Establishing off-site R&D centers in innovation-rich regions is crucial for enterprises in peripheral areas to overcome the constraints of the “agglomeration shadow” and construct a regional collaborative innovation system. Based on the data of high-tech enterprises and their associated enterprises in Hebei Province, this study systematically examines the layout characteristics, industrial correlations, and internal and external driving factors of enterprises’ off-site R&D centers. The findings are as follows: 1) In terms of the layout characteristics of departure locations, there are significant disparities in the number of off-site R&D centers among prefecture-level cities. Shijiazhuang leads significantly with a 24.91% share, forming the first echelon. Leveraging their locational advantages, Langfang, Baoding, and Tangshan have prioritized setting up off-site R&D centers in Beijing and Tianjin, thus forming the second echelon. In contrast, Xingtai, Hengshui, and Chengde are relatively underdeveloped with sluggish growth in the later period. 2) In terms of the layout characteristics of destination locations, off-site R&D centers have gradually expanded from the initial local agglomeration adjacent to central areas to distant innovation-rich regions, forming a multi-tiered spatial layout that covers megacities with high innovation levels, regionally innovative provincial capitals, and coastal cities with a high degree of trade liberalization. 3) The driving factors for the layout of enterprises’ off-site R&D centers exhibit the characteristics of internal and external coordination: at the enterprise level, capital reserves, locational attributes, and innovation cooperation levels are the main internal driving factors for their layout; at the urban level, talent cultivation, population density, and digital infrastructure play a facilitating role in the layout, while the lag in the business environment exerts a significant crowding-out effect.

Metropolitan areas are an important organizational form of urbanization and exert a significant influence on regional development. The Yangtze River Delta represents a major urban agglomeration that contains multiple metropolitan areas which are spatially adjacent, highly functionally intertwined, and characterized by overlapping planning boundaries. These metropolitan areas simultaneously compete and cooperate, forming a distinctive spatial structure that profoundly shapes regional integration. Based on multidimensional indicators such as population size, economic development level, and industrial structure, this study employs weighted integrative methods including the entropy approach to characterize patterns of spatial competition-cooperation among metropolitan areas under a polycentric configuration. The results indicate a significant deviation between the actual functional interaction scope of metropolitan areas and their planned boundaries. Spatial competition-cooperation is unevenly distributed and gives rise to 4 major types, including the core synergistic type, the cross provincial dependent type, the peripheral coupled type, and the multidirectionally embedded type, reflecting diversified structural features in both spatial and functional terms. This differentiation is mainly manifested in the inconsistent affiliation of cities under multi core dynamics. Some cities show stable attachment, while others lie at competitive and cooperative interfaces shaped by overlapping dual core or multi core influences. Moreover, spatial competition-cooperation is not randomly distributed but tends to cluster along major corridors such as Shanghai-Nanjing, Shanghai-Hangzhou, and Nanjing-Hefei. Metropolitan interfaces and interprovincial transition zones exhibit more blurred functional boundaries and greater differentiation among competition-cooperation configurations.

Focusing on 34 prefecture-level administrative units in China’s 3 northeastern provinces (Liaoning, Jilin, and Heilongjiang), this study systematically explores the coupling coordination relationship between urban shrinkage and industrial upgrading and their spatiotemporal evolution characteristics during 1990-2023, by integrating the entropy weight method, coupling coordination degree model, and geographical detector method. The research findings are as follows: 1) Urban shrinkage in the Old Industrial Base of Northeast China exhibits a phased pattern of “initial intensification followed by gradual mitigation”, while industrial upgrading is marked by a developmental pattern of lingering at a low level in the early stage and surging rapidly in the later phase, as reflected in the changing distributions of the urban shrinkage index and industrial upgrading index. 2) The overall coupling coordination degree between the 2 variables shows an upward trend, forming a high-coordination agglomeration zone centered on Shenyang, Changchun, and Harbin. In contrast, peripheral areas have long been trapped in a “low-coordination dilemma”. Spatial differentiation of the coupling degree further confirms this core-periphery pattern, and the kernel density estimation reveals a gradual narrowing of the coordination gap across cities. 3) Geographical detector analysis reveals that urban location, industrial structure upgrading, and total factor productivity (TFP) serve as the key determinants influencing the coupling coordination degree. Among these, industrial structure optimization and technological innovation exert a significant positive effect on improving the synergistic level. This study suggests that priority should be given to enhancing industrial resilience through advancing industrial structure upgrading and TFP improvement, and differentiated regional policies should be adopted to facilitate the coordinated development of core and peripheral areas.

This paper follows the logical thread of “why, for whom, what to govern, and how to govern” conducts a three-dimensional analytical framework of “rational cognition-key contents-implementation pathways”, systematically exploring the theoretical logic and practical approaches to urban shrinkage governance within the Chinese context. The study highlights that: 1) At the level of rational cognition, the logical starting point of shrinkage governance lies in a cognitive transformation regarding urban shrinkage-critically examining local governments’ “exclusionary cognition” toward the shrinkage label and driving the shift of the shrinkage issue from “being ignored” to “being confronted”. Throughout the governance process, a people-centered value orientation must be upheld. 2) At the level of key content, governance must achieve a paradigm shift from “incremental expansion” to “stock optimization” and from “scale-oriented” to “quality-oriented”, with a focus on four core domains: economic transformation and industrial restructuring, infrastructure adjustment and public service optimization, spatial restructuring and urban renewal, and social governance innovation and community building. 3) At the level of implementation pathways, 5 pathways are proposed: fostering multi-actor coordination, integrating and coordinating policy systems, implementing differentiated governance strategies, building a regional coordination framework, and strengthening support through technological and interdisciplinary integration. The research findings aim to promote the “Chinese localization” of responsive urban shrinkage governance, provide theoretical and methodological support for urban shrinkage governance and planning practices, and contribute to Chinese-style modernization.

AI technology transfer is an important force to reshape the regional development pattern and optimize the allocation of innovation resources. However, there is little research on its spatio-temporal evolution characteristics and patterns. This paper studies the spatial distribution and mode of AI technology transfer in China from 2004 to 2024 by using spatial autocorrelation, social network analysis and other methods. The results show that: 1) the spatial pattern shows a significant trend of dual core polarization and gradient diffusion. Beijing and Shenzhen are always at the top of the intensity of technology transfer. Cities in the Yangtze River Delta such as Shanghai and Suzhou form the second echelon of “high-high” technology transfer agglomeration, “low-low” technology transfer depression. 2) The network power structure is dominated by Beijing and Shenzhen, and the network density continues to increase, but the standard deviation expands synchronously, indicating that the polarization effect is further aggravated while the network scale expands; In the core edge structure, the triple pole connection density of Beijing, Shanghai and Shenzhen reached 399.833, which further strengthened its absolute dominant position. The spatial imbalance deepened with the development of the network. 3) The inter city technology transfer shows a significant stage of spatial evolution, which in turn shows the evolution from core edge, multi center networking, and then to the intensification of polarization. 4) According to the scale, flow direction and network centrality of technology transfer, the spatial patterns of AI technology transfer in China can be divided into 3 types: Intermediary hub type, global radiation type and technology endogenous agglomeration type.

