The administrative hierarchy of the city in China determines its ability of mobilizing resources and the direction of migrations, and it is also the direct subjects of policy implementation. Previous literature has rarely analyzed migrations from the perspective of urban administrative hierarchy. Using data from the 2017 China Migrants Dynamic Survey, this study explores the patterns of migration across urban administrative hierarchy and the influencing factors of destination choice. The results show that according to the urban administrative hierarchy, upward migrations are dominant. Spatially, inter-regional migration to the eastern region is a prominent feature. For the population that has migrated multiple times, subsequent migrations are dominated by horizontal and intra-regional migrations, with the proportion of downward migrations increasing and exceeding that of upward migrations. In the first migration, ordinary prefecture cities and provincial capital cities are preferred. In the subsequent migrations, the proportions of county-level cities (counties), separately planned cities and directly-administered municipalities have increased, which reflect repositioning of population after the first migration. Economic profits are the main driving force of migration, the socio-economic attributes and hukou-registered places affect the choice of destinations, which reflect the migrants' employment competitiveness, employment preferences, life cycle and path dependence on hukou-registered places. The choice of destination is also related to the migration scope, provincial capital cities are being preferred in intra-provincial migrations, while directly-administered municipalities are most likely to be chosen in inter-provincial migrations. This paper provides evidence for the theory of population migration that urban administrative hierarchy works, which shows a different pattern from Ravenstein's laws of step migration, and deepens the connotation of push-pull theory. The findings of the study are of revelatory value for the implementation of the new urbanization policy with counties as important carriers.

Population aging has become a major issue affecting the socio-economic sustainable development worldwide. In response to China's national situation of "getting old before getting rich", comprehensively improving the level of home-based elderly care services is an inevitable way to meet the multi-level elderly care needs. Based on the public or quasi-public characteristics of elderly care service facilities, a basic framework has been constructed from the perspectives of demand and supply. It takes into account the heterogeneity of elderly care needs and the balance between fairness and efficiency with the core of service facilities accessibility. The data of home-based elderly care needs came from questionnaire surveys and interviews with 545 elderly people aged 60 and above from 2021 to 2023 in Beijing, which included the needs for daily dining, cultural and sports activities, medical and health services and daytime care. The other data included 1 km population grid, permanent population and population ratio of different age groups, and POI of elderly care service facilities. By using SPSS statistical analysis and two-step floating catchment area method, the heterogeneity of home-based elderly care needs were analyzed and applied in evaluating accessibility of different elderly care service facilities. Dagum Gini coefficient and bivariate spatial autocorrelation method were used to analyze the spatial fairness and efficiency of comprehensive accessibility. The study found that (1) the individual attributes of elderly people certainly determine the heterogeneity of elderly care needs. Retirement status, census register, educational level, occupation (before retirement) and age are the important factors. (2) When the heterogeneity of elderly care needs was taken into account, the positive correlation between the accessibility and the satisfaction survey results is more significant. Compared to neglecting the heterogeneity, the result better revealed the matching relationship between service facilities and elderly care needs as well as significant spatial differences. (3) The comprehensive accessibility of home-based elderly care service facilities shows spatial unfairness with a gradually decreasing regional difference from the city center to the suburbs. However, the allocation of service facilities in most areas has taken into account utilization efficiency.

Financial agglomeration and economic resilience have become the hot and frontier field in economic geography. It is of great theoretical and practical significance to study the influence of financial agglomeration on urban economic resilience. Based on the analysis of relevant theories and research progress, this paper measures the level of financial agglomeration and economic resilience of 285 cities at or above the prefecture level from 2008 to 2021, and analyzes the overall characteristics, development process and spatial pattern characteristics of the above indicators. An econometric model is constructed to study the influence of financial agglomeration on economic resilience. The findings are as follows: (1) At the initial stage of the study, financial agglomeration mainly occurred in the central cities of Beijing-Tianjin-Hebei region, Yangtze River Delta and Pearl River Delta; Subsequently, the degree of financial agglomeration in some cities in the central and western regions increased. The spatial distribution of financial agglomeration showed a diffusion phenomenon, from point-like distribution to blocky distribution. (2) The high value of urban economic resilience is mainly distributed in the central and western regions of China, and shows a trend of transferring from north to south and west to the central region. The overall level of economic resilience in the northeast region is not high, and the level of economic resilience declines significantly at the end of the study. (3) The full sample regression results show that, at the level of prefecture-level cities, the direct impact of financial agglomeration on urban economic resilience presents a significant inverted U-shaped relationship of first rising and then declining. The influence of financial agglomeration on economic resilience has a positive spatial spillover effect, and the local economic resilience will be positively weighted by the level of financial agglomeration in the surrounding areas. (4) The estimation results of the intermediary effect model show that with the improvement of the level of financial agglomeration, the industrial structure will deviate from the secondary industry, and the change of industrial structure can become the intermediary variable of financial agglomeration affecting the urban economic resilience. (5) Regional heterogeneity test results show that financial agglomeration has a negative spillover effect on economic resilience in the eastern region; The spatial spillover effect of the western and northeast regions is weak, and the spillover effect is relatively not obvious. The test of city type heterogeneity shows that for all types of cities, the direct promoting effect of financial agglomeration on economic resilience is significant, but the promoting effect is manifested as resource-based cities and old industrial cities > general cities > provincial capitals and sub-provincial cities.

