It is important to study the coupling relationship between urbanization and water ecosystem service in basin to promote high-quality socio-economic development and ensure water ecological security. As trans-regional linkages within the basin continue to strengthen, the mobility of factors has intensified, the telecoupling interactions between urbanization and water ecosystem service have become increasingly pronounced. Based on constructing an analytical framework for the local coupling and telecoupling relationship between urbanization and water ecosystem service in basin, this study takes the Yellow River Basin as a case study to systematically examine the spatiotemporal evolution characteristics of their coupling relationship from 2000 to 2023 and predicts future development trends. The results show that: 1) The level of urbanization in the basin has continued to rise, showing a clear gradient of downstream > midstream > upstream, with disparities progressively widening. The quality of water ecosystem service remained generally stable, exhibiting a spatial pattern of upstream > midstream > downstream. 2) Urbanization dominates the enhancement of local coupling coordination, while telecoupling simultaneously exhibits spatial dependency and cross-regional efficiency. The spatial pattern of local coupling and telecoupling coordination degree is “downstream optimal, midstream secondary, and upstream poor”, but the gaps among the upstream, midstream, and downstream regions are gradually narrowing. Meanwhile, the spatial combination types in the basin are primarily characterized by “low urbanization-low water ecosystem service” and “low urbanization-high water ecosystem service” under moderate imbalance and basic coordination. 3) In the future, the local coupling and telecoupling coordination degree between the two will steadily increase, though the rate of improvement will vary among the upstream, midstream, and downstream regions. This study provides theoretical support and a scientific basis for implementing precise zoning regulation and governance in basin, thereby promoting high-level coordination between urbanization and water ecosystem service.
Ecological conservation and high-quality development in the Yellow River Basin (YRB) require coordinated management of conflicts among production-living-ecological (PLE) spaces under pronounced upstream-downstream heterogeneity. Dynamic diagnosis reveals the spatiotemporal evolution of such conflicts and the interactive effects of natural and socioeconomic drivers, thereby supporting differentiated governance and territorial spatial-pattern optimization. This study examined the spatiotemporal evolution of PLE space conflicts, identified critical areas for conflict governance from the perspective of urban agglomerations, and quantified the contributions of natural and socioeconomic drivers. Land-use remote-sensing data from 2000 to 2023 were analysed using a spatial-conflict diagnostic model. The model characterized temporal evolution and spatial distribution across the basin, and the resulting conflict patterns were compared among urban agglomerations. Urban agglomerations provided the framework for identifying governance-critical areas. An extreme gradient boosting model combined with Geo-SHAP method quantified the directional trends and relative contributions of the selected drivers. Production-ecological space and ecological space decreased annually, whereas living-production space expanded annually. Spatial conflicts intensified initially and then eased, but increased overall during the study period. Critical areas for conflict governance were concentrated in the Zhongyuan Urban Agglomeration and the Shandong Peninsula Urban Agglomeration in the lower reaches of the basin. Future scenarios showed that conflict levels increased over time. The moderate-development and climate-constrained pathway represented by SSP2-RCP4.5 was more conducive to coordinating socioeconomic development with conflict governance than the other evaluated pathways. Topographic constraints, human activity intensity, and landscape diversity made the largest contributions to conflict variation, while geographic location and greenness were secondary factors. Spatial conflict evolution reflected the joint influence of natural conditions and human activities rather than a single-factor process. The results identify downstream urban agglomerations as priority areas for spatial-conflict governance and establish the need to address the joint effects of natural conditions and human activities in territorial spatial planning, providing a scientific basis for differentiated governance and territorial spatial-pattern optimization in the YRB.