Innovation-oriented urban regeneration is an important way for China’s major cities in implementing urban regeneration initiatives. Based on the Triple Helix theory and the conceptual tool of “architect” in innovation ecosystem study, this article constructs an analytical framework of “architect–strategic behavior–resource advantage-path selection”. Using 3 case studies of the innovation-oriented regeneration of old university campuses in Nanjing, it empirically analyzes the different paths and outcomes of innovation-oriented urban regeneration with multiple governance models. The findings include that: 1) In the micro-level practice scenarios of innovation-oriented urban regeneration for old university campuses, a multi-governance structure has objectively taken shape, with university-led initiatives being the most prevalent, followed by those led by large enterprises, and local government-led initiatives being the least frequent; 2) The strategic behavior and resource advantage structure of the 3 types of architects-universities, local governments, and large enterprises-profoundly influence the path selectivity for innovation-oriented urban regeneration, which collectively shape different practical paths and micro-innovation ecosystems; 3) Innovation-oriented urban regeneration with different governance structures has limitations respectively. Fostering strategic synergy and resources sharing & cooperating among universities, local governments, and enterprises emerges a common optimization strategy. The research has expanded the theoretical methods and enriched the policy instruments for understanding and managing innovation-oriented urban regeneration. Firstly, it enriches the understanding of China’s transformation pathways towards urban innovation economies as well as the diversity of governance vehicles for the transformation. Secondly, the proposed theoretical analysis framework effectively addresses the shortcomings of existing studies on innovation-oriented urban regeneration pathways based on the Triple Helix theory, through puting the roles of architects, their behavioral motivations, and resource capabilities into analysis. Thirdly, it enhances the understanding of policy tools in the practice of innovation-oriented urban regeneration. We argue that selecting an appropriate architect is crucial, and it is equally important to intervene in the strategic behavioral motivations and resource capabilities of the architect implementing innovation-oriented urban regeneration. To overcome the limitations of innovation-oriented urban regeneration advanced by different architects, it is essential to build a Triple Helix collaborative governance framework among universities, local governments, and enterprises, based on promoting strategic alignment and complementary resource capabilities among them.

As an important strategic pivot for China’s coordinated regional development, the synergistic relationship between land use and ecological resilience in the city cluster in the middle reaches of the Yangtze River is of great significance for realizing high-quality development. This paper takes 28 prefecture-level cities in the city cluster in the middle reaches of the Yangtze River from 2000 to 2020 as the research object, and comprehensively applies the super-efficient non-expectation SBM model, VIKOR model, and Coupling Coordination Degree (CCD) modle to systematically reveal the spatio-temporal evolution law and coupled coordination characteristics of land use efficiency (LUE) and ecological resilience (ER). The results show that: 1) LUE shows a “W”-shaped fluctuating upward trend, with significant “core-edge” spatial differentiation, and Wuhan, Changsha, Nanchang and other central cities have obvious clustering effects; 2) ER generally shows a downward trend, with a rapid decay from 2000 to 2007 and stabilization from 2008 to 2020, Wuhan City Circle is lower than the city clusters around Changzhou-Zhuzhou-Xiangtan and Poyang Lake, the spatial polarization effect is obvious, and the “center collapse” is prominent in the junction area; 3) CCD is slightly out of order, with a significant “core-edge” differentiation in space. CCD has increased from mildly dysfunctional (0.372) to barely dysfunctional (0.501), and a multi-center pattern with Wuhan, Changsha and Nanchang as the core has been formed spatially, but the overall level of coordination is still low. The results of the study can provide theoretical support for the coordinated ecological security and intensive development of the city cluster in the middle reaches of the Yangtze River, and serve as a decision-making reference for the sustainable development of the same type of region.

In the context of the synergistic development of digitalization and greening, digital technology innovation collaboration has become an important driving force for bridging the gap between the spatial polarization of digital innovation resources and the widespread demand for green transformation. Using panel data from 284 Chinese cities during 2006-2022, this study empirically examines the impact and mechanisms of digital technology innovation collaboration on urban green transformation. The results show that: 1) Both the digital technology joint R&D and technology transfer networks have steadily expanded in scale, forming denser and more efficient structures. The joint R&D network exhibits a spatial pattern characterized by “Beijing-led coordination among major cities”, while the technology transfer network demonstrates a hierarchical diffusion pattern of “core-city technology output-peripheral-city technology absorption”. 2) China’s urban green total factor productivity (GTFP) has shown an overall upward trend, presenting a concave spatial distribution pattern of “high in the eastern and western regions, low in the central region”. 3) Both digital technology joint R&D and technology transfer exert significant positive effects on urban green transformation and display mutual complementarity, though the former plays a stronger driving role. 4) Compared with eastern and resource-based cities, both forms of digital technology collaboration have a more pronounced impact on green transformation in western and non-resource-based cities. Moreover, joint R&D is more effective in cities with well-developed digital infrastructure, while technology transfer performs better in cities with weaker infrastructure. 5) Digital technology innovation collaboration promotes urban green transformation through two mechanisms-enhancing green technological innovation capacity and optimizing resource allocation efficiency. Among them, joint R&D plays a stronger leading role in green innovation, whereas technology transfer serves as a more powerful driver of resource optimization.

Based on the 2017 China Migrants Dynamic Survey, this study focuses on re-migrants, employing sequence analysis to examine the spatiotemporal trajectories of individual migration from a life course perspective, and to identify several typical migration patterns. Additionally, multinomial logistic regression models are used to analyze the underlying factors influencing these migration patterns. The findings reveal that: 1) Most young re-migrants experience their first migration between the ages of 15 and 19, while re-migration typically occurs after the age of 20. Moreover, the duration of stay in the initial destination is significantly shorter than that in the current destination. 2) Initial migration predominantly occurs upward across hierarchical levels, followed by movement within the same city tier and downward migration along the urban hierarchy. As individuals age, the share of upward migration decreases, while same-level and downward migration gradually increase. 3) Based on the temporal and spatial characteristics of migration, six typical migration patterns and their associated group characteristics are identified: early upward migration followed by lateral/downward movement, upward migration with long-term stay followed by lateral/downward movement, upward mobility followed by lateral/downward movement, lateral migration, late upward migration followed by lateral/downward movement, and unstructured migration of accompanying children. 4) Migration patterns of young re-migrants result from the combined effects of individual-level factors and city-level factors. This study not only highlights the significance of young re-migrants’ socioeconomic characteristics but also explores the influence of place of origin on migration patterns. The findings contribute to a clearer understanding of migration dynamics and provide a foundation for city authorities to develop targeted policies for attracting and retaining talent.

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.

Against the backdrop of the digital economy development strategy, rural digital new media platforms have effectively driven the high-quality development of rural tourism in ethnic minority mountainous areas by aggregating attention capital and converting it into the tourism economy. Taking the “Village Super League” (Cun Chao) in Guizhou Province as a case study, this paper draws on the theoretical framework of the traffic flow economy and employs methods such as field surveys and semi-structured interviews to deeply investigate the transformation logic and practical pathways of tourism in ethnic minority mountainous areas empowered by traffic flows. The findings reveal the following: 1) In the digital economy era, the tourism industry is transforming into a traffic-intensive industrial form. Rural digital new media platforms aggregate both physical tourist flows and virtual data volumes, enabling ethnic minority mountainous areas to break the “core-periphery” spatial structure and build a multi-format, interconnected tourism industrial ecosystem. 2) The digitalization, platformization, sharing and spatialization characteristics of the traffic flow economy systematically drive the transformation of rural tourism, enabling the circulation and value appreciation of traffic flows across vertical and horizontal temporal-spatial dimensions, and empowering destinations to form multifunctional traffic spaces with inclusive characteristics. 3) In response to the potential risks and practical dilemmas that traffic flows may cause, this paper constructs a practical pathway of “platform aggregation of traffic, innovation-driven traffic attraction, and mechanism-based traffic management”. Specifically, platform-led culture serves as a traffic-aggregating vehicle to consolidate the sense of community for the Chinese nation; innovation in lived-scenario traffic attraction transforms traffic spaces into spiritual anchorages for tourists; and the resilient governance model strives to break through institutional obstacles in rural tourism transformation and achieve mechanism-based traffic flow management. The research results expand the explanatory scope of traffic flow economy theory in the field of rural revitalization and provide both theoretical support and practical references for the tourism transformation and comprehensive revitalization of ethnic minority mountainous areas in the digital era.