The urban system is essentially a multilayer network formed by multiple single-layer networks that evolve and interact with each other. However, there is a notable paucity of empirical studies investigating interurban networks from a multiplexity-based perspective. This study addresses this gap by empirically investigating the structure and evolution of China's multilayer urban network from 2005 to 2020 across four key dimensions: multilayer centrality, interlayer correlations, multilayer hinterlands, and multilayer clique communities. The multilayer urban network is constructed from three distinct single-layer networks: the network of top 500 public companies, the patent transfer network, and the air flight network. This study yields four key findings. First, the multilayer centralities of cities exhibit a sequential growth trend, with the self-organizing feature mapping (SOFM) method identifying nine distinct evolutionary paths. Spatial dependence and convergence have continuously strengthened, with cities of high centralities clustered in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta, the Shandong Peninsula, and the west coast of the Taiwan Strait. Second, a positive interdependency exists among different types of single-layer networks. The spatial pattern of edge interdependency forms a diamond shape, with the Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta, and the Chengdu-Chongqing region as vertices. Node interdependency exhibits a trend towards decentralization, with a more pronounced hierarchical structure and spatial independence compared to multilayer centralities. Third, multilayer hinterland has rapidly expanded beyond geographical proximity, with the number of hinterland relationships increasing from 255 to 1814. Core cities within major urban agglomerations are embedded in the hinterlands of multiple cities, resulting in intertwined and overlapping multilayer hinterlands. Additionally, the decentralization of cities' power within multilayer hinterlands has become increasingly evident. Fourth, the number of cities in multilayer clique communities (when k=5 and m=2) increased from 14 to 168. These communities increasingly exhibit overlapping and mosaic characteristics, driving the evolution of China's multilayer urban network into a core-periphery structure. The study enriches the existing literature by exploring the coupling and diversity of network relationships and analyzing the structure and evolution of urban network from a multiplexity perspective. It also fills a critical gap in the analytical framework by presenting a novel approach for analyzing multilayer urban networks. The findings offer important implications for policymakers. In the future, the Chinese government should pay close attention to the multidimensional differences in cities' positions within multilayer urban networks, and give full play to the role of functional urban organizations that transcend geographical proximity - especially multi-factor flow channels and multilayer communities - to facilitate the efficient flow and optimal allocation of resources on a national scale.

Establishing external collaboration linkages is essential for cities to foster technological diversification. However, the effectiveness of these linkages relies on whether external technologies can effectively integrate with local ones. Most existing studies treat external collaborations as "homogeneous" linkages, overlooking the diverse technological contributions that different external partners might offer and their varying impacts on local innovation. To address this gap, this paper utilizes patent data from the China National Intellectual Property Administration (2001-2020) to examine how the technological heterogeneity in external collaboration linkages affects technological diversification in cities of the Yangtze River Delta (YRD). The study reveals several key insights: (1) Regarding the evolution paths of technological diversification, core cities in the YRD are shifting from related to unrelated diversification, whereas peripheral cities are moving in the opposite direction. These dynamics are shaped by the cities' varying technological foundations, economic modes, and policy implementations. (2) Regarding the heterogeneity of external technologies, we observe that core cities tend to obtain external technologies that are highly related with local knowledge bases, focusing on complex, cutting-edge fields. In contrast, peripheral cities tend to engage with external technologies that are less related with local knowledge bases, and are often concentrated in traditional, low-end areas, indicating varying technological focuses and approaches of different cities in forming external collaborations. (3) Regression analysis indicates that the mere quantity and geographical scope of external collaborative connections do not guarantee whether a city is able to achieve technological diversification. Instead, the degree to which external technologies align with local capacities is crucial. Strong relatedness between external and local technologies could promote related diversification, while weaker relatedness might encourage unrelated diversification. This analysis underscores the importance of recognizing and leveraging the heterogeneity in external collaborations to enhance local technological diversification effectively.

Revealing the adaptive relationship between public cultural service supply and people's well-being constitutes an important issue in building a cultural power and enhancing people's quality of life. It is also a crucial link in promoting common prosperity. Based on the panel data of 26 cities at or above the prefecture level within the Yangtze River Delta Urban Agglomeration from 2012 to 2022, this study examines the adaptation mechanism between public cultural service supply and people's well-being, constructs the evaluation index systems of the two, and employs kernel density estimation, trend surface analysis, and other methods to depict the spatio-temporal evolution characteristics. The spatio-temporal adaptation relationship and interaction characteristics between the two systems is explored through a comprehensive fit model, spatial center of gravity model, and exploratory spatio-temporal data analysis. The results show that: (1) During the study period, public cultural service supply and the people's well-being index of the Yangtze River Delta Urban Agglomeration rose dynamically. The development level differed significantly between the east and the west, and the inter-city disparity of the public cultural service supply index tended to converge, while the disparity of the people's well-being index continued to expand. (2) The distance between the center of gravity of public cultural service supply and people's livelihood initially increased and then decreased. The overall adaptation level of the study area rose amid fluctuations, presenting an evolution process of "low-level coupling - run-in adjustment period - high-level adaptation". The public cultural service supply has not formed a benign adaptation relationship with social well-being and health well-being. (3) The spatial correlation pattern between the public cultural service supply and people's well-being shows a certain transfer inertia, featuring strong path dependence and spatial locking characteristics, and the regional synergy effect is not prominent. The study can offer a geographical interpretation for public cultural service to enhance people's well-being and provide a scientific reference for formulating differentiated cultural development plans during the 15th Five-Year Plan period (2026-2030).

In the context of the construction of Healthy China, the configuration of sports facilities from the environmental justice perspective (EJP) is important for enhancing the quality of life, health equity and sustainability of cities. How to embed the EJP to guide the optimization of the layout of sports facilities has emerged as a key focus. This paper constructs a research framework of "benefit evaluation-pattern mechanism-governance response", explores the feasibility of analyzing the spatial benefit of urban sports facilities (SBSF) while considering environmental "distribution" justice and spatial governance while considering environmental "distribution-recognition-ability-participation" justice, which is empirically analyzed in the context of Changsha, Hunan province. The conclusions can be drawn as follows: (1) Enhancing SBSF with the EJP involves material (corresponding to distributive justice), institutional (corresponding to recognition and ability justice) and organizational layers (corresponding to participation justice). (2) The social equity (SE), functional well-being (FW) and environmental health (EH) benefits of sports facilities in Changsha are all at low to medium values. The correlation between SBSF is in weak coordinated and uncoordinated development. (3) The structural differentiation of Changsha's SBSF is the result of a combination of urban material conditions, institutional conditions, market relations and community autonomy. (4) Due to the need to improve the spatial benefits of SE-FW-EH coordination, Changsha can form a zoning and categorization governance strategy according to environmental "distribution-recognition-ability-participation" justice in eight categories: low-benefit, SE benefit, FW benefit, EH benefit, SE-FW benefit, FW-EH benefit, EH-SE benefit and coordinated benefit. This study is an attempt to construct a theoretical framework for evaluating the SBSF based on the EJP toward the SDGs. The indicator design, evaluation ideas and classified policy practices proposed by Changsha as empirical evidence can provide some references for the optimization of the layout and spatial governance of facilities in other cities.