The Yellow River Basin serves as both a vital ecological barrier for China and a crucial corridor for sustainable socio-economic development. A scientific assessment of total factor ecological welfare performance(TFEWP) in this basin is important for both theory and practice. It can deepen understanding of ecological priority and green development, support integrated basin governance, and improve coordinated development pathways. This article expands ecological welfare performance from a total factor perspective. It builds an evaluation framework covering natural resource consumption, environmental carrying pressure, and social welfare output. Using the SBM-DDF model, this study measures TFEWP in the Yellow River Basin from 2010 to 2021. The Dagum Gini coefficient is then used to decompose spatial disparities and identify their sources. The geographical detector method is further applied to examine driving mechanisms from both single-factor and interaction perspectives. Main findings are as follows: 1) TFEWP in the Yellow River Basin as a whole, as well as in its upper, middle, and lower reaches, shows a fluctuating upward trend. Spatially, TFEWP is the highest in the lower reaches, moderate in the middle reaches, and lowest in the upper reaches. 2) Spatial disparity in basin TFEWP shows a fluctuating convergence trend. Intra-regional disparities follow the order of upper reaches > lower reaches > middle reaches. The Gini coefficient of the upper reaches remains relatively high. Inter-regional disparity is the main source of spatial heterogeneity. Difference between the upper and lower reaches is most evident. Further decomposition confirms that inter-regional disparity is the primary driver of TFEWP heterogeneity. 3) From a single-factor perspective, infrastructure, population agglomeration, and technological innovation are key factors. Their effects differ across regions. Environmental regulation plays a dominant role in the upper reaches. Urban greening is most important in the middle reaches. Infrastructure has the strongest influence in the lower reaches. From an interactive perspective, spatial differentiation is shaped by nonlinear synergy among multiple factors. In the upper reaches, interaction between population agglomeration and infrastructure is most significant. In the middle reaches, interaction between population agglomeration and financial development dominates. In the lower reaches, interaction between population agglomeration and technological innovation is most prominent. To promote coordinated improvements in TFEWP, future policies should optimize regional ecological governance strategies and adopt targeted measures for different reaches. Stronger coordination among key factors is also needed.
Inclusive green growth represents a sustainable development approach that seeks to achieve economic growth, social equity, and environmental sustainability. This study takes 60 cities in the Yellow River Basin from 2013 to 2021 as the research subjects. It utilizes the entropy-weighted TOPSIS method and the super-efficiency SBM model with undesirable outputs to measure the level and efficiency of inclusive green growth, and employs the Haken model to investigate the synergy between them, with the aim of analyzing its evolutionary trends and synergistic patterns.The findings reveal that: 1) During the study period, the level of inclusive green growth in the Yellow River Basin showed a fluctuating upward trend, while inclusive green efficiency declined in phases before leveling off. The growth level followed a pattern of ‘lower reaches > middle reaches > upper reaches’, whereas cities with high efficiency were mainly clustered in the lower reaches and a few core cities. 2) Inclusive green growth acts as the order parameter governing the inclusive green development system in the Yellow River Basin, facilitating the system’s co-evolutionary development, whereas the feedback effect of efficiency on growth is hindered by ‘stickiness and resistance’. 3) A three-stage evolution of the basin’s synergy level was observed—‘inverted U-shaped fluctuation, adjustment and restoration, and high-quality transition’—with four types identified: steady improvement, fluctuating adjustment, low-level breakthrough, and locked decline. 4) The spatial evolution exhibited a dynamic trajectory characterized by ‘core agglomeration, radiation diffusion, and adjustment and convergence’. High-value areas remained centered on the southeastern region, with phased expansion and contraction, whereas low-value areas progressively converged toward the northwest. Overall, the spatial differentiation was notable.
Scientific assessment of the supply, demand, and flow trajectories of ecosystem services, together with the formulation of ecological compensation policies, is essential for promoting regional high-quality development. However, existing studies have largely focused on the spatial matching of ecosystem service supply and demand, while the cross-regional flow of carbon sequestration services and its implications for horizontal ecological compensation remain insufficiently explored. This study utilizes NEP data, the population density method, and the supply-demand ratio index to evaluate the supply, demand, and balance of carbon sequestration services in the Qinling Mountains region from 2001 to 2021. By integrating atmospheric transport dynamics with ecosystem service flow theory via the HYSPLIT model, we accurately simulate the dispersion pathways of carbon sequestration service flows and, on this basis, calculate horizontal ecological compensation at the county scale. During 2001—2021, the supply of carbon sequestration services in the Qinling Mountains region increased from 1.13×108 t to 1.80×108 t, while demand rose from 0.78×108 t to 2.31×108 t. The supply pattern exhibits a southwest-high and northeast-low gradient, whereas demand shows an east-high and west-low pattern. CO2 from carbon-demand areas within the Qinling Mountains region mainly disperses northward. Beyond serving internal areas, the carbon-supply zones also provide sequestration services to 15 external regions, including 10 northern and 5 southern beneficiary provinces. The compensation payable by carbon-demand areas within the Qinling Mountains region amounts to 81.04×108 yuan; external regions need to pay 33.39×108 yuan to the Qinling Mountains region supply zones and receive 90.69×108 yuan from the Qinling Mountains region demand areas. The total compensation received by the Qinling Mountains region supply zones is 91.54×108 yuan, and the central government is required to cover 67.80×108 yuan on behalf of paying entities. The proposed compensation framework helps clarify the relationships among service providers, beneficiaries, and compensation payers, thereby enhancing the operational feasibility of cross-regional ecological compensation. This study reveals the cross-regional flow characteristics of carbon sequestration services in the Qinling Mountains region and proposes a compensation mechanism that balances equity and feasibility, thereby providing a scientific basis for transboundary ecological compensation and coordinated ecological governance across administrative regions.
