Search Results (2,750)

With the global economic restructuring and the consequent population mobility, urban shrinkage has become a common phenomenon. The Qinling–Daba Mountains, a zone with a key ecological function in China, have long experienced population decline and functional degradation. Clarifying the dynamics and influencing factors of urban shrinkage plays a vital role in supporting the sustainable development of the region. This study, using permanent resident population growth rates and nighttime light data, classified cities in the region into four spatial patterns: expansion–growth, intensive growth, expansion–shrinkage, and intensive shrinkage. It further examined the spatial characteristics of shrinkage across four periods (2005–2010, 2010–2015, 2015–2020, and 2020–2022). A Geographically and Temporally Weighted Regression (GTWR) model was applied to examine core influencing factors and their spatiotemporal heterogeneity. The results indicated the following: (1) The dominant pattern of urban shrinkage in the Qinling–Daba Mountains shifted from expansion–growth to expansion–shrinkage, highlighting the paradox of population decline alongside continued spatial expansion. (2) Three critical indicators significantly influenced urban shrinkage: the number of students enrolled in general secondary schools (X₅), the per capita disposable income of urban residents (X₇), and the number of commercial and residential service facilities (X₁₂), with their effects exhibiting significant spatiotemporal heterogeneity. Temporally, X₁₂ was the most influential factor in 2005 and 2010, while in 2015, 2020, and 2022, X₅ and X₇ became the dominant factors. Spatially, X₇ significantly affected both eastern and western areas; X₅’s influence was most pronounced in the west; and X₁₂ had the greatest impact in the east. This study explored the patterns and underlying drivers of urban shrinkage in underdeveloped areas, aiming to inform sustainable development practices in regions facing comparable challenges. Full article

Strengthening climate resilience constitutes a foundational approach through which cities adapt to climate change and mitigate associated environmental risks. However, research on the influence of economic policy environments on climate resilience remains limited. Guided by institutional theory and dynamic capability theory, this study employs a panel dataset comprising 272 Chinese cities at the prefecture level and above, covering the period from 2009 to 2023. It constructs a composite index framework for evaluating the green business environment (GBE) and urban climate resilience (UCR) using the entropy weight method. Employing a two-way fixed-effect regression model, it examined the impact of GBE optimization on UCR empirically and also explored the underlying mechanisms. The results show that improvements in the GBE significantly enhance UCR, with green innovation (GI) in technology functioning as an intermediary mechanism within this relationship. Moreover, climate policy uncertainty (CPU) exerts a moderating effect along this transmission pathway: on the one hand, it amplifies the beneficial effect of the GBE on GI; on the other hand, it hampers the transformation of GI into improved GBEs. The former effect dominates, indicating that optimizing the GBE becomes particularly critical for enhancing UCR under high CPU. To eliminate potential endogenous issues, this paper adopts a two-stage regression model based on the instrumental variable method (2SLS). The above conclusion still holds after undergoing a series of robustness tests. This study reveals the mechanism by which a GBE enhances its growth through GI. By incorporating CPU as a heterogeneous factor, the findings suggest that governments should balance policy incentives with environmental regulations in climate resilience governance. Furthermore, maintaining awareness of the risks stemming from climate policy volatility is of critical importance. By providing a stable and supportive institutional environment, governments can foster steady progress in green innovation and comprehensively improve urban adaptive capacity to climate change. Full article

In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, this study employs a multiperiod difference-in-differences (DID) approach, leveraging smart city pilot policies as a quasinatural experiment, to assess how digital infrastructure affects urban synergistic pollution-carbon mitigation (SPCM). The empirical results show that digital infrastructure increases the urban SPCM index by 1.5%, indicating statistically significant effects. Compared with energy and income effects, digital infrastructure can influence this synergistic effect through indirect channels such as the energy effect, economic agglomeration effect, and income effect, with the economic agglomeration effect accounting for a larger share of the total effect. Additionally, fixed-asset investment has a nonlinear moderating effect on this relationship, with diminishing marginal returns on emission reduction when investment exceeds a threshold. Heterogeneity tests reveal greater impacts in eastern, nonresource-based, and environmentally regulated cities. This study expands the theory of collaborative environmental governance from the perspective of new infrastructure, providing a theoretical foundation for establishing a long-term digital technology-driven mechanism for SPCM. Full article