The future industry serves as a critical platform for cultivating new quality productivity forces. Based on panel data of 284 prefecture-level and above cities in China, this study analyzes the spatio-temporal characteristics of future industry enterprise entry. On this basis, the impact effects and mechanisms of the national new generation artificial intelligence innovation and development pilot zones on such entry are empirically explored. The findings are as follows: (1) From 2011 to 2022, the number of future industry enterprises entering the market in China shows an upward trend, with future information industry and future manufacturing industry dominating the landscape. The spatial distribution of future industry enterprise entries gradually evolves from a pattern of "high in the east and west, with a collapse in the central part" in 2011 to a “two-tier echelon structure of east and central-west regions" by 2022. (2) The pilot zone policy can significantly promote the entry of future industry enterprises. (3) Heterogeneity analysis shows that pilot zone policy exerts a stronger promotional effect on future industry enterprise entry in the central and western regions, normal-grade cities and low-policy-intensity cities compared to the eastern region, higher-grade cities, and high-policy-intensity cities. (4) Mechanism tests indicate that the pilot zone policy promotes future industry enterprise entry mainly by facilitating the clustering of breakthrough technologies, attracting inflows of venture capital, and promoting the clustering of talents. (5) The spillover range of the pilot zone policy in attracting future industry enterprises is approximately 100 km. Compared to pilot zones in the central and western regions, normal-grade cities, and low-policy-intensity cities, those in the eastern region, higher-grade cities and high-policy-intensity cities exhibit a broader spillover range of policy. The study provides empirical supports for optimizing future industry layouts and advancing new quality productive forces, as well as enriching the research perspectives of economic geography on enterprise location decisions.

The global value chain (GVC) is a key force shaping the international division of labor and an important perspective for understanding global economic dynamics. This paper constructs a long-term global value chain network dataset based on multi-regional input-output tables and input-output analysis techniques. By integrating advanced network analysis algorithms such as core-periphery profile, disparity filter, and simulation attacks, this study characterizes the macrostructure and spatiotemporal evolution of the GVC network. The paper analyzes the topological structure features of the GVC network and measures its structural resilience and evolutionary characteristics in multiple dimensions. The research findings are as follows: (1) The value flow scale of major global economies forms a hierarchical structure, and value distribution exhibits a highly spatially uneven characteristic. The global value chain network has been expanding and densifying, with the value flow scale in East Asia increasing, evolving from a "dual-center" structure of Europe and North America to a "tri-polar" structure of Europe, North America, and East Asia. (2) The core-periphery structure of the GVC network is significant, and the network position of a node is determined by both the scale of its participation in the global value chain and the degree of diversification of its value links. Countries such as the United States, Germany, the United Kingdom, France, Italy, the Netherlands, and Spain remain at the core, while Asian countries such as China, Japan, India, and the Republic of Korea are gradually rising. (3) The backbone structure of the GVC network has shifted from a single convergence core centered on the United States to a dual-core system driven by China and the United States, with Europe and Japan playing a stabilizing role in the network structure. Over time, the backbone structure has evolved with a trend of eastward shift and increasing globalization characteristics. (4) The resilience level of the global value chain network is generally limited, shows a four-stage evolutionary characteristic taking international impact events as turning points, and key economies such as the United States, Germany, the United Kingdom, France, Italy, Russia, Japan, China, and India have strong influences on network resilience. Based on the research conclusions, this paper discusses the node and structural characteristics of the global value chain network and proposes potential measures to enhance China's resilience and position within the network, aiming to provide insights for understanding the dynamics of economic globalization in the new era and optimizing China's global value chain participation strategy.

As crucial nodes in the illegal wildlife trade and trafficking network, transportation hubs play an important role in combating wildlife crime globally. Based on the data of China Judgements Online, this study utilizes mathematical statistics and spatial analysis to investigate wildlife trafficking patterns and their differentiation mechanisms involving transportation hubs in China from 2005 to 2019. It is found that: (1) The inter-annual variation in wildlife trafficking cases involving transportation hubs presents an 'M-shaped' pattern, with the inter-month occurrence peaks in January and April, and the intra-month peak at the beginning of the month. (2) Spatially, the distribution of wildlife trafficking involving transportation hubs exhibits a decline pattern from east to west: "gathering in coastal and border regions, scattering in central regions and sparse in the northwest", characterized by a main concentration of air transport in Beijing, Guangdong, and Shanghai, while road transport is concentrated in Yunnan, Guangxi, and Guangdong. (3) The wildlife trafficking involves 51 families of species, with a focus on elephants, pangolins, rhinoceroses, and bears. Airports and customs ports tend to facilitate the disassembly and transport of large animals, while inspection checkpoints, service areas, and toll stations are more likely to handle live transport of small to medium-sized animals. (4) The patterns of wildlife trafficking vary across different transportation hubs: airports and customs ports favoring luggage and postal concealment as well as disguise techniques, while road inspection checkpoints, toll stations, service areas, train stations and bus terminals mainly relying on luggage and vehicle concealment. This differentiation mechanism reflects the traffickers' rational adaptation: choosing the way of trafficking based on origin-destination pairs and species categories, determining the trafficking routes depending on regional law enforcement efforts, and then tailoring concealment strategies to the characteristics of each transportation hub on the way. Finally, this paper combines the situational crime prevention theory to construct a prevention strategy framework of wildlife trafficking in China from five dimensions.