Against the backdrop of “connotative development” emerging as the core guiding principle of new-type urbanization, urban agglomerations, as strategic core regions for national high-quality development, are gradually shifting their spatial expansion mode from “incremental growth” to “stock-based quality improvement.” Scientific assessment and optimization of the spatial expansion efficiency of urban agglomerations is of great theoretical and practical significance for promoting their green, efficient, and intensive development, as well as for improving territorial spatial policies. From the perspectives of green total-factor productivity and the full life cycle of urban development, this study constructs a comprehensive evaluation system for spatial expansion efficiency encompassing both the urban construction and operation stages. Employing the network DEA model, the Malmquist index, and redundancy analysis, it explores efficiency improvement pathways from the dual dimensions of multi-factor input-output and city scale. The results indicate that: 1) From 2000 to 2020, the static efficiency of the Central Plains Urban Agglomeration exhibited an overall fluctuating-declining trend. The inter-city efficiency disparities were remarkable and reached there peak in 2020. The mean efficiency and number of DEA-efficient cities during the construction stage were both lower than those in the operation stage, representing the key constraint on overall expansion performance. 2) The dynamic expansion efficiency declined at an average annual rate of 2.05%, with a greater reduction in the operation stage than in the construction stage, and the technological change index exerted a particularly prominent driving effect. 3) In 2020, the 17 non-DEA-efficient cities showed no insufficiency in desirable outputs but generally presented input redundancy in factors including construction land and labor force, alongside excessive undesirable outputs such as PM2.5 and CO2 emissions. Low resource utilization efficiency and high eco-environmental pressures were the main causes of efficiency decline. Differentiated adjustment strategies combining “scale adaptation and structural optimization” should be formulated based on each city’s input-output structure and scale characteristics.
Based on theories of landscape ecology and related disciplines, this study constructs an ecological resilience evaluation model of “size-density-morphology-function” and examines the spatio-temporal dynamics and drivers of the coordination between new-type urbanization and ecological resilience across 84 cities in the Yellow River Basin from 2010 to 2022. The coupling coordination degree increased steadily over the study period, at an average annual rate of 0.68%, although the overall system remained moderately imbalanced. Spatially, coordination was generally stronger in the west and north than in the east and south, high-high clusters and coordinated cities were concentrated primarily in the upper reaches. Ecological resilience contributed more strongly to coupling coordination than new-type urbanization, with pronounced regional heterogeneity and interaction effects. Per capita green space, nighttime light intensity, and carbon emissions per unit area emerged as the dominant drivers, although both the magnitude and direction of their effects varied substantially across space. These findings support an “external driving-internal interaction-spatial response” mechanism, whereby economic and environmental drivers shape the spatio-temporal evolution of coupling coordination through nonlinear inter-system interactions and spatially differentiated.