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 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.

Farmland is crucial for food security and social stability, but abandonment due to lack of rural motivation has been a persistent issue in China. Reducing abandonment requires balancing land demand and supply, but research from the demand-side perspective is limited. Integrating primary, secondary, and tertiary industries in rural areas have emerged as a solution. The 2024 No. 1 Central Document calls for promoting this integration, focusing on modernizing rural industries and revitalizing abandoned land. It emphasizes the need to develop a coordinated system for grain, cash crops, livestock, and fisheries, on the context of connecting production, processing, and sales. It is critical to explore how industrial integration impacts farmland abandonment. Based on survey data from 526 villages in Zhangjiakou City in August 2024, this paper uses OLS models to explore the relationship between rural industrial integration and farmland abandonment from a village-level perspective, offering a new approach to addressing the issue of farmland abandonment. 1) Rural industrial integration significantly reduces cropland abandonment, with findings confirmed by endogeneity tests and robustness checks. 2) The impact operates through 3 key pathways: labor transfer, land circulation and infrastructure improvement. From a labor perspective, industrial integration creates non-agricultural jobs and promotes mechanization, allowing labor to shift between agricultural and non-agricultural work, which reduces cropland abandonment. 3) In terms of land circulation, industrial integration activates the farmland transfer market, optimizes land use, and minimizes disputes, promoting the conversion of abandoned land to productive use. Integration entities acquire farmland and encourage local labor participation, reducing abandonment. While integration entities prefer cultivated over abandoned land, the difference is insignificant, suggesting balanced land integration. 4) From an infrastructure perspective, industrial integration enhances agricultural production factors by improving transportation, digital, and logistics infrastructure, lowering operational costs and risks and making abandonment less economically attractive. 5) Rural industrial integration reduces cropland abandonment across all terrains. In non-plain areas, industrial integration drives more innovation, leading to a stronger impact on reducing abandonment compared to plain areas. First, strengthen the coordination between labor allocation and industrial integration. Link non-agricultural employment with land use, promote mechanized management, and ease labor shortages on abandoned land. Second, improve the land transfer system for industrial integration. Set up a priority transfer mechanism for abandoned land, offer soil fertility subsidies and tax reductions, and incentivize the reuse of abandoned land. Third, match infrastructure development with rural industrial needs. Focus on building industrial support infrastructure in areas with concentrated abandoned land, creating a positive cycle of infrastructure improvement and land revitalization. Fourth, develop terrain-specific strategies for industrial integration. In non-plain areas, relax marginal land use restrictions to reduce abandonment through resource value adjustment. In plain areas, strengthen ties between new entities and small farmers to prevent large-scale operations from overtaking marginal land.

Grounded in the social-technological-ecological transition of the digital intelligence era, this paper systematically reviews the theoretical evolution trajectory of Time Geography along the path of “classical foundation-theoretical innovation-digital intelligence leap”. It traces the theoretical development of key concepts from diorama to project and pockets of local orders, and articulates three ontological shifts of Time Geography. The new Time Geography witnesses an ontological shift: the view of space-time transforms from absolute space-time to relational space-time; the view of behavior shifts from space-time path description to project-driven activity system, connecting intention with action and introducing the social dimension; and the view of human-ecological interaction expands from the fabric of existence woven by individual paths to the all-ecological analysis of the project-activity system. Focusing on theoretical and methodological innovations in the digital intelligence era, this paper synthesizes recent conceptual developments-including physical-virtual hybrid paths, physical-digital dual constraints, and ICT-mediated pockets of local orders-and identifies emerging methodological approaches such as dual-activity diary surveys, hybrid physical-virtual measurement, and foreground-background activity visualization. The paper identifies emerging features of human activities in the digital intelligence era: persistent frontstage-background intertwining, space-time decoupling and recoupling, normalization of remote intervention, and diversification of pacesetters. It further argues that algorithms are becoming an endogenous force reshaping projects and their pockets of local orders. The innovative development of Time Geography in the digital intelligence era provides a robust scientific foundation for deeply analyzing the mechanism of digital transformation of daily life, spatial and temporal optimizing the people-oriented city, and improving residents’ well-being.

The increasingly pervasive application of digital technologies and artificial intelligence has accelerated the arrival of the digital-intelligent era, profoundly reshaping geographical space and behavioral geography. Building upon a comprehensive review of Behavioral Geography research in the digital-intelligent era, this paper conceptualizes how digital intelligence reconfigures spatial attributes, human subjectivity, spatial behavior, and spatial governance. Furthermore, by introducing well-being, this study constructs an analytical framework to decipher the interactive relations among geographical space, affective experience, activity systems, and spatial governance. Based on this framework, it systematically reflects on the shifting relationship among subjective well-being, spatial behavior, and spatial governance in the digital-intelligent age. The research highlights the threefold impact of digital intelligence. First, digitalization can negatively impact human subjective well-being by altering reference points for judgment, modifying sensitivity to environmental experiences, and creating misalignment between algorithmic optimization objectives and individual value systems. Second, it reshapes the “information gathering–value judgment–spatial decision-making” chain by restructuring the set of available spatial choices, reducing the role of value judgment in behavioral decisions, and redefining the very meaning of “spatial” behavior. Third, digitalization alters the drivers of political behavior, diminishes the perceived importance of transforming physical space, and highlights the growing significance of digital spaces design and temporal planning. The paper further proposes recommendations such as strengthening interpretable analytical frameworks, enriching governance approaches, promoting cross-scale integration, and reconstructing fundamental principles in the digital-intelligent era. Furthermore, the paper discusses how digitalization and intelligence reconstruct the connotations and impacts of core concepts in Behavioral Geography-namely “space” and “behavior”. This study expands theoretical innovation in Behavioral Geography for the digital-intelligent era and provides a crucial reference for deepening our understanding of the interrelationships among geographical environments, subjective well-being, and spatial behaviors.

With the continuous evolution of digital intelligence technologies, individual behavioral patterns are undergoing profound restructuring. Physical and virtual activities have coalesced into a physical-virtual activity system characterized by mutual permeation and real-time interactive feedback, while the technologically mediated hybrid physical-virtual environment has fundamentally altered the interaction between environment and behavior. This process exerts complex and far-reaching impacts on residents’ mental health by rendering the acquisition of mental health resources and social support more accessible, yet simultaneously engendering novel mental health risks. Against the backdrop of the deep integration of physical-virtual environments and the growing interweaving of physical and virtual activities, it is necessary to re-examine the dynamic evolution of environment, behavior, and mental health, as well as the complex interrelationships among the three. This paper systematically reviews mental health research from the perspective of behavioral geography and summarizes the reconfiguration of behavioral patterns and the corresponding changes in mental health in the age of digital intelligence. It further explores the mechanisms through which individual digital literacy, hybrid physical-virtual environments, and reconfigured behavioral patterns affect mental health under the influence of digital intelligence technologies. On this basis, the paper constructs a new “Environment-Behavior-Mental Health” research framework for the age of digital intelligence. This framework incorporates hybrid physical-virtual environments and physical-virtual activity systems, introduces individual digital literacy and its interaction with the environment to reveal population heterogeneity, characterizes the multi-dimensional features of physical-virtual activity systems from temporal, spatial, and interaction perspectives, and systematically reveals mental health outcomes from risk to well-being and from immediate responses to long-term scales. It also proposes mental-health-oriented strategies for the synergistic optimization of physical and virtual environments, together with behavioral guidance aimed at promoting healthier patterns of physical-virtual activity. Overall, this study provides new insights for environment health research in the context of digital intelligence and deepens the understanding of health mechanisms in the digital intelligence era from a behavioral geography perspective.