The growing recognition of bidirectional urban-rural resource flows reveals the inadequacy of the traditional urbanization model, which conceptualizes development as a one-way rural-to-urban transition, in explaining the complex evolution of county-level rural-urban relations. This study proposes an "Urbanity vs. Rurality × Development" double pyramid framework that unifies villages and communities within a single assessment system, enabling a comprehensive analysis of rural-urban relations. Using villages and communities in Shanting district, Zaozhuang city as the basic evaluation units, this study draws on multi-source data, to develop a methodology for assessing individual and network indices through comprehensive evaluation and social network analysis; and then it conducts a three-level spatial structure analysis of the study area via a "grading-categorization-zoning" approach. The results are shown as follows. (1) Within the individual index of Shanting district, urbanity exhibits a multi-polar and scattered distribution, whereas rurality forms contiguous high-value clusters across the plains. Development is shaped by multiple interacting factors, resulting in an overall spatial equilibrium accompanied by localized dispersion. (2) After accounting for village-community network connections, the three-dimensional indices reveal a more pronounced spatial pattern: urbanity forms multi-polar linkages, rurality diffuses west to east, and development exhibits multi-directional diffusion. (3) In terms of grading, "middle development-high urbanity" areas account for the largest share; in terms of categorization, integrated development areas are the dominant type; and in terms of zoning, the pilot zones for urban-rural integration hold the highest proportion. A spatial system centered on factor linkage and functional agglomeration is thus initially established. The study concludes by proposing context-specific strategies, providing theoretical and practical insights into urban-rural restructuring, especially in evaluating unified villages and communities and analyzing their multidimensional interactions.

The spatial restructuring of large Chinese cities has exacerbated internal spatial differentiation and social segregation, resulting in disparities in the distribution of environmental risks across social groups and regions. This has negatively impacted the health and well-being of urban residents. This study analyzes the socio-spatial disparities in environmental risk distribution in Shanghai, Guangzhou, and Chengdu using pollution discharge permit data and census data, with ArcGIS spatial analysis methods. Principal component analysis is then applied for dimensionality reduction to capture the characteristics of urban spatial restructuring. Interaction term models are applied to analyze the intrinsic connections between environmental inequality and the urban spatial restructuring process. The findings reveal that individuals with lower education levels and migrant populations are exposed to greater environmental risks, with environmental inequality increasing from the city center to the periphery. The spatial variations in environmental inequality across the three cities can be attributed to their respective urban spatial restructuring processes and development trajectories, resulting in three distinct patterns of environmental inequality: minimal impact, localized improvement, and environmental deprivation. The study draws on Spatial Production Theory and Rawls' Theory of Justice to elucidate the evolution of environmental inequality in spatial differentiation within the context of urban spatial restructuring, emphasizing the shift from capital-driven spatial production to government-led social justice practices. It is suggested that when formulating and implementing strategies to promote environmental justice and sustainable urban development, the global and dynamic nature of urban space development should be considered to ensure equitable sharing of environmental benefits across all regions and social groups.

The spatial expansion mode determines the urban construction, land development, and resource allocation patterns within a metropolitan area, and plays a pivotal role in the development of new quality productive forces. This study focuses on six major metropolitan areas in central China: Zhengzhou metropolitan area, Wuhan metropolitan area, Changsha-Zhuzhou-Xiangtan metropolitan area, Hefei metropolitan area, Nanchang metropolitan area, and Taiyuan metropolitan area. Using spatial dynamic simulation analysis method, we analyzed the spatial expansion models and their evolution of various metropolitan areas from 1990 to 2023, and conducted scenario simulations for the period from 2024 to 2035. The results show that: (1) The total development, increment, and density indicators of the six major metropolitan areas in central China have undergone drastic changes, with significant differences in their evolutionary processes: The Zhengzhou metropolitan area has evolved into "single core with multiple centers and clusters", the Wuhan metropolitan area maintains "single core+cluster", the Changsha-Zhuzhou-Xiangtan metropolitan area has evolved into "single core agglomeration", the Hefei metropolitan area has evolved into "primary and secondary centers", the Nanchang metropolitan area maintains "dual centers", and the Taiyuan metropolitan area has evolved into "centers with corridors and clusters". In the future, these characteristics will continue to be maintained and strengthened. (2) The Zhengzhou metropolitan area, Wuhan metropolitan area, and Changsha-Zhuzhou-Xiangtan metropolitan area are "core-dominant" models that can accelerate the development of metropolitan areas and improve expansion efficiency in a short period of time. However, they are also prone to exacerbating regional disparities and causing the development of surrounding cities to lag behind. The Hefei metropolitan area, Nanchang metropolitan area, and Taiyuan metropolitan area follow a "hub and spoke" model, opting for a gradual and steady expansion approach. This approach facilitates the absorption of the radiation power from external economic entities. However, their development is relatively slow and the efficiency remains low. (3) Guided by the principles of "multi-level, multi-center, networked development, smart growth, and urban integration", measures such as implementing regional strategies, controlling expansion, adjusting zoning, and establishing a policy system should be taken to scientifically optimize the spatial expansion mode of urban agglomerations.

Transportation equity for mobility-vulnerable groups is an important issue of social equity. As the arterial system of cities, metro systems, due to their advantages of safety, reliability, punctuality, and efficiency, serve as a crucial guarantee for ensuring mobility equity for vulnerable groups, such as the seniors and underage students. The built environment surrounding metro stations, as an important component of urban transportation spaces, not only influences the metro travel behavior of these groups, but also reflects spatial justice through its equal accessibility. However, the mechanisms and pathways by which the built environment affects travel remain unclear. This study focuses on seniors and underage students in Kunming, selecting frequent travelers from both groups based on smart card data from the metro system. By integrating multi-source data, including land use, the study employs a Gradient Boosted Decision Tree (GBDT) model to reveal the complex mechanisms between the built environment around metro stations and the metro travel behavior of these two groups, comparing the differences in impact pathways between them. The results show that: (1) The relationship between the built environment and metro ridership of different groups exhibits four patterns: overall consistency, group diversity, senior group specificity, and student group specificity; (2) Variables such as land use mix, road network density, betweenness centrality, and proximity to intercity transport hubs have a relatively consistent effect on metro ridership across different groups, while the influence of other variables differs significantly; (3) The number of residential communities and land use mix have a consistent relationship with metro ridership across groups, showing a mainly positive nonlinear relationship and an inverted U-shaped relationship, respectively, while the relationships between other variables and metro ridership vary; (4) Compared to traditional linear models, the nonlinear model is more sensitive and can more accurately capture threshold effects. This study deepens the application of spatial justice theory in transportation geography and provides theoretical and empirical support for guiding travel for vulnerable groups and optimizing the built environment around metro stations.