Investigated the carbon reduction and pollution control effectiveness, spatial structural characteristics, and influencing factors in 73 cities across the Yellow River Basin from 2003 to 2022 using SBM-DEA model, spatial autocorrelation analysis, and Geographically and Temporally Weighted Regression (GTWR). The results demonstrate that: 1) The overall carbon reduction and pollution control effectiveness in the Yellow River Basin showed an upward trend, with downstream and upstream regions outperforming the midstream region, albeit with low spatial clustering intensity. 2) Spatial distribution of hotspot areas for emission reduction effectiveness shifted from downstream to upstream regions, while coldspot areas remained concentrated in the midstream region. 3) Regarding the influencing factors, energy consumption intensity acts as the primary determinant, exerting a strong negative effect. The share of secondary industry value added in regional GDP and the urbanization rate also show negative inhibitory effects. Conversely, per capita GDP, the proportion of science and technology expenditure in local general public budget expenditure, the enrollment in urban regular higher education institutions, the green coverage rate of built-up areas, and the ratio of completed investment in industrial pollution control to local GDP all exert positive promoting effects. Notably, the total urban year-end population has a negative impact on the middle reaches of the Yellow River Basin, but plays a positive role in the upper and lower reaches. 4) To optimize the synergies of carbon and pollution reduction across cities in the Yellow River Basin, spatial-specific strategic pathways are mandated. The upper reaches require a technology-driven quality improvement paradigm, underpinned by carbon and energy reduction, enhanced technological innovation, and rigorous pollution governance. The middle reaches should transition towards an industrial restructuring and ecological greening paradigm, prioritizing economic transformation, technological advancement, and ecological rehabilitation. Meanwhile, the lower reaches should adhere to an energy conservation and pollution mitigation paradigm, dedicated to curtailing energy consumption, managing pollution, and fostering green development. These findings provide spatially differentiated policy recommendations for coordinated environmental governance across the basin.
Since the implementation of China’s “Sky Net Project”, a massive number of social security surveillance systems in urban public areas—also known as Closed-Circuit Television (CCTV)—have been constructed. These systems have become one of the most common and important means in current Chinese crime prevention and control measures. According to Situational Crime Prevention Theory and Crime Prevention Through Environmental Design theory, after the installation of video surveillance, the monitoring of people and objects in the spatial environment increases the risk for potential offenders, produces a deterrent effect, and ultimately achieves crime reduction. Therefore, the actual application effect of video surveillance has attracted not only the attention of police departments but also widespread concern from scholars all over the world. However, existing research only evaluates its crime prevention effect from a static perspective, neglecting to explore the temporal variation characteristics of its effect. To fill this gap, this article takes Gusu District in Suzhou as a case study,and uses a Difference-in-differences (DID) method to evaluate the temporal trends of theim-pact of police CCTV on overall crime and different types of crime. The empirical results showthat: Over time, the effect of police CCTV in overall crime prevention initially demonstrates anupward trend, followed by a downward one. Regarding different types of crime, the temporaltrends of their preventive effects vary. Specifically, the effect of police CCTV in preventing onthe specific theft of battery of electric cars begins to weaken 12 months after installation, whileits impact on the general theft crime continues for an additional six months. The inhibitoryef-fect on brawls remains remarkably prominent for 30 months. Within the initial six-monthperi-od following the installation of police CCTV, they exert a remarkably pronounced inhibitoryimpact on offenses involving public order disruptions and electric bicycle theft. Nevertheless,during the span from the 6th to the 18th month, their efficacy in curbing electric bicycle theftwanes, whereas the preventive efficacy against disturbing public order crimes endures.Accord-ing to the findings of this study, periodically adjusting the angle and direction of videosurveil-lance cameras will help enhance the long-term effectiveness of police video surveillance incrime prevention.
The spatiotemporal selection of criminal behavior is an important topic in crime geography. Characterized by a dynamic sequence of behaviors, serial crime provides a useful entry point for examining the spatiotemporal decision-making mechanisms of individual offenders. Focusing on serial theft offenses committed in Changchun between 2012 and 2019, this study measures the time intervals and spatial distances between consecutive offenses to characterize their spatiotemporal relationships. K-means clustering is employed to identify distinct spatiotemporal behavioral patterns based on the interaction between the temporal and spatial dimensions. An XGBoost model is subsequently constructed, and the SHAP method is applied to interpret the factors associated with each pattern. The results identify 4 spatiotemporal behavioral patterns of serial crime in Changchun: “short-term proximity”“flash raid”“latent lurking” and “cross-regional planning”. Among them, “latent lurking” is the predominant pattern. The spatiotemporal decisions of serial offenders are closely associated with offense-related gains and behavioral experience. Specifically, offenses involving larger stolen amounts are more likely to correspond to long-distance patterns that entail higher mobility costs. This finding suggests that greater offense-related gains may partly compensate for the spatial resistance associated with longer-distance offending. By contrast, offenders who consistently target the same type of location tend to adopt “short-distance” patterns involving relatively lower temporal and spatial costs. Offenders acting in groups are more likely to exhibit the “flash raid” pattern. In addition, offenders with different individual attributes exhibit differentiated pattern preferences: female offenders are more likely to exhibit short-distance patterns, whereas offenders with prior criminal records are less inclined to adopt the “latent lurking” pattern. By identifying behavioral patterns through the interaction between temporal and spatial dimensions, this study reveals the complexity of offenders’ decision-making processes. It further shows that these spatiotemporal patterns can be understood as the outcomes of dynamic trade-offs between offense-related gains and behavioral experience under the constraints of individual attributes, thereby providing a more detailed understanding of serial offending from a rational choice perspective.