Green innovation is a critical driver of sustainable development, yet it often faces efficiency challenges in rapidly industrializing economies. This study investigates the effect of China’s Circular Economy Demonstration Policy (CEDP) on urban green innovation efficiency (GIE) using city-level panel data from 2010 to 2021. Employing a difference-in-differences (DID) approach, we find that CEDP significantly enhances GIE, with the policy effect becoming statistically significant after a three-year lag and accumulating over time. Robustness tests, including placebo analyses, alternative dependent variables, and propensity score matching, confirm the validity of the results. Mechanism analysis reveals that the policy improves green innovation primarily by reducing capital distortion, promoting market integration, and enhancing resource allocation efficiency. Further heterogeneity analyses show that the positive effects are stronger in central cities, capital cities, and eastern regions, reflecting the role of local economic and institutional conditions. The study concludes with policy implications emphasizing regionally tailored implementation, capacity building, and long-term commitment to maximize green innovation outcomes. Full article

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article

Urban infrastructure, such as water supply networks, sewage systems, and electricity networks, is essential for the functioning of cities and, consequently, for the well-being of citizens. Despite its essentiality, the distribution of infrastructure in urban areas is not homogeneous, especially in cities in developing countries. Socially vulnerable areas often face significant deficiencies in sewage and road paving, exacerbating urban inequalities. In this regard, urban planners must consider the multiple elements of urban infrastructure and assess the compensation levels between them to reduce inequality effectively. In particular, the complexity of the problem necessitates considering the multidimensionality and heterogeneity of urban infrastructure. This complexity qualifies the operational framework of composite indicators as the natural solution to the problem. This study develops a new weighting system for the balanced expansion of urban infrastructures through composite indicators constructed by the Ordered Weighted Average operator. Implementing these weighting systems provides an opportunity to analyze urban infrastructure from different perspectives, offering transparency regarding the weaknesses and strengths of each perspective. This prevents unreliable representations from being used in decision-making and provides a solid basis for allocating investments in urban infrastructure. In particular, the study suggests that adopting weighting systems that prioritize intermediate values and avoid extreme values can lead to better resource allocation, helping to identify areas with deficient infrastructure and promoting more equitable urban development. Full article

Improving the green innovation quality (GIQ) of center cities is crucial to achieve sustainable urban agglomeration development. Utilizing data on green patent citations and economic indicators across cities in the Yangtze River Delta urban agglomeration (YRD) from 2003 to 2022, this research examines the influence of center cities’ GIQ on the economic performance of peripheral municipalities. The results show the following: (1) Center cities’ GIQ exerts a significant suppressive effect on peripheral cities’ economic growth overall. Heterogeneity analysis uncovers a distance-dependent duality. GIQ stimulates growth in proximate cities (within 300 km) but suppresses it beyond this threshold. This spatial siphoning effect is notably amplified in national-level center cities. (2) Mechanisms suggest that GIQ accelerates the outflow of skilled labor in peripheral cities through factor agglomeration and industry transfer mechanisms. Concurrently, it impedes the gradient diffusion of urban services, collectively hindering peripheral development. (3) Increased government green attention (GGA) and industry–university–research cooperation (IURC) in centers can mitigate these negative impacts. This paper contributes to the theoretical discourse on center cities’ spatial externalities within agglomerations and offers empirical support and policy insights for the exertion of spillover effects of high-quality green innovation from center cities and the sustainable development of urban agglomeration. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

Land urbanization enables a thorough perspective to explore the decoupling of land use environmental efficiency (LUEE) and energy use, thereby supporting the shift into low-carbon land use by emphasizing energy conservation and reducing carbon emissions. This paper first calculates LUEE from 2011 to 2021 by using the EBM-DEA model in China. The geographical detector model is used to examine the driving factors of land use environmental efficiency. The results show the following: (1) China’s LUEE is high in general but shows a clear pattern of spatial differentiation internally, with the highest values in the eastern region represented by Beijing, Jiangsu, and Zhejiang, while the central and western regions show lower LUEE because of their irrational industrial structure and lagging green development. (2) Energy consumption, economic development, industrial upgrading, population size, and urban expansion are the driving factors. Their explanatory power for the spatial stratification heterogeneity of land use environmental impacts varies. (3) Urban expansion has the greatest impact on the spatial differentiation of land use environmental effects, while energy consumption also shows significant explanatory strength. In contrast, economic development and population size exhibit relatively weaker explanatory effects. (4) The interaction of the two driving factors has a greater impact on LUEE than their individual effects, and the interaction is a two-factor enhancement. Finally, we make targeted recommendations to help improve land use environmental efficiency. Full article