Urban expansion, as a key driving force in the evolution of the Earth's surface human-environment system, profoundly influences land resource allocation and the stability of ecosystems. The horizontal expansion patterns and impacts of urban construction land are well-established at the global, national, and city scales. However, the expansion types, spatial characteristics, and driving mechanisms on the three-dimensional terrain gradient remain inadequately understood. Therefore, this study focuses on analyzing the slope variation characteristics and spatial interaction relationships of construction land, ecological land, and arable land in 2754 counties across China. By systematically categorizing gradient expansion types and employing a combination of random forest model and geodetector, this study delves into the driving factors of spatial differentiation of various expansion types. The results indicate that: (1) The rapid urbanization in China, with stringent arable land protection policies, has driven urban construction land to expand into areas with steeper slopes. In 78.18% of counties, the dominant gradient expansion type of construction land is characterized by an increase in slope. Meanwhile, the expansion type featuring increased slopes for arable land or ecological land is primarily concentrated in the northeast, northwest, and southwest regions. (2) The gradient expansion of construction land is closely linked to the gradient evolution of arable land, as the development of sloping arable land provides new space for urban construction land. In regions where the slope of arable land is notably steeper, the rate of expansion in construction land area is twice as high as that in areas where the slope is decreasing. Furthermore, the cultivation of sloping arable land serves as a major source for supplementing arable land resources. (3) The complexity of regional topography and the intensity of agricultural production are the main constraints and driving factors for the significant differences in the gradient expansion of China's urban areas. The interaction of topographical factors, including elevation, slope, and the proportion of flat land, accounts for 30% of the explanatory power in elucidating the spatial differentiation of slope changes in construction land. Quantitatively characterizing the spatial patterns, processes, and driving mechanisms of construction land expansion along gradients holds significant importance for mitigating construction land pressures in mountainous urban areas, protecting arable land, and promoting regional sustainable development.

Entering the new era, the close integration of return migration and county urbanization has become an important grasp on people-centered new-type urbanization in central and western China. However, existing studies predominately focus on the effect of return migration on the county-level economy, with less emphasis on the spatial perspective of county urbanization patterns. Taking Tianmen-Mianyang region of Hubei province as a case, this paper utilizes the field survey data from April 2018 to November 2022 to examine the impacts of apparel manufacturing migrants returned from cities (i.e. Guangzhou and Wuhan) to their home counties during the urbanization process. The results show that the entrepreneurship and employment of return migrants centered around the general manufacturing industry promote the transformation of exogenous county urbanization to endogenous county urbanization relying on local industrialization. Specifically, it forms three types of county urbanization: centralized county seat urbanization with economic development zones as the space carrier, centralized township urbanization with town-level industrial parks as the space carrier, and decentralized county seat urbanization with residential communities around schools as the space carrier. The governmental initiative of high-quality development leads to a decline of inclusiveness in county economy, which promotes the transformation of return entrepreneurship from formal and centralized to informal and decentralized. Meanwhile, the space carrier of return entrepreneurship shifts from the incremental expansion characterized by economic development zones and town-level industrial parks to the reuse of the existing stock exemplified by residential communities around schools. The future of return-migrant urbanization faces great challenges, and it is necessary to concern and to facilitate the recombination of returned capital and labor in home counties.

Accurately identifying the "production-living-ecological" spaces (PLES) is the premise of urban functional zone optimization, livable cities construction, and urban-rural development balancing. Existing research on identifying spatial distribution of PLES is insufficient in identifying and quantitatively characterizing integration space and interactive space. There is an urgent need to establish methods that consist of complete system and can accurately quantify spatial functions by integrating multi-source geographic data based on existing rural-urban regional systems. Thus, this present constructed three indices, including Spatial Function Strength index (SFS), Spatial Function Coverage index (SFC), and Spatial Function Interaction index (SFI). These indices were calculated using the Point of Interest (POI) data, land cover, and cell phone communication data using the road network community as the fundamental unit. The PLES in Haidian district, Beijing was identified by determining the priority of the three indices with the decision tree interpretation method. In addition, this study compared the spatial distribution and characteristics of functions at the global, class, and patch levels using landscape indices. The results include: (1) The functional zones at different regional systems were significantly different. Along the urban-rural gradient, the diversity spatial types and complexity of shapes, and the patch density increased, but the spatial aggregation in the same class decreased. (2) Individual ecological and living spaces showed concentrated distribution within the rural and urban regional systems, while the spatial characteristics of individual production space in different regional systems were quite different in terms of dominant industry type. Within the integrated spaces, the type and characteristics were different between rural and urban areas. For interactive spaces, they were mainly distributed in the transitioning spaces between rural and urban zones, characterized by "separation between living and working spaces". (3) At the patch level, landscape indices complemented and supported the spatial pattern for the system and classes of the PLES at a finer scale. In addition, landscape indices effectively identified special city functional regions with the largest spatial diversity and smallest spatial aggregation. The result of this study realized system interpretation and spatial identification of multi-functionality for PLES at the urban-rural regional systems based on innovated methods for integrating data in illustrating the advantages of multi-source geographic big data, which provided supports in terms of data and methods for territorial spatial planning and management.

The digital competence of residents is a crucial component of personal and social development and significantly influences regional development patterns through its geographic distribution and dynamic evolution. It has increasingly emerged as a critical driving force in advancing common prosperity. This study constructs a measurement system for assessing the digital competence of Chinese residents with respect to common prosperity. It develops a theoretical framework to explore the underlying mechanisms through which digital competence promotes common prosperity, aiming to offer robust theoretical support and empirical evidence for policy design. This study employs spatiotemporal analysis, spatial variogram, spatial autocorrelation, Dagum Gini coefficient decomposition, and fixed effects models to systematically examine the spatial and temporal characteristics of residents' digital competence across 25 provincial-level regions in China, along with its multifaceted influence on common prosperity. The study presents the following findings: (1) From 2016 to 2022, the overall level of digital competence showed a generally rising but fluctuating trend, although the national average remained relatively low. Specific dimensions demonstrated upward yet uneven trajectories, including data and information literacy, digital communication and collaboration, and digital problem-solving. In contrast, declines in digital content creation and digital security raise concern, especially in regions such as Yunnan, Guizhou, and Sichuan, where consistently low levels are observed. (2) National spatial disparities in digital competence have been narrowed over time, yet the east-west divide remains the most pronounced. Coastal provinces exhibit relatively balanced internal development, whereas the Gini coefficient of hypervariable density contributes most significantly to national disparity and shows an increasing trend. (3) At the village and community levels, improvements in digital competence notably promote common prosperity, with pronounced benefits for inland and rural regions. This positive effect operates through multiple forms of livelihood capital - human, material, financial, social, and psychological - and varies across regions. The study enhances the theoretical understanding of the dynamic evolution of regional digital development and the digital divide, offering practical implications for advancing balanced growth in Chinese residents' digital competence and achieving common prosperity.