Against the backdrop of rapid population ageing and the widespread diffusion of digital technologies, telecommunications and online fraud victimization among older adults has emerged as a pressing social challenge in ageing societies. While existing studies have focused primarily on individual-level determinants, insufficient attention has been paid to how the built and social environments—particularly community contexts—shape victimization risk. Integrating Routine Activity Theory, Social Disorder Theory, and Lifestyle Theory within an “Environment-Activity-Victimization” framework, this study adopts a geographical perspective to examine how the built and social environments affect telecommunications fraud victimization among older adults. A survey of 1 012 older adults (including 171 victims) was conducted across 45 communities in central Guangzhou, China, and multilevel logistic regression models were developed to identify the individual- and community-level determinants of victimization. The results reveal that victimization is jointly shaped by individual and community characteristics, with individual-level factors playing a more prominent role. At the individual level, better physical and mental health significantly reduce the likelihood of victimization, whereas low self-control in daily life is associated with a significantly higher risk. At the community level, neighbourhood committees, which function as a form of semi-formal control, significantly inhibit victimization; in contrast, collective efficacy, a higher proportion of agricultural residents, a higher degree of population ageing, and greater density of leisure facilities are associated with elevated victimization risk. Notably, the positive association between collective efficacy and victimization runs counter to conventional expectations, underscoring the complex and potentially paradoxical role of community governance in telecommunications fraud prevention. Theoretically, this study extends Routine Activity Theory from physical space to telecommunications space and advances geographically informed explanations of fraud victimization. Practically, the findings support community-based, targeted interventions—such as strengthening the semi-formal control capacity of neighbourhood committees and delivering differentiated anti-fraud education—to protect urban older adults from telecommunications fraud.
This study examines how innovation cooperation networks shape urban entrepreneurial vitality, with particular attention to the underlying mechanisms from both intra-city and inter-city perspectives. By matching and integrating micro-level data on authorized invention patents and business registrations with city-level data, we construct indicators to measure urban urban innovation cooperation networks and entrepreneurial vitality. A two-way fixed effects model is employed to rigorously examine how innovation cooperation networks, both within cities and across cities, contribute to urban entrepreneurial vitality, with particular attention to the underlying mechanisms through which these networks exert their influence. In addition, this study investigates the role of internet development and its interaction with these networks in shaping entrepreneurial activity. Empirical results indicate that both intra-city and inter-city innovation cooperation networks significantly promote urban entrepreneurial vitality. Moreover, mechanism tests reveal pronounced synergistic effects arising from the interaction between these two types of networks, underscoring their joint contribution to entrepreneurial dynamism. The findings further show that internet development positively moderates the relationship between innovation cooperation networks and urban entrepreneurial vitality, thereby amplifying the positive effect of innovation cooperation networks on entrepreneurial vitality. Further analysis of the underlying mechanisms indicates that intra-city innovation cooperation networks primarily enhance entrepreneurial vitality by promoting technology agglomeration, thereby fostering local innovation and the clustering of resources. In contrast, inter-city innovation cooperation networks boost entrepreneurial vitality through talent agglomeration, facilitating cross-regional knowledge exchange and skill development. These complementary effects highlight the multifaceted ways in which innovation cooperation networks strengthen urban entrepreneurial ecosystems. Overall, this study provides empirical evidence and policy implications for leveraging innovation cooperation networks to enhance urban entrepreneurial vitality. Policymakers and urban planners should capitalize on the synergistic potential of intra-city and inter-city networks, alongside internet development, to foster more dynamic entrepreneurial environments. By strengthening both local and cross-regional innovation cooperation, cities can improve competitiveness and support long-term economic vitality.