Since the rise of the behavioral revolution in the 1970s, the research paradigm of human geography has shifted from macro-scale pattern descriptions toward the exploration of micro-scale process mechanisms in human-land relationships. With the increasing availability of long-term spatiotemporal behavioral big data, empirical behavioral geography is transitioning from traditional “space-behavior” interaction analysis to refined process tracking and causal inference design. Despite the accumulation of significant research outcomes, the field still faces two core challenges: first, a lack of long-term dynamic tracking covering the entire interaction chain of “physical space-resident behavior—living space”; and second, a tendency to remain at the level of verifying the significance of correlations rather than establishing robust causal links. Traditional studies often rely on cross-sectional data and assume a static equilibrium between space and behavior, which overlooks the dynamic formation process of stable states and fails to address the fundamental question of how spatial adjustments trigger specific behavioral shifts. To address these limitations, this paper systematically reviews recent research progress and proposes a novel research framework that integrates process tracking with causal inference. This framework focuses on the dynamic interaction between physical space, individual behavior, and life space, aiming to move beyond “black-box” correlations toward the identification of causal effects. Methodologically, the paper emphasizes the use of “big yet thick” data, such as long-term mobile signaling data, to construct natural experiment scenarios, including passive spatial interventions like infrastructure development and active interventions like residential relocation. By introducing quasi-experimental designs, such as Difference-in-Differences, Regression Discontinuity, and Causal Forests, researchers can mitigate common biases like confounding, over-control, and residential self-selection. The research content is structured into 3 progressive components: first, tracking the impact of physical space on behavioral responses, distinguishing between immediate, lagged, gradual, and sudden response patterns; second, uncovering the evolutionary mechanisms of life space formation using advanced techniques such as Topological Data Analysis (TDA) and Inverse Reinforcement Learning to decode individual decision-making preferences; and third, integrating these perspectives to optimize urban planning and emergency response. This integrated approach allows for the scientific evaluation of spatial intervention policies under both normal conditions, such as the assessment of 15-minute community life circles, and emergency states, such as the resilience of urban mobility during public health crises like the COVID-19 pandemic. Looking ahead, the paper advocates for the fusion of multi-source heterogeneous data and the adoption of cutting-edge artificial intelligence, including Large Language Models and AI agents, to enhance the reliability of causal discovery. By clarifying the mechanisms by which space shapes behavior and behavior constructs life space, this paradigm shift provides evidence-based theoretical and methodological support for precision urban planning, sustainable built environment design, and the cultivation of urban resilience, ultimately advancing the study of micro-scale human-land relationships.

This paper reviews recent advances and extends the “space-time-human” coupling framework to the study of digitally mediated urban environments. Rather than treating digital media as an independent fourth dimension, the framework conceptualizes them as a cross-cutting force that reconfigures how time, space, and individual characteristics interact to shape health and well-being. Theoretically, digital media introduce instantaneous and cumulative exposure as well as temporal compression into the time dimension; extend the space dimension from physical settings to hybrid digital-physical environments; and make digital literacy and individual agency within algorithmic systems central to the human dimension. The paper further proposes 3 interrelated concepts. Digital landscape refers to algorithmically mediated information environments and individuals’ exposure to and perception of them; virtual behavior encompasses information seeking, online social interaction, navigation, and digital health management; and digital health support includes wearable devices, AI-assisted services, telemedicine, and context-aware interventions. Together, these elements form dynamic feedback loops in which digital exposure shapes virtual and physical behaviors, user activities modify subsequent information environments, and health status further influences patterns of engagement. Although these processes can expand access to health resources, they may also reproduce or intensify inequalities through digital divides, algorithmic bias, information overload, and unequal capacities to convert available resources into health benefits. Methodological advances follow 2 interconnected tracks. At the data level, the integration of GPS trajectories, platform and application logs, wearable sensor data, ecological momentary assessment, social media content, and physiological indicators enables more dynamic and context-sensitive measurement of individual exposure, behavior, and health outcomes. At the analytical level, explainable geographic artificial intelligence, causal inference, virtual experiments, digital twins, and agent-based simulations provide tools for identifying mechanisms, inferring causality, and evaluating interventions. In practice, these developments translate into two major application domains. At the individual level, geofenced and personalized health services, early risk detection, remote healthcare, and digital behavior interventions support proactive and precision health management. At the spatial level, mobility-responsive allocation of public health resources, evidence-based environmental design, and adaptive urban governance contribute to building healthy and resilient cities. Future research should move beyond the physical-virtual dichotomy, conduct longitudinal and cross-regional comparative studies across the life course, and integrate explainable artificial intelligence with causal research designs. Greater attention should be paid to privacy, algorithmic transparency, digital inclusion, public accountability, and environmental health justice.

The proposed framework consists of 2 interrelated components: structural foundations and a 3-layer coupled mechanism. The structural foundations include 3 parts. First, behavioral subjects are no longer defined solely by conventional socio-economic attributes, but are increasingly differentiated by digital literacy, platform experience, access to smart devices, and the ability to understand and respond to algorithmic logic. Second, digital-intelligent intermediaries, including platform interfaces, navigation tools, and recommendation algorithms and etc., actively reshape information visibility, behavioral opportunities, and decision structures. Third, the spatiotemporal context of behavior has shifted to a hybrid and computable environment in which virtual and physical spaces are intertwined and continuously sensed, recorded, and modeled. Together, these elements define the contextual foundation within which individual behaviors are generated in the digital-intelligent era. Building upon this foundation, the framework further identifies a 3-layer coupled mechanism: the real-world behavioral generation layer, the digital twin simulation and expansion layer, and the behavioral regulation and feedback layer. The first layer focuses on how individual behaviors are generated in real-world hybrid environments through cognition, decision-making, and action across pre-behavior, in-behavior, and post-behavior stages. The second layer emphasizes how real-world behaviors are transformed into computable and modelable representations through multi-source behavioral data and digital twin technologies, making scenario simulation and behavioral prediction possible. The third layer highlights how simulation results feed back into urban planning, governance, and behavioral guidance, while also continuously updating the twin system through new data inputs. In this sense, individual space-time behavior is no longer understood merely as a response to pre-existing spatial constraints, but as part of a dynamic loop linking behavioral generation, datafication, simulation, intervention, and renewed behavioral adaptation. The proposed framework thus contributes not only to advancing the theoretical development of behavioral geography under the digital-intelligent turn, but also to providing a conceptual basis for linking behavioral analysis with planning and governance practices in increasingly data-rich and algorithmically mediated urban environments.

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.