In the context of the increasing importance of talent dividend in societal development, it is crucial to understand talent development in space, especially talent spatial flows, as the key element to support local high-quality growth. Drawing on the connotation of opportunities for talents, this paper investigates spatial and temporal changes of employment opportunities for university graduates. It proposes a conceptual framework and empirical research approach to quantify the employment opportunity space of university graduates, with a six dimensions of first employment after graduation, settlement, life comfortability, environmental amenity, social inclusion, and futural development. As a result, the employment opportunity map is firstly established at a city level, which helps to examine the evolution of the spatial distribution of opportunity space for the graduates. Between 2005 and 2021, the average employment opportunity index for cities in China increased by 73.4%. There is a general improvement, not the polarization in opportunity space. The gap between cities continued to diminish. The opportunity index has exhibited significant differentiation from east to west over an extended period, with the dominant spatial distribution pattern shifting from "coastal-inland" to "center-periphery" differentiation. All six dimensions of the indices show an upward trend, with the most substantial increases observed in first-time employment and amenities. The various dimensions of opportunity reveal distinct spatial and temporal evolutionary characteristics. Based on the characteristics of different opportunity combinations, six city opportunity types were identified, predominantly characterized by three lower-level city opportunity types. The spatial and temporal distribution and dynamic transformation of these six city opportunity types are active. Furthermore, the difference in the importance of opportunities between graduates of 985/211 universities and those from ordinary undergraduate institutions is primarily reflected in the two opportunity dimensions of settling down and social integration. Nonetheless, there is a consistency in the spatial distribution of employment opportunities in the respective cities for graduates from both types of institutions.

Promoting social green transformation is an inherent requirement and a key task in the national strategy for a comprehensive green transformation of the economy and society. However, research on the quantitative characterization and spatiotemporal patterns of social green transformation remains relatively lacking. To address this gap, this paper introduces social psychology theory to construct a quantitative characterization framework for social green transformation. Using 19 urban agglomerations in China as the study area and following the "pattern-process-effect" research logic, the study integrates methods such as entropy-weighted TOPSIS, spatial Markov chains, and Random Forest model to sequentially reveal the spatiotemporal evolution patterns, spatiotemporal transformation, and dynamic impacts of the social green transformation on the economic green transformation. Finally, a comprehensive quantitative framework for regional green transformation is proposed. The results show that: (1) During the study period, the level of social green transformation in China's urban agglomerations showed a fluctuating upward trend, with the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations leading in social green transformation, while those along the middle reaches of the Yangtze River, the northern slope of Tianshan Mountains, Lanzhou-Xi'an region, and Ningxia along the Yellow River were relatively lagging. (2) There is a phenomenon of club convergence and spatial spillover effects in the social green transformation of urban agglomerations, and the transformation exhibits path dependence and spatial dependence, with low probabilities of cross-level and cross-regional transitions. (3) Social green transformation serves as a significant driving force for the green transformation of urban economies, and this driving effect has been strengthening over time. The role of social green transformation in advancing the strategy of ecological prioritization and green development is increasingly profound. Furthermore, this study helps to improve existing research on regional green transformation evaluation, providing new methods and ideas that better align with and respond to the current comprehensive green transformation strategy.

The well-being of people's livelihood is an important issue that goes hand in hand with the great rejuvenation of the Chinese nation, and it is also the fundamental purpose and ultimate destination of human development. This paper explores the evolution and influencing factors of the well-being level of urban and rural residents in China based on the data from the 2012-2021 China Livelihood Survey, using principal component analysis, cold- and hot-spot analysis, spatial kernel density estimation and multi-layer linear modeling. The findings are as follows: (1) China's urban and rural residents' well-being level shows a fluctuating upward trend, with both urban and rural well-being levels increasing. (2) China's urban and rural residents' well-being shows significant regional differences, with levels of the Northwest and the Northeast being higher than those of the others. (3) China's urban and rural residents' well-being level has obvious clustering characteristics. In 2021, there was a "hot-shrinking-cold-shrinking-hot-expansion-cold-shrinking" development trend, and in 2018-2021, the agglomeration of urban and rural residents in areas with high levels of well-being gradually increased, while the agglomeration of areas with low levels of well-being tended to weaken. (4) Individuals, gender, age, education, work status, and household type, were the most important factors in the well-being of urban and rural residents in China. At the individual level, gender, age, education level, working status, and hukou type have an impact on the well-being of urban and rural residents; at the regional level, GDP per capita, population density, city level, and geographic location have a nonlinear impact on the well-being of urban and rural residents. (5) Compared with the eastern region, the negative effect of unemployment on urban residents' well-being is relatively more pronounced in the central and northeastern regions. Similarly, in the central and western regions, unemployment has a relatively stronger negative effect on rural residents' well-being. Compared with the eastern region, the positive association between per capita GDP and urban residents' well-being is relatively weaker in the central and western regions, whereas in the northeastern region, this association is relatively stronger. The results of the study are intended to provide useful insights for studies on well-being and Chinese-style modernization.