In the digital era, against the dual backdrop of the maritime power strategy and the digital-real integration strategy, the high-quality coordinated development of pseudo and reality human settlements in coastal cities serves as a key accelerator for the urbanization process. This study is based on the research context and theoretical framework of the “Three-State” human settlements. Using methods such as the entropy weight method, coupling coordination degree model, and geographic detector, it empirically examines the spatiotemporal development characteristics and coupling coordination patterns of 53 coastal cities in China from 2011 to 2022, and explores their influencing factors and driving mechanisms. The results show that: 1) In terms of development trends, the 53 coastal cities demonstrate rapid and high-quality development, with continuous improvement in all aspects of the five major systems of human settlements, showing a positive development trend and a gradual reduction in spatial disparities; 2) The coordination between pseudo and reality human settlements is generally in a state of mild imbalance but exhibits a fluctuating upward trend, with gradual enhancement and phased leaps in coordination, presenting a “multi-point blooming” and “center-radiation” spatial effect by 2022; 3) Regarding driving mechanisms, socio-economic development constitutes the dominant driving factor, public infrastructure construction serves as the fundamental supporting force, the tool system is increasingly prominent as an emerging driving force, and the information system plays a significant mediating role. By positioning coastal cities as the main subject, this study constructs a new theoretical framework for human settlements, which contributes to enriching and improving the theoretical system of human settlement geography. It provides scientific basis for the planning and construction of coastal cities, and offers typical cases and decision-making references for formulating measures to coordinate and unify the path towards high-quality development.
By optimizing the fishery industrial layout and urban functional positioning, the fishery economic network provides robust support for the sustainable and high-quality development of the fishery economy. This study constructs China’s fishery economic network using data from A-share listed fishery enterprises and their subsidiaries between 2011 and 2024. Employing social network analysis and geographic detector methods, it examines the spatiotemporal evolution of network structure and the impact of multidimensional proximity on the evolution of urban connection intensity. Findings indicate: 1) The hierarchical structure of China’s fishery economic network is constrained by distance, with higher-level cities exhibiting fewer connections. 2) The network exhibits breadth expansion, with increasing inter-city flow efficiency and intensified economic exchanges. 3) Pronounced regional imbalances are evident, featuring misalignments between certain city nodes and their local cluster sizes, while Guangzhou demonstrates exceptional bridging connectivity. 4) Social and geographical proximity significantly enhance the Chinese fishery economic network, while the explanatory power of institutional proximity for inter-urban connections gradually diminishes. Non-linear, mutually reinforcing interactions exist between different proximity factors. This research aims to inform urban network studies from an enterprise connectivity perspective and the development of integrated land-sea modern fishery systems, thereby contributing to the high-quality development of China’s fishery economy.
Against the backdrop of the coordinated advancement of the “Dual Carbon” goals and the Digital China strategy, clarifying the mechanisms through which the spatial distribution of digital factors influences the green and low-carbon transition holds significant theoretical and practical importance. Based on panel data from 282 prefecture-level and higher cities in China from 2010 to 2023, this study assesses the current status of urban digital proximity and green energy efficiency and analyzes the spatiotemporal evolution characteristics of both. Using a mediation effect model and the Spatial Durbin Model (SDM), this study examines the mechanism through which urban digital proximity influences green energy efficiency, as well as potential spatial spillover effects. The findings reveal that: 1) Digital proximity can significantly improve local green energy efficiency, and this conclusion remains valid after endogeneity and multidimensional robustness tests; 2) Digital proximity indirectly improves energy efficiency through 3 mediating pathways: stimulating green technological innovation, promoting the upgrading of industrial structure, and optimizing regional resource allocation. The mediating effects of these 3 channels account for 15.6%, 23.9% and 18.8%, respectively; 3) Digital proximity exhibits positive spatial spillover effects: the digital supply advantages of neighboring cities can drive improvements in local energy efficiency. These spillover effects exhibit a distinct distance-decay pattern, with the highest intensity within 200 km and no longer significant beyond 500 km; 4) This enabling effect exhibits significant regional heterogeneity. The eastern, central, and southern regions, as well as national-level urban agglomerations, demonstrate stronger enhancing effects, exhibiting a pattern of decreasing gradients and club convergence. Green energy efficiency and digital proximity are highly spatially coupled; however, the overall national energy efficiency level remains low, and regional development imbalances are prominent. Based on the research findings, this paper proposes the following differentiated regional governance strategies: 1) The central government should coordinate the spatial layout of the digital industry and prioritize the interconnection of digital infrastructure within a 200 km radius of urban agglomerations; 2) Urban agglomerations in the eastern and southern regions should focus on the deep integration of digital and green technologies, while central, western, and northern regions should leverage “digital enclaves” to benefit from the technological dividends of core areas; 3) A cross-regional green digital trading platform should be established to facilitate the 3 enabling channels of innovation, industry, and resource allocation; 4) Urban digital-green synergy alliances can improve cross-regional ecological compensation and factor-sharing mechanisms, fully unleash the spillover benefits of the digital space, and support the systematic green and low-carbon transition of cities nationwide.