Based on investment data from strategic emerging industry enterprises in Gansu Province in 2014 and 2024, this study constructs a cross-regional network of new quality productive functions in less-developed cities and employs social network analysis and exponential random graph models (ERGMs) to systematically examine the network’s evolutionary characteristics and underlying mechanisms. The results show that: 1) the network continued to expand, with increasingly stronger intercity linkages; the degree distribution followed a power-law pattern, while disparities among nodes widened; and an agglomeration-diffusion spatial pattern emerged, centered on Lanzhou, Jiuquan, and other key cities. 2) Within Gansu Province, only the number of prestige-type cities increased, whereas outside the province, the number of cities in all categories increased. Capital mainly originated from provincial capitals in neighboring provinces and high-ranking cities in eastern China, while investment destinations extended to more developed cities capable of providing advanced resources such as R&D and producer services. Consequently, a multi-core-periphery structure across administrative boundaries became increasingly prominent. 3) Compared with 2014, the network in 2024 became more stable and mature, with stronger reciprocal cooperation and greater dependence on the expansion of non-core nodes and the intermediary role of high-ranking cities. Industrial upgrading remained the principal driver of outward investment, while the effects of innovation capacity and economic development strengthened. Financial abundance became increasingly important in attracting investment. Technological proximity consistently dominated intercity cooperation, whereas the effects of geographical distance and social proximity weakened, and institutional linkages shifted toward cooperation across institutional differences. Less-developed cities increasingly tended to cooperate with cities east of the Hu Huanyong Line that featured higher administrative status, greater marketization, and stronger technological similarity. These findings provide theoretical insights and policy implications for developing new quality productive forces in less-developed cities according to local conditions.

Urban system models represent a frontier research domain in Human Geography and urban planning. They constitute a comprehensive theoretical synthesis of urban evolution and operation, while also serving as important scientific instruments for urban research, planning and governance. This study develops a comprehensive evaluation framework for urban system models, encompassing 6 dimensions (principles, structure, functions, technical parameters, quantitative methods and applications) and identifies 35 key evaluation indicators. Using this framework, we conduct a comprehensive and systematic assessment of 109 urban system models developed since 1960. The analysis reveals that: 1) urban system models have undergone a substantial paradigm shift from static equilibrium to dynamic evolution and from macro-level aggregation to micro-level simulation. Through this process, they have gradually exhibited a development trend characterized by interdisciplinary theoretical integration, cross-scale technological integration, and multidimensional scenario expansion, reflecting the increasing integration of theories, modelling techniques, analytical scales and application contexts in urban system modelling; 2) current urban system models continue to face several major challenges, including insufficient construction and representation of evolutionary mechanisms, limited capacity for responding to multiple and diverse policy interventions, lagging adoption and development of modelling paradigms capable of representing complex urban systems, and the absence of an open and shared modelling ecosystem. These challenges constrain the further development and broader application of urban system models; and 3) urban system models are currently at a critical juncture in the transition from traditional structural simulation toward the explicit representation of complex mechanisms. Looking ahead, future research should focus on developing complexity-oriented, adaptively coupled, and practically deployable model architectures; establishing integrated, extensible, and responsive comprehensive modelling systems; advancing intelligent computing paradigms jointly driven by mechanisms, data, and problems; and building an open, unified, operable, and standardized modelling ecosystem. These directions together point toward a new stage in which urban system models move beyond the simulation of urban structures toward a more comprehensive representation of the complex mechanisms underlying urban evolution and operation. The findings of this study provide theoretical insights and technical directions for the development of new-generation urban system models and their enabling platform technologies.

Against the backdrop of high-quality development and demographic transition in China, talent has become a key focus of urban competition, while cultural amenity has increasingly emerged as a critical dimension for assessing urban livability and residents’ sense of belonging. Based on 487 508 samples from the 2024 National Urban Physical Examination Survey, this study employs an interpretable machine learning framework using LightGBM combined with SHAP values to systematically examine the nonlinear effects of cultural amenity on residents’ settlement intention. The results indicate that cultural amenity is a significant determinant of settlement intention. Among its dimensions, commercial attractiveness ranks as one of the most influential factors, second only to homeownership, and exerts a stronger effect than most traditional economic variables. Different dimensions of cultural amenity exhibit distinct nonlinear patterns. Atmosphere-oriented amenities, such as historical and cultural preservation, display clear threshold effects, with evaluations below the “satisfied” level exerting a pronounced inhibitory impact on settlement intention. In contrast, improvements in practical function-oriented amenities, particularly commercial services, generate substantial marginal benefits. Furthermore, settlement decisions demonstrate pronounced educational heterogeneity. Residents with a bachelor’s degree or above are most sensitive to cultural atmosphere and place greater emphasis on quality enhancement; those with junior college education respond strongly to changes in the quality of cultural and recreational activities; while residents with senior high school education or below place greater importance on practical amenities, for whom improvements in everyday commercial and recreational services can effectively enhance settlement intention. By revealing the differentiated pathways through which cultural amenity influences settlement intention across educational groups, this study provides important empirical evidence for cities to formulate more targeted talent attraction and retention strategies.

In this study, the modified coupling coordination degree model, OPGD and IGTWR model were employed to identify the water-carbon-food coupling relationship in the middle and lower reaches of the Yellow River from 1990 to 2020, and to explore the dominant interaction factors and their spatio-temporal heterogeneity characteristics. The results show that: 1) From 1990 to 2020, carbon storage and food production in the middle and lower reaches of the Yellow River were relatively stable and continuously increased, while water resources fluctuated greatly. In addition, both water resources and food production show a characteristic that the downstream is greater than the midstream, while carbon storage shows the opposite. 2) The coupling relationship of water-carbon-food in the middle and lower reaches of the Yellow River is in a barely coordinated state. Overall, it shows a pattern of “high in the east and low in the west, high in the south and low in the north”. The high-value areas are concentrated in the Qinling Mountain area in southern Shaanxi, the Yellow River alluvial plain, the hilly area in central and southern Shandong and the Jiaolai Plain, while the low-value areas are distributed in the core area of the Loess Plateau. 3) The interaction and superposition between climate change and human activities dominate the coupling relationship of water-carbon-food. The precipitation factor in the climate change index layer has always played a crucial role, and geoengineering shows a significant synergistic enhancement effect in the interaction process with precipitation. 4) The interaction between precipitation and population urbanization mainly has a negative inhibitory effect on the coupling relationship of water-carbon-food, and the areas with strong negative influence are distributed in the counties at the junction of Shanxi, Shaanxi and Henan Provinces. The interaction between precipitation and economic urbanization is manifested as the coexistence of positive promotion and negative inhibition. The areas with strong positive influence are concentrated in the counties of eastern Shaanxi and central and southern Shanxi. The interaction between precipitation and returning farmland to forest and grassland shows a positive promotion, and the high-value areas are distributed in the core area of the Loess Plateau. Finally, suggestions were put forward from aspects such as the optimization path of nature-engineering integration, development strategies under water resource constraints, and the detection of the laws of key interaction processes.

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 1.13×10⁸t to 1.80×10⁸t, while demand rose from 0.78×10⁸t to 2.31×10⁸t. 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.