Digital economy enables the smooth transformation of cities in the Yellow River Basin, which is a key measure to promote ecological protection and high-quality development in this basin. This paper took the Yellow River Basin as the study area, evaluated urban transformation efficiency by using the super-efficiency SBM model, and constructed the spatial Markov transfer matrix, panel Tobit model and intermediary effect model to explore the spatio-temporal transfer characteristics of urban transformation efficiency and the driving effect of the digital economy on urban transformation efficiency. The results showed that: (1) From 2011 to 2021, the urban transformation efficiency in the study area was dominated by stable development, with certain "path dependence" and "self locking" effects; After considering spatial effects, the urban transformation efficiency mainly shifts upwards, and there was heterogeneity in the type transfer probability of urban transformation efficiency under different neighborhood types. (2) The digital economy had a positive effect on urban transformation efficiency, and the effect was regional heterogeneity, which was shown as follows: the middle reaches > the lower reaches > the upper reaches. (3) Technological innovation had a partial positive intermediary effect between the digital economy and urban transformation efficiency. The digital economy could promote urban transformation in the Yellow River Basin by improving the level of technological innovation; technological innovation had a single threshold effect of marginal reduction for the digital economy to improve urban transformation efficiency in the study area. When the level of technological innovation crosses the threshold value, the promotion effect of the digital economy on urban transformation efficiency begins to weaken.

Central cities, as drivers of regional economic development, have reemerged as a focal point of attention nowadays. However, their impact on the surrounding cities is inconsistent. Both positive and negative effects have been verified in different cases. One promising way to understand various impacts of central cities is to employ the dynamic lens. This paper focuses on the Central China Plains urban agglomeration, which developed and grew rapidly during the research period 2000-2020, and analyzes the dynamic impact of Zhengzhou on other small and medium-sized cities within the urban agglomeration (228 cities, counties, and county-level cities). The empirical analysis confirms that the role of central cities undergoes dynamic changes, and this case does not support the theoretical expectation of "siphoning first and then spilling over". Specifically, before 2005, there was no evidence of Zhengzhou's impact on the economic development of other cities in the Central China Plains urban agglomeration. Between 2005 and 2015, the evidence was inconsistent, hinting at a transitional phase between the two situations. After 2015, Zhengzhou mainly had a positive spillover effect on the development of cities within a certain geographical distance. The reasons for the aforementioned findings may lie in the fact that central cities, represented by Zhengzhou, focuses on attracting major resources from outside the province rather than within, and place great emphasis on and actively develop the manufacturing industry. Although a longer time period and evidence from more urban agglomerations are needed, the findings of this paper are a positive signal in favour of central city development strategies.

The urban-rural integration in the new era requires the coupled and coordinated development of new urbanization and comprehensive rural revitalization. This paper constructs an evaluation index system for new urbanization and comprehensive rural revitalization, and uses the modified coupling coordination degree model, spatial Markov chain, random forest model and other methods to quantitatively analyze the spatio-temporal evolution characteristics and influencing factors of coupling coordination types of new urbanization and comprehensive rural revitalization in Central China from 2007 to 2022. The results show that: (1) From 2007 to 2022, the coupling coordination type in the study area experienced a transition from moderate imbalance to minimal coordination, with regions of severe imbalance gradually disappearing and high-quality coordinated areas emerging, and the coupling coordination relationship has continuously improved. In terms of spatial distribution, high-value zones of coupling coordination level have remained concentrated in provincial capitals, while low-value zones have shifted toward western edge and the junction of Henan-Anhui-Hubei provinces, with boundary effects gradually emerging. (2) Regardless of the neighborhood conditions, the transition of the coupling coordination state exhibits "path dependence" and "self-locking" effects, while displaying "club convergence" phenomena, there is the possibility of transition to higher level but it is difficult to achieve leapfrog development. The geographical background plays an important role in the evolution of the coupling coordination state, which has an obvious spatial spillover effect, and the Markov prediction results also prove that spatial spillover effect will exist for a long time, the long-term evolution trend of the coupling coordination state is relatively good. (3) In the process of coupling and coordinated development, the level of industrial development plays a core leading role, the level of regional investment, the level of scientific and technological innovation, the level of human capital, and the employment structure of the population offer guarantees in terms of essential factors, and the geographical distance plays a restrictive role. Finally, this paper puts forward specific countermeasures and suggestions to provide scientific basis for the coordinated development of new urbanization and comprehensive rural revitalization in Central China.

This study examines the structure of the spatial association network of agricultural activities in the Changsha-Zhuzhou-Xiangtan urban agglomeration and explores its impact on urban-rural integration. This study employs social network analysis and a modified gravity model to analyze the spatial network characteristics of agricultural resource allocation. Furthermore, a coupling coordination model is used to evaluate the relationship between network structure and urban-rural integration. The results indicate that Changsha county, Xiangtan county, and Ningxiang city have strong resource adaptability and mobility, showing the potential to evolve into agricultural modernization demonstration areas. In contrast, Shaoshan city and Shifeng district exhibit significant weaknesses in resource utilization efficiency and factor allocation optimization. Based on these insights, this study proposes optimization paths and policy recommendations to improve the agricultural spatial network, enhance agricultural industry efficiency, and promote coordinated and sustainable urban-rural development. First, agricultural modernization demonstration zones should be established around Changsha, Xiangtan and Ningxiang, and agricultural science and technology innovation and infrastructure development should be strengthened to enhance regional resource flow efficiency. Second, efforts should be made to reinforce resource complementarity between core and peripheral areas in Shaoshan and Shifeng by increasing policy support and optimizing resource allocation. Finally, the agricultural industry chain should be extended to integrate agriculture with other industries and comprehensively improve regional agricultural modernization and urban-rural integration quality.

Ecological resilience refers to an urban agglomeration's ability to resist, adapt, and recover from external disturbances. Enhancing ecological resilience is crucial for promoting high-quality development in the modern era. However, few studies have evaluated the ecological resilience of urban agglomerations from the perspective of human-land interactions or explored its evolutionary mechanism. This study assesses the interannual variation of ecological resilience in the middle reaches of the Yangtze River urban agglomeration, focusing on resistance, adaptation, and recovery. The Least Squares Structural Equation Model is employed to analyze the impact degree and pathways through which human-land interactions affect ecological resilience. The results indicate that from 2000 to 2020, resistance, adaptability, and recoverability exhibited fluctuating trends over time and an unbalanced spatial distribution. Ecological resilience initially decreased but later improved, with significant spatial heterogeneity, forming a "higher in the southeast and lower in the northwest" pattern. Natural environment improvement (coefficient: 0.42) and regional policies (coefficient: 0.18) had significant positive direct effects on ecological resilience, while urbanization exerted a significant negative effect (coefficient: -0.26). Although green innovation had no significant direct effect, it exhibited significant indirect influence, with the most significant pathway being green innovation→regional policy→natural environment→ecological resilience (coefficient: 0.18). This study enhances our understanding of how the natural environment, green innovation, and regional policies shape ecological resilience, providing a scientific reference for urban agglomeration development that fosters harmony between humans and nature.