Exploring the spatiotemporal pattern and spillover effects of digital economy driven integrated urban-rural development is of great importance in promoting the construction of new urban-rural relationships and high-quality urban-rural development. Based on the connotation, an evaluation index system was constructed. Multiple econometric methods were used to analyze the spatiotemporal pattern evolution characteristics and spatial effects of digital economy and integrated urban-rural development in Shandong Province during 2014—2022. The main research conclusions are as follows: 1) During 2014—2022, the level of digital economy and urban-rural integration showed a fluctuating upward trend, but the coefficient of variation of digital economy and urban-rural integration decreased, indicating that regional differences continue to narrow, reflecting the coordinated development of digital economy and integrated urban-rural development; 2) The digital economy and integrated urban-rural development showed spatial differentiation characteristics, with high-level areas of digital economy and urban-rural integration in a roughly inclined “H”-shaped distribution. The spatial correlation between the digital economy and urban-rural integration is mainly characterized by positive agglomeration, reflecting the obvious spatial dependence between the digital economy and urban-rural integration; 3) The digital economy has a significant positive effect on the urban-rural integration, but the spatial spillover effect on the overall region and surrounding areas is not significant. The level of economic development, government support, opening-up, allocation of transportation resources, and high degree of industrial structure all have a positive regulatory effect. The research results expand the explanatory dimensions of digital economy theory in the field of urban-rural integration, providing theoretical support and case studies for the development of urban-rural integration and rural revitalization in the digital economy era.
Existing studies of metro commute accessibility are often constrained by a station-centric perspective, overlooking how full travel-chain time costs interact with socio-spatial stratification. Taking central Zhengzhou as the study area, this article integrates multi-source spatiotemporal data to construct a multimodal metro commuting time-cost model that captures the entire travel chain, including first-mile access, in-station movement, inter-station travel, and last-mile egress. Lorenz curves and Gini coefficients are subsequently used to examine the accessibility and spatial equity of metro commuting for resettlement housing residents. The results show that first-mile access is the primary bottleneck limiting commuting efficiency for residents of resettlement housing. Accessibility exhibits a pattern of concentric collapse and spatial polarization, while residents of low-rent resettlement housing in peripheral areas face a form of dual deprivation. From the full travel-chain perspective, the overall urban Gini coefficient remains within a relatively favorable range, but clear spatial differentiation persists across rent groups and ring-road zones. Electrified feeder modes, especially e-bikes, can improve equity to some extent. Compared with traditional models, the full travel-chain approach produces accessibility estimates that are on average 15.3% higher and Gini coefficients that are 13.3% higher, suggesting that it captures both accessibility and equity more realistically by incorporating previously neglected commuting segments. Overall, the full travel-chain perspective offers a more comprehensive understanding of the social equity implications of rail transit systems and provides a stronger basis for optimizing jobs-housing relationships and urban resource allocation.
Poverty alleviation relocation is a large-scale resettlement initiative led by the Chinese government to achieve multiple objectives, including poverty eradication, economic development, and ecological protection. As a complex social process, it represents a profound transformation from subsistence-oriented agrarian livelihoods to a consumption-driven market economy. Existing research has mainly focused on explaining, at the macro institutional level and the meso-community governance levels, why relocated migrants often encounter difficulties in achieving social integration. Much less attention has been paid to the theoretical question of how migrants negotiate structural constraints through everyday spatial practices and thereby regain social embeddedness. To address this gap, this study adopts the spatial perspective of the nearby (Fujin in Chinese) and draws on a social infrastructure lens to examine how relocated migrants respond to structural challenges in their new environment and reconstruct the nearby. The nearby is conceptualized as a dynamic, lived spatial field rooted in migrants’ embodied experiences. It includes the relational networks formed through social interaction, the functional provision of accessible resources, and the symbolic and emotional bonds that connect people to one another and to place. This paper takes Jinping Community in Pingli County, Shaanxi Province, as a typical case to examine migrants’ agentic practices of creating or transforming spaces of the nearby. The findings indicate that: 1) Spaces of the nearby among relocated migrants serve triple functions, namely self-maintenance, social connection, and livelihood generation, while exhibiting a multi-core and spatially contiguous topological pattern; 2) The formation of such spaces rests on the interplay among four dimensions: nearby consciousness, nearby action, nearby subjects, and nearby capability; 3) The production of nearby is a dynamic process characterized by friction and negotiation, through which migrants engage market forces and administrative power through transversal logics to reshape spatial orders and foster institutional innovation. The study elucidates the embodied, mobile, social, and affective dimensions of the nearby as a spatial scale and demonstrates the efficacy of qualitative GIS in exploring the spatial expressions and implications of everyday sociocultural phenomena.