As an important part of ecosystem services, water conservation plays an important role in ensuring water security in river basin and ecological balance. In this study, the Dongjiang River Basin was selected as the research area, and the InVEST model was used to calculate the water conservation of the basin from 2000 to 2023. The Mann-Kendall test and the cumulative anomaly method were used to analyze the temporal variation characteristics and changing trends of water conservation during the study period. The global spatial autocorrelation and local spatial autocorrelation methods were used to identify the spatial distribution patterns of water conservation and to reveal its spatial clustering characteristics across the basin. In addition, the correlation analysis method and geographical detector model were used to explore the influencing factors of the water conservation function of the basin. The results show that: 1) The water conservation capacity of the Dongjiang River Basin from 2000 to 2023 is 117.93-309.93 mm. During the study period, there were some abrupt change points. The overall water conservation first decreased, then increased, and subsequently declined again. It also showed a cyclical pattern characterized by an initial decrease followed by an increase. 2) The spatial pattern of water conservation is high in the north and low in the south. The water conservation capacity of the watershed is significantly concentrated. High-high concentration areas are mainly distributed in the northwestern part of the basin, while low-low concentration areas are mostly found in the northeast and south. 3) The results of the geographic detector indicate that plant available water capacity has the greatest impact on water conservation in the Dongjiang River Basin. On the temporal scale, the influence extent of evapotranspiration on the water conservation of the watershed generally exhibits an upward trend. The interaction effects among the different factors further strengthened the water conservation function of the basin, indicating that their combined influence was greater than the effect produced by any single factor alone. The geographically weighted regression results further indicate that when plant available water capacity is the dominant factor, it mainly controls about 66.86% of the watershed area. These areas are mainly distributed across most of the eastern and northern parts of the Dongjiang River Basin.

This paper selects Yangdai Village, a typical footwear and apparel industrial village in Chendai Town, Jinjiang City, Fujian Province, as a case study to investigate land use issues and countermeasures in rural industrialized areas at the plot scale. Based on field investigations and utilizing data from 2 786 land plots, 36 876 records of permanent resident spatial information, 2 817 POI data points for public service facilities, and 704 spatial information records for footwear and apparel enterprises in Yangdai Village, this study employs methods including inductive-deductive reasoning, descriptive statistics, and factorial ecological analysis. The findings reveal that land use in Yangdai Village exhibits distinct self-organization characteristics and a circular spatial fabric, which adversely affects property rights recognition, industrial optimization and upgrading, and the social integration of the migrant population. The evolution of land use in Yangdai Village has undergone 4 stages: the germination of the private economy, a period of rapid industrial development, a stage of industrial cluster formation, and a phase where spatial constraints impede production. The interaction among multiple stakeholders-including local government, village collectives, villagers, lineage forces, and overseas Chinese kinship networks-has driven the process of industrialization and land development from the bottom up. Based on factorial ecological analysis, the village’s land plots are classified into 6 categories: residential and public service plots held by individuals, residential plots co-owned by multiple people, plots with a higher certification rate owned by non-natural persons, newly built small plots with unclear property rights inhabited by locals, large public service plots owned by collectives and industrial plots owned by non-corporate enterprises. Redevelopment should be based on the consolidation of land use scales, following the procedural steps of “property rights confirmation → defining redevelopment units → allocating public services and municipal facilities → designating land for offsetting costs → re-dividing cadastral parcels and land use functions.” Within the redevelopment units, differentiated redevelopment pathways are proposed for the various types of land plots identified. This paper aims to provide a reference for optimizing land use in rural industrialized areas.

Enhancing residents’ satisfaction and subjective well-being (SWB) is the central objective in building modern people-oriented cities in China, with the construction of urban amenities serving as a critical lever. Many studies have explored the linkage between the objective urban human settlements elements, especially the built environment elements, and SWB. However, studies adopting a human-centered perspective to examine the link between the perception of urban amenities and SWB remain relatively scarce, and even fewer have considered the moderating role of housing affordability in this relationship. Using social satisfaction survey data from the 2021 China City Health Examination Evaluation, this study constructs a comprehensive analytical framework of urban amenities perception, covering natural environment, service facilities, and socio-cultural dimensions. It then employs a multiple linear regression model to examine the effects of urban amenities perceptions on residents’ SWB, as well as the moderating role of housing affordability (including both subjective and objective measures) in this relationship. The results show that: first, urban residents generally have a good SWB in China, with an average score of 4.04. Among the three types of urban amenities perception, perception of socio-cultural amenities witnesses the highest score (4.21), followed by the perception of natural environment amenities (4.19), and the perception of service facilities amenities (4.14). Furthermore, all three types of perceived urban amenities have a significant positive effect (P<0.01) on urban residents’ SWB, with the perception of service facilities amenities witnessing the strongest impact. In addition, both objective and subjective housing affordability significantly and negatively affect SWB, with the former exerting a stronger negative effect. Moreover, the two types of housing affordability weaken the positive effect of urban amenities perception on SWB. Last, heterogeneous analysis reveals that perception of all three types of urban amenities exert stronger positive effects on the SWB of high-income residents and homeowners. The perception of natural environment amenities boosts SWB more for dwellers in the super-large cities and megacities, the perception of service facilities amenities matters most for new citizens (born elsewhere, with local household registration) and those living in large cities and small-medium cities, while the perception of socio-cultural amenities has stronger effects for local residents, as well as residents in large cities and small-medium cities. Our findings not only advance the theoretical understanding of the intricate interplay among urban amenities perception, housing affordability, and urban residents’ subjective well-being in the Chinese urban context, but also offer valuable policy insights for building livable cities and improving residents’ SWB in urban China.

Based on multi-source data, this study constructed an evaluation index system for residential environment deprivation from a comprehensive ‘physical-social’ perspective to measure the deprivation level in Hangzhou, China. Furthermore, GIS spatial analysis method and Geodetector model were employed to analyze its spatial distribution pattern and influencing factors. The results show that: 1) The overall level of residential environment deprivation in Hangzhou is relatively low to moderate (0.29). Specifically, the deprivation index from high to low is as follows: neighborhood deprivation, leisure service deprivation, transportation service deprivation, environmental pollution deprivation, education service deprivation, life service deprivation, medical service deprivation, and natural landscape deprivation. 2) The spatial pattern of residential environment deprivation in Hangzhou shows a typical ‘core-periphery’ structure. Driven by the combined effects of spatial polarization and housing market filtering mechanisms, low-deprivation areas are highly concentrated in the urban core. Meanwhile, suburban areas exhibit a complex spatial differentiation characterized by the improvement of physical environments and the exacerbation of neighborhood deprivation. Specifically, the spatial distribution characteristics of life, education, and medical service deprivation all show ‘multi-center’ structures. The spatial distribution characteristics of natural landscape, environmental pollution, and neighborhood deprivation all show hierarchical structures. Other dimensions largely resemble the overall deprivation pattern. 3) Results from Geodetector reveal that population density, economic development, planning regulation, and geographical condition jointly drive the spatial pattern of residential environment deprivation in Hangzhou. The interactive combinations of all driving factors belong to the ‘dual factor enhanced type’, with particularly strong enhancement effects observed in the interactions of altitude with both industrial structure and planning factors. These findings highlight the profound constraints imposed by the physical geographical base on the efficacy of socioeconomic and planning interventions, serving as the underlying logic that perpetuates and widens disparities in resource deprivation within megacities. Addressing residential environment deprivation in megacities requires the establishment of a collaborative governance system that integrates population regulation, industrial development, planning guidance, and spatial optimization, thereby promoting the high-quality development of livable cities.

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.

Regional brand development is an important approach to achieving rural revitalization, and digital technology may reshape regional brand development pathways by fostering new quality productivity. Taking the regional brand of the lychee industry in Gaozhou City as a case study, this study employs in-depth interviews and participant observation to analyze the challenges in building the regional brand, elucidate the pathways and logic through which new quality productivity empowers regional brand reconstruction, and propose optimization strategies for further promoting regional brand development. The principal findings are as follows: 1) By promoting the emergence of key elements, including new types of labourers, objects of labour, and instruments of labour, and thereby cultivating new quality productivity, the development constraints of the regional brand of Gaozhou’s lychee industry can be effectively overcome, thereby facilitating regional brand reconstruction. 2) The basic logic through which new quality productivity empowers regional brand development is to integrate new factors of production into the industrial chain, foster production relations compatible with these new factors, and enhance regional brand value in terms of quality, sales, and reputation. 3) In the future, the further upgrading of regional brands can be promoted through innovation-driven breakthroughs in core technologies, the establishment of a long-term brand management system, and the cultivation of innovative talent. The study suggests that empowering regional brand development through new quality productivity contributes to comprehensive rural revitalization; however, such efforts should be adapted to local conditions, with particular attention to the coordinated development of physical and virtual spaces.