Against the backdrop of China’s fast-growing digital economy and its financial inclusion agenda, there is still little city-level evidence on whether the e-CNY pilot accelerates financial deepening at the grassroots. Using a balanced panel of 271 prefecture-and-above cities for 2016–2022, this study employs a staggered difference-in-differences (SDID) design augmented by the synthetic control method (SCM) to rigorously identify the policy effect of the e-CNY pilot. The results show that the pilot program significantly improves urban financial inclusion, contributing to more equitable access to financial services and supporting inclusive socio-economic development. Mechanism analysis suggests that the effect operates mainly through two channels, a merchant-coverage channel and a transaction-scale channel, with the former contributing the majority of the overall effect. Incorporating a migration-based mobility index shows that most studies’ focus on the merchant-coverage effect is amplified in cities under tight mobility restrictions but wanes where commercial networks are already saturated, whereas the transaction-scale channel is largely insensitive to mobility shocks. Heterogeneity tests further indicate stronger gains in non-provincial capital cities and in the eastern and central regions. Overall, the study uncovers a “penetration-inclusion” network logic and provides policy insights for advancing sustainable financial inclusion through optimized terminal deployment, merchant incentives, and diversified scenario design. Full article

The Xiong’an New Area, a newly established national-level zone in China, faces the threat of land subsidence and ground fissure due to groundwater overexploitation and geothermal extraction, threatening urban safety. This study integrates time-series InSAR and GNSS monitoring to analyze spatiotemporal deformation patterns from 2017/05 to 2025/03. The key results show: (1) Three subsidence hotspots, namely northern Xiongxian (max. cumulative subsidence: 591 mm; 70 mm/yr), Luzhuang, and Liulizhuang, strongly correlate with geothermal wells and F4/F5 fault zones; (2) GNSS baseline analysis (e.g., XA01-XA02) reveals fissure-induced differential deformation (max. horizontal/vertical rates: 40.04 mm/yr and 19.8 mm/yr); and (3) InSAR–GNSS cross-validation confirms the high consistency of the results (Pearson’s correlation coefficient = 0.86). Subsidence in Xiongxian is driven by geothermal/industrial groundwater use, without any seasonal variations, while Anxin exhibits agricultural pumping-linked seasonal fluctuations. The use of rooftop GNSS stations reduces multipath effects and improves urban monitoring accuracy. The spatiotemporal heterogeneity stems from coupled resource exploitation and tectonic activity. We propose prioritizing rooftop GNSS deployments to enhance east–west deformation monitoring. This framework balances regional and local-scale precision, offering a replicable solution for geological risk assessments in emerging cities. Full article

Accurate side road detection is essential for traffic management, urban planning, and vehicle navigation. However, existing research mainly focuses on road network construction, lane extraction, and intersection identification, while fine-grained side road detection remains underexplored. Therefore, this study proposes a road segment-level side road detection method based on crowdsourced trajectory data: First, considering the geometric and dynamic characteristics of trajectories, SRDet introduces a trajectory lane-change pattern recognition method based on mutation intervals to distinguish the heterogeneity of lane-change behaviors between main and side roads. Secondly, combining geometric features with spatial statistical theory, SRDet constructs multimodal features for trajectories and road segments, and proposes a potential side road segment classification model based on random forests to achieve precise detection of side road segments. Finally, based on mutation intervals and potential side road segments, SRDet utilizes density peak clustering to identify main and side road access points, completing the fitting of side roads. Experiments were conducted using 2021 Beijing trajectory data. The results show that SRDet achieves precision and recall rates of 84.6% and 86.8%, respectively. This demonstrates the superior performance of SRDet in side road detection across different areas, providing support for the precise updating of urban road navigation information. Full article

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article