The development and utilization of natural rubber have profoundly shaped the formation of the modern industrial system, while the evolution of rubber plantation patterns has significantly influenced global resource allocation and regional development dynamics. Drawing upon panel data and historical documents, this study employs trend analysis, the concentration index, and the center-of-gravity migration model to systematically examine the spatiotemporal evolution of the global rubber plantation industry over nearly 300 years. The analysis focuses on temporal changes in global plantation area and concentration, as well as spatial shifts in major production regions and the overall center of gravity. The results indicate that: 1) The global rubber plantation pattern has undergone a transformation from a unipolar to a multipolar structure, with the major production region shifting from the Amazon Basin in South America to Southeast Asia during the 19th—20th centuries, where the concentration of rubber plantations in Asia increased from 24.52% to 92.06%; 2) Since the 1960s, the global concentration index has declined by 8.55%, reflecting a shift from a highly concentrated to a more diversified and dispersed configuration, characterized by the rapid expansion of rubber cultivation in the Lancang–Mekong River Basin and the growing shares of Africa and the Americas; 3) The center of gravity of global rubber plantations has generally migrated northwestward, accompanied by a trend toward spatial dispersion; 4) In recent years, rubber cultivation in Asia has continued to expand, while the Gulf of Guinea in Africa and Brazil in South America have shown signs of recovery, whereas some traditional production regions have contracted. These changes collectively indicate a gradual restructuring of the global rubber plantation pattern, with emerging production regions gaining importance alongside the contraction of some traditional regions. Overall, the global rubber plantation industry is experiencing a profound transformation—from unipolarity to multipolarity and from high concentration to dispersion. This dynamic restructuring not only reshapes the international division of labor and regional economic linkages but also brings new challenges, including shifts in land use, intensified ecosystem pressures, and increasing demands for environmental governance.
Drought poses an increasingly severe threat to summer maize production in the Huang-Huai-Hai Plain. Due to the varying responses of summer maize to water stress across different growth stages, there is an urgent need to systematically assess future drought risks to summer maize production at the growth-stage scale, in order to support refined agricultural disaster prevention and mitigation. Therefore, based on the disaster risk system theory, this study constructed a drought risk assessment framework from four dimensions: hazard, exposure, vulnerability, and disaster prevention capacity. The assessment distinguishes between irrigated and rainfed agricultural systems to systematically estimate the drought risk for summer maize at different growth stages under future climate conditions in the Huang-Huai-Hai Plain. The results indicate that: 1) High-risk areas are mainly distributed in the central part of the Huang-Huai-Hai Plain and around the Shandong Peninsula, with the highest drought risk occurring during the tasseling-milking stage. Compared with irrigated conditions, under rainfed farming, the area of medium-high and high-risk zones increased significantly, while the area of low-risk zones decreased; the central region remained a high-risk zone, and small areas of medium-high risk emerged in the northwest. 2) During the jointing-tasseling and tasseling-milking stages, the comprehensive risk under irrigated agriculture was significantly lower than that under rainfed agriculture, with high-risk areas mainly located in the central-eastern and southeastern parts of the study area. 3) The tasseling-milking stage remained the growth stage with higher drought risk. Under the SSP126 scenario, high-risk areas expanded northward in the near term but showed some alleviation by the mid-term. In terms of changes in high-risk area across growth stages, the high-risk area during the sowing-jointing stage increased by 32.04% in the near term. In the long term, the high-risk area during the milking-maturity stage and sowing-jointing stage increased by 30.43% and 25.62%, respectively.