Against the backdrop of intensifying global climate change, extreme rainstorm events have been occurring with increasing frequency and intensity, frequently triggering large-scale traffic paralysis, disrupting emergency rescue operations, and posing severe systemic challenges to the safe operation and emergency response capacity of urban transportation systems. Taking the extraordinary “7.20” catastrophic rainstorm disaster in Zhengzhou as a typical case, this study constructs topological models of the urban road network and the metro transit network, respectively, based on network science theory. On this basis, it integrates multi-source empirical data, including official metro operational records, road damage statistics and public assistance information, meanwhile systematically analyzes the dynamic evolution of transport network performance across multiple dimensions, such as connectivity, operational efficiency, and structural characteristics. The main findings are as follows: First, after the extreme rainfall event, the operational efficiency of both road and metro transport networks shows a continuous downward trend, and core structural indicators such as network connectivity exhibit a synchronized deterioration. Second, loop lines, with their closed annular topological structure, serve as a critical transport nexus, maintaining the connection between the urban core and peripheral areas after the disaster, and play an irreplaceable role in dispatching emergency resources during extreme rainstorm events. Third, the overall robustness of the urban transport network continues to decrease as the disaster progresses; specifically, the metro network is significantly more vulnerable than the road network due to the susceptibility of underground spaces to waterlogging. The relevant conclusions can also serve as practical guidance for disaster-prevention planning of urban transport infrastructure and for the formulation of emergency traffic management strategies under extreme rainfall scenarios.

Taking the Tanka fishing village in Lingshui Li Autonomous County, Hainan Province, as a case study, this research constructs a spatial justice theoretical framework to examine the transformation and social effects of production space in traditional fishing villages under ecological civilization transition. By integrating high-resolution remote sensing imagery, semi-structured interviews, and questionnaire surveys, it systematically analyzes the evolution of fishing village space, the manifestations of spatial imbalance, and their underlying generative mechanisms. The findings indicate that: First, production space has undergone a systematic reconfiguration driven by the dual forces of administrative governance and capital. Influenced by lagoon remediation and fishery upgrading policies, the traditional nearshore aquaculture space has been significantly compressed, leading to a ‘spatial displacement’ of production functions. This is manifested in the expansion of onshore catering and homestay businesses alongside a structural shift in offshore production toward capital-intensive deep-sea cage culture. This displacement represents a fundamental transition in spatial resource utilization rather than a simple functional replacement. Second, the process of spatial transition exhibits a tripartite challenge characterized by distributive imbalance, procedural limitations, and a lack of cultural recognition. At the distributive level, barriers to capital and technology have led to ‘elite capture’ in emerging industries such as deep-sea aquaculture, where resources tend to concentrate among a few well-capitalized actors, thereby restricting the livelihood space of traditional small-scale fishers. At the procedural level, critical decisions such as spatial planning and the demarcation of prohibited zones rely heavily on top-down administrative and technical logic, with limited inclusion of fishers’ agency and indigenous experiences, which creates challenges in the implementation of spatial rights. At the recognition level, Tanka traditional culture has been commodified and ‘spectacularized’ in commercial development; the narrative authority of fishers as cultural subjects has weakened, and their identity has been impacted by the commercial restructuring of physical spaces. Third, the root of spatial imbalance lies in the cumulative effect of capital’s profit-seeking nature and the state’s dominant role in spatial redistribution. This shift has altered the logic of spatial production from ‘livelihood-oriented’ to ‘capital-oriented’, resulting in the marginalization of vulnerable groups during the transition. Based on these findings, this study proposes a three-dimensional governance path: equitable resource allocation, multi-stakeholder procedural empowerment, and the return of cultural subjectivity. By improving compensation mechanisms for historical rights, strengthening the full-process participation of fishers, and establishing cultural benefit-sharing mechanisms, this approach aims to reconcile economic efficiency with spatial justice, providing theoretical references and practical insights for the sustainable transition and social equity of traditional coastal fishing villages.

This study is based on socio-economic data, land use data, and high-precision water system data that have been repeatedly corrected during the same period. By constructing a comprehensive evaluation system for river networks and storage and flood control capacity under the background of urbanization, a spatiotemporal geographically weighted regression model (GTWR) is used to analyze the quantitative relationship between river networks system changes and storage and flood control capacity in the Changsha-Zhuzhou-Xiangtan urban agglomeration from 1995 to 2020, as well as the impact of urbanization factors and various river networks system factors on water system storage and flood control capacity. Research has shown that: 1) The three-dimensional urban development level of the Changsha-Zhuzhou-Xiangtan area exhibits notable temporal and spatial disparities, with a discernible shift in the urban centre of gravity towards the northwest. 2) The hydrological system has undergone significant changes,The indicators of the hydrological systems exhibit considerable variation across different cities and time periods. In quantitative terms, with the water surface ratio (W_p) and river network density (D_r) exhibiting a 33% and 2% reduction. With regard to structural characteristics, the decay rates of the tributary development coefficient K and river network complexity C_r are 5.50% and 5.11% respectively. 3) During the study period, the water system’s storage and flood control capacity showed significant regional differences. The trench storage capacity (C) and the unit area trench storage capacity (SR) exhibited an increase, whereas the available storage capacity (AC) and the unit area available storage capacity (ASR) demonstrated a decline. 4) There is a significant correlation between the water system’s storage and flood control capacity and a number of factors, including per capita GDP, water surface ratio W_p, river network density D_r, area-length ratio R_al, and river network complexity C_r. In terms of temporal heterogeneity, The impact of per capita GDP, R_al and C_r on trench storage capacity C has undergone a process of shifting from negative to positive and increasing year by year. With regard to spatial analysis, per capita GDP has been found to have the greatest impact on trench storage capacity in Zhuzhou, while in Changsha, the impact is found to be the least significant. This study provides support for the environmental protection of the Changsha-Zhuzhou-Xiangtan urban agglomeration in the lower reaches of the Xiangjiang River Basin.

The complex evolution of rural social relations driven by tourism integration amid the interweaving of heterogeneous subjects' interests and the mismatch of actions is of great significance to resolving the structural tension between traditional human relations and modern contractualism. Based on the Actor-Network Theory, this study explores the evolution characteristics and internal logic of social relations in Zhushan Village and finds that: 1) The village's social relations have transformed from a traditional familiar society to a modern categorized society; 2) The evolution of social relations shows phased characteristics. In the nascent stage, it adheres to both etiquette customs and the pursuit of legal contracts. During the rapid development stage, heterogeneous subjects form a “categorized network” based on common interests, with the interest-contract bond becoming prominent and the role of human relations weakening, presenting a coexistence of semi-familiar and categorized social relations. In the mature transformation stage, categorized social relations dominate, and commercial contracts and rational governance become the core mechanisms for maintaining social operation; 3) The logic of social relation evolution is characterized by the loosening of the ethical community catalyzed by policy potential, the deepening of the “categorized network” mechanism of heterogeneous subjects due to the embedding of market capital, and the reconstruction of social relations driven by population mobility, professional division of labor, and cooperation, as well as the shaping of stable and fluid categorized social relations through functional collaboration and institutional rules.

