience. Full article