This paper provides a comprehensive reflection on the evolution of globalization research in the Pearl River Delta (PRD), considering the current international context and national strategies. It identifies several challenges in existing studies, such as the ambiguity of globalization patterns and the insufficient representativeness of key indicators. In response to these challenges, this paper draws upon the theory of strategic coupling to propose a new theoretical framework for analyzing globalization in latecomer regions. Based on the concepts of spatial stickiness and locational advantages, this paper further develops a two-dimensional quantitative indicator matrix. Using the PRD as a case study, this paper conducts empirical measurements and analysis, drawing three main conclusions. First, the theory of strategic coupling proves well-suited for analyzing the globalization of latecomer regions, exemplified by the PRD. It offers a more systematic, clearer, and more robust explanatory framework compared to traditional measurement methods. Second, the empirical analysis from the PRD reveals that the pattern of regional globalization does not follow a simple linear growth or cyclical model. Instead, it exhibits a circuitous, complex, and upward spiral, unfolding along an S-shaped evolutionary trajectory. Third, through comparisons of the east and west coasts of the study area, as well as segmented city analyses, this study finds that locational advantages significantly shape the evolutionary pattern of globalization. This influence is not only apparent during the region's initial take-off phase but also plays a more profound role in shaping its subsequent developmental trajectory. This study makes a distinctive contribution to both the theoretical understanding of globalization in latecomer regions and the practical field of regional economic development in China. Additionally, it introduces a novel measurement approach for studying regional globalization.

Domestic reinvestment by foreign enterprises (referred to as "domestic reinvestment") represents an emerging yet understudied dimension of foreign investment from a geographical perspective. Drawing on firm-level investment data from over 210,000 enterprises in Guangdong province (2000-2021), this paper constructs a domestic reinvestment network relationship matrix to systematically analyze its network structure, industrial spatial patterns, and underlying mechanisms. A comparative analysis is further conducted against foreign direct investment (FDI), investments by Hong Kong-Macao-Taiwan (HKMT) enterprises, state-owned enterprises (SOEs), and private domestic firms. Key findings reveal that: (1) Domestic reinvestment has transitioned from constituting 2.42% of total foreign investment in 2000 to surpassing FDI at 61.16% by 2021, emerging as Guangdong's predominant foreign-invested modality; (2) Spatially, exhibiting "local network embeddedness" and "hierarchical diffusion" characteristics, with capital concentration in Shenzhen-Guangzhou dual cores (82.3% of the total) and interprovincial flows favoring regional hubs; (3) Industrially, policy-driven expansion dominates power industries (76.4% state-guided projects), while manufacturing and service sectors demonstrate industry-chain dependent patterns-low-value-added industries cluster locally versus high-value-added sectors' hierarchical dispersal; (4) Compared to other types of enterprises, domestic reinvestment is influenced by distance and market size, ranking between direct investment and domestic enterprise investment, and relies more on talent and technology, external connections, policy support, and industrial linkages than direct investment. This study provides critical insights for optimizing China's foreign capital governance framework through differentiated industrial spatial policy instruments.

In response to climate change and global environmental crisis, more and more countries have started to pursue a low-carbon economy. With significantly reduced or no tailpipe emissions, new energy vehicles (NEVs) - vehicles that are powered by alternatives to fossil fuels, such as electricity and non-traditional fuels - are gaining popularity and becoming the future of the automotive industry. Using NEV supplier data of Tesla's Shanghai Gigafactory (Tesla Shanghai), the paper performed a network analysis based on firm headquarter-subsidiary connections to map out the factory's global production network (GPN), revealed the spatial configuration of the network, and explored the forces driving its formation and development. The research yielded several findings. First, the global production of auto parts for Tesla Shanghai resembles a typical GPN with a core-periphery structure. Tesla Shanghai has established strong high-frequency connections with economic centers (or manufacturing centers with strong R&D capability) located in East Asia, North America, and Europe. Second, within the Tesla Shanghai's GPN, four supply chain systems - smart electronic components, battery and electric drive systems, thermal management systems, and chassis and trim - display varying hierarchical structures. Third, within each of the four supply chain networks, most communities (or subnetworks) span across geographical and administrative boundaries, connecting cities around the world through modular production of auto parts. These communities demonstrate strong internal heterogeneity with an emerging core-periphery structure of network nodes. Using the four explanatory variables of the GPN 2.0 framework (i. e., cost-capability ratio, market imperatives, financial discipline, and risk environment), the paper further analyzed the main factors that shape the highly complex NEVs GPN of Tesla Shanghai from the perspectives of global environment, market demand, technological linkages, and local competitive advantages. The study contributes to the new economic geography literature by providing an interesting case study. The findings of the research provide theoretical insights and practical implications for the innovation and sustainable development of the NEV industry.

Intercity connections are crucial for understanding regional structures, with business activities serving as key elements in the formation of city networks. Although big data is increasingly applied in urban network studies, its inability to distinguish between various groups and travel purposes limits a deeper understanding of intercity business connections. This paper proposes a method that integrates big and small data to identify inbound business visitors. It uses survey-based small data to construct a model and applies it to large-scale mobile phone data to identify and analyze the activities of inbound business travelers in Shanghai. The analysis focuses on temporal characteristics and the spatial distribution of their originating cities, main business destinations, and accompanying activities, summarizing spatial structures and regional patterns. The study reveals that approximately 37% of Shanghai's inbound travelers are for business purposes and they mainly originate from the core Yangtze River Delta region and distant major cities. These visits are mostly short-term, lasting less than four days, and show regular weekly fluctuations. Spatially, inbound business travel and related activities exhibit significant polycentric characteristics, forming a four-tiered structure: dual hubs (Hongqiao and Lujiazui-Nanjing Road), a horizontal core area, contiguous districts, and corridors. The spatial distribution of inbound business destinations regarding different originating cities varies significantly by city size and distance, presumably associated with industrial characteristics. The proposed method of integrating big and small data offers broad applicability and holds substantial value for city network research and spatial planning.