Universities and specialized, refined, distinctive and innovative (SRDI) enterprises are key supply and demand actors in regional innovation systems. Their coordinated spatial distribution is crucial for optimizing the allocation of innovation resources and building efficient regional innovation networks. Focusing on Beijing-Tianjin-Hebei, the Yangtze River Delta and the Pearl River Delta urban agglomerations, this study develops a theoretical framework to analyze the spatial mismatch between universities and SRDI enterprises. Methods including the spatial mismatch index, the optimal parameter-based geographical detector, and partial least squares (PLS) regression are employed to examine their spatial distribution patterns, mismatch characteristics, and influencing factors. The results indicate the following key findings. 1) Both universities and SRDI enterprises in the three major urban agglomerations exhibit significant spatial agglomeration characteristics. These can be broadly categorized into three typical patterns: a ‘single-center agglomeration’ model, a ‘multi-core networked’ model, and a ‘deep specialization-broad higher education’ model. The latter is exemplified by the Pearl River Delta region, where SRDI enterprises are highly concentrated in Shenzhen, while higher education resources are clustered in Guangzhou. Bivariate spatial analysis further shows that the spatial distributions of universities and SRDI enterprises demonstrate a relatively weak positive spatial autocorrelation overall. Among the three urban agglomerations, the Beijing-Tianjin-Hebei region displays the strongest spatial association between the two, followed by the Yangtze River Delta, while the Pearl River Delta shows comparatively weaker spatial linkage. 2) A widespread spatial mismatch exists between universities and SRDI enterprises, with notable variations in both the degree and types of mismatch within each urban agglomeration. These mismatches exhibit multi-level structural differences across cities. Specifically, the Pearl River Delta demonstrates a relatively high overall level of matching between universities and enterprises. In contrast, the Yangtze River Delta exhibits more pronounced spatial mismatch phenomena, characterized by a higher prevalence of ‘dual-low positive mismatch’ types, where both universities and enterprises are relatively underrepresented but maintain a positive spatial relationship. Meanwhile, ‘enterprise-dominated negative mismatch’ and ‘dual-high negative mismatch’ types-indicating imbalances where either enterprises or both entities are disproportionately concentrated-are less common. 3) The spatial mismatch between universities and SRDI enterprises is jointly driven by multiple dimensions of factors. Among these, road network density and elevation provide fundamental geographical and infrastructural conditions. Economic development levels and the scale of talent cultivation in higher education institutions create structural tensions that shape spatial alignment. In addition, public cultural resources and the quality of the business environment play important moderating roles, influencing how effectively universities and enterprises can co-locate and interact within the urban innovation system. Overall, these findings contribute to a deeper understanding of the spatial organization and interaction mechanisms of innovation actors, offering valuable insights for policy-making aimed at enhancing regional innovation efficiency.

Cultural empowerment has emerged as a critical strategic pathway to promote rural revitalization and modernization. This paper constructs a logical framework of cultural em-powerment for rural revitalization, and analyzes the multi-dimensional value coupling mechan-isms and cultural IP construction pathways. The results show that: 1) Cultural empowerment for rural revitalization follows the logic of “value identification and coupling-resource capitaliza-tion and IP reconstruction-spatial restructuring and industrial operation”. The essence is to achieve innovative transformation with characteristic IPs through exploration and integration of cultural resources and value coupling, thereby promoting spatial restructuring and industrial op-eration to empower rural revitalization. 2) The multi-dimensional value attributes of cultural empowerment interact and transform with each other, and each value dimension forms a two-way coupling with the goal of rural revitalization. By fully activating the economic, spiritual, governance, ecological, and life well-being values of rural cultural resources, it promotes the construction of rural civilization, industrial integration, governance innovation, ecological liv-ability, and prosperous life in a coordinated manner. 3) Cultural IP construction constitutes a key path for cultural empowerment of rural revitalization. Through resource exploration and IP design, IP spatial structure and scene construction, as well as IP brand promotion and industrial integration, the industrialization of cultural resources and the comprehensive rural revitaliza-tion can be achieved, forming the logic of “value coupling- value embedding-value transforma-tion”. In the future, cultural empowered for rural revitalization should focus on the research of basic theories, spatial structures, path models and guarantee mechanisms for cultural resource industrialization, cultural IP construction, regional public brand cultivation, county-town-vil-lage cultural IP system construction, and gradually establishs a research system of cultural em-powerment to support comprehensive rural revitalization and urban-rural integrated develop-ment.

To explore the variations of aeration zone soil specific yield under the condition of deep buried groundwater, The southern edge of Gurbantunggut Desert was taken as the research area by field in-situ observation.The complete specific yield under the condition of zero surface flux, the average releasing specific yield under the condition of evapotranspiration and the average charging specific yield under the condition of lateral leakage recharge were determined, and the effects of groundwater depth, infiltration and evapotranspiration on specific yield were discussed. Results showed that: 1) It is feasible to determine the soil specific yield under the condition of deep buried groundwater by the zone of aeration section water content method. 2) Under the condition of zero surface flux, the complete specific yield μ increases with the increase of groundwater depth H. When the groundwater depth exceeds the maximum rising height of capillary water, the change of complete specific yield is small and can be approximately regarded as a constant. 3) The average groundwater depth of interdune land in the southern edge of Gurbantunggut Desert is 8.80 m. The complete specific yield under the condition of zero surface flux is 0.36, the average releasing specific yield under the condition of deep buried groundwater evaporation is 0.13, and the average charging specific yield under the condition of lateral leakage recharge is 0.17. The results of this study can provide a new idea for the determination of soil specific yield under the condition of deep buried groundwater.

Return migration has become a notable socio-economic trend in the new stage of China's urbanization, and the analysis of its driving mechanism has received extensive academic attention. As a micro behavior, the return of migrants is not only affected by personal and family factors, but also closely related to external environment. However, existing studies have focused on the role of individual factors, but not enough research has been conducted on the relationship between regional contexts and return migration. We introduce a gradient boosting decision tree model in the field of machine learning, based on the data from the 2017 China Migrants Dynamic Survey, with the return intention as the response variable and the regional contexts—Both in the place of origin and destination—As well as migrants' personal and household factors as the explanatory variables, focusing on the non-linear influence of the regional contexts on the return migration intentions and the threshold effect. The results show that: 1) The total contribution of the local contexts of the place of place of the origin and destination to the intentions of the migrants to return is 44.1%, which is an important factor influencing the return intentions, and the contributions of the two places is roughly equal. Among these, medical and health resources and air pollution are extremely important in both places. In addition, economic growth in the place of origin is also important for the return intention of migrants, while the climatic condition in the place of destination is more important; 2) There are both non-linear and linear relationships between local contextual factors and migrants' intention to return. Among them, medical and health resources, basic education resources, air pollution have obvious non-linear effects on the return intention, while economic growth and temperature conditions have mainly linear effects; 3) The influence of individual factors on return intention is mainly nonlinear effect. There is an irregular U-shaped relationship between age, migration duration and return intention, and the non-linear influence of household income is more complex. There is an obvious threshold effect between household housing expenditure and return intention, and a negative correlation between migrant's education level and return intention. This study incorporates the local contexts of the place of origin and destination into the analytical framework for the mechanism of return migration, identifies the relative importance of the local context and individual characteristics of the two places on the return intention of the migrants, and reveals the specificity and complexity of internal return migration in China, which contributes to deepening the research on migration in the new era and provides scientific reference for policy makers.