Human-Economic Geography and regional/spatial planning serve as mutual ‘theory-practice’ supports. Particularly, the research in Human-Economic Geography concerning functional zoning, urban spatial structures, resource allocation, and locational theories provides a scientific basis and technical support for the development of regional/spatial plans. For instance, functional zoning research underpins the spatial division of labor and functional orientation; the theory of spatial structure provides the framework methodology for determining urban and regional economic patterns; and the location theory of element allocation serves as a critical basis for productive-force layout. Currently, the external environment is undergoing profound and complex changes. The primary conflict in regional/spatial planning has shifted from ‘development-protection’ to the mismatch between the demand for high-quality development and spatial supply. Under the global context of ‘regionalization’ and China’s population contraction, the innovative development of new regional/spatial planning requires addressing new demands from including building the new development paradigm, implementing new development philosophy, developing new quality productive forces, promoting high-quality development, and constructing new spatial governance model. This necessitates an adaptive transformation in the foundational logic, geographic layout schemes, and technical methods of regional/spatial planning research and formulation. It also raises new requirements for research in Human-Economic Geography regarding the human-land relationship across different scales and types of spaces, the flow and allocation of multiple elements across all fields, the laws of locational selection, and the collaborative spatial governance between government and market. In light of this, this paper proposes new topics for Human-Economic Geography in the coming period, particularly focusing on the evolution of China’s Economic Geography under the new development paradigm, the locational characteristics and layout principles suited to new quality productivity, the locational layout and synergistic linkage of new urban infrastructure, and the sustainable development of priority conservation areas under the requirement of harmonious coexistence between humans and nature. Furthermore, promoting integrated innovation between Human-Economic Geography and regional/spatial planning should clarify the differences in transition contexts and practical demands between Chinese and Western research. Future studies should be grounded in the phase-specific conditions of Chinese-style modernization, actively advancing summaries of Chinese-specific theoretical/methodological innovations, to serve and support national major strategies and regional socioeconomic development.

Scenic-town symbiotic space refers to a composite spatial system that emerges from the spatial interaction of economic, social, and cultural elements between scenic spot and town. Additionally, it functions as the geographic spatial carrier that accommodates scenic-town symbiotic relationships. This paper introduces the symbiosis theory to construct the theoretical framework and index system of scenic-town symbiotic space. Theoretical analysis reveals that the scenic-town symbiotic space can be categorized into four types: superimposed, inclusive, overlapping, and separated. Economical, social and cultural symbiosis serve as the dynamic driving forces that propel the operational dynamics of scenic-town symbiotic space. From the perspective of symbiotic relationships, the spatial patterns of scenic-town symbiosis are classified into three fundamental types, namely commensalism, asymmetric mutualism, and symmetric mutualism. Furthermore, these patterns manifest four distinct evolutionary paths: positive, cyclical, stable, and reverse evolution. Then taking Huangshan Mountain scenic spot and its gateway towns as examples, the evolution characteristics and patterns of symbiotic space in scenic spot and towns are discussed, through the application of gravity model, kernel density estimation and Lotka-Volterra symbiosis model. The empirical results indicate that: 1) The development of this space exhibits significant systemic imbalance and co-evolution. During the study period, the development index of the scenic spot experienced short-term fluctuations but long-term stability. The development indices of the gateway towns increased markedly, albeit with substantial internal disparities, while the capacity of the symbiotic environment continued to improve. 2) The symbiotic correlation intensity between Huangshan Mountain scenic spot and gateway towns shows distinct gradient differences. Specifically, the correlation with Tangkou Town was the strongest and most stable, followed by Jiaocun Town, Tanjiaqiao Town, and Gengcheng Town. The symbiotic space between the scenic spot and these towns is characterized by a multi-nucleated, overlapping, and circular spatial structure. 3) In the process of dynamic adjustment of the symbiotic relationship between scenic spot and town, Huangshan Mountain scenic spot and Tangkou Town show a reverse evolution development model of symmetrical mutualism-partialism symbiosis; with Tanjiaqiao Town, it follows a stable evolution model of partial symbiosis; and with Gengcheng Town and Jiaocun Town, it demonstrates a positive evolution model of asymmetric mutualism-partialism symbiosis. This theoretical and empirical investigation holds significant implications for fostering harmonious coexistence between scenic spot and town, optimizing regional tourism spatial layouts, and promoting sustainable development.

Urban parks, as semi-permanent natural entities within urban spaces, are crucial to urbanizationa, acting as vital mediators in the dense fabric of modern cities. Past research mostly addresses history, accessibility, sustainability, ecosystem services, and health. Yet such work tends to remain park-centered, overlooking broader human-nature connections and often treating parks as isolated islands rather than integral parts of the socio-spatial fabric. This paper uses a dialectical perspective on humans and nature, underlining time and space to propose that urban parks serve both as tangible sites and as a geographical method for examining ties among human, nature, and society. To deconstruct these complexities, we analyze 3 theoretical views: anthropocentrism, naive harmony between human and nature, and the more-than-human perspective. Anthropocentrism sees parks mainly for human benefit, while naive harmony presumes seamless nature-urban integration. In contrast,more-than-human frameworks highlight nonhuman agency and socioecological processes that shape and are shaped by parks, revealing hidden tensions within communities and between humans and nature. Further, the paper endorses using urban parks as lens, echoing calls for relational thinking in Human Geography. Rooted in the Chinese context, this lens unveils social transformation, spatial governance, and everyday life, revealing shifting cultural practices and power structures that inform urban change. Parks thus become tangible arenas for studying social and ecological interplay. Finally, this approach reengages Marx’s dialectical stance on human-nature relations while resonating with China’s contemporary vision of ecological civilization. It underscores integrating historical materialism with socioecological imperatives, emphasizing environmental stewardship alongside social justice. By recasting urban parks as a lens, this research enriches urban nature studies and provides ways toward resilient, inclusive, and ecologically aligned urban futures. Ultimately, this reorientation fosters more holistic views of urban ecosystems, guiding integrative and equitable policy-making for long-term sustainability and inclusive development.

Investigating the cooling effects of blue-green spaces and their influencing factors is essential for optimizing urban spatial configuration and enhancing environmental resilience. Using Xi’an as a case study, this study integrates multisource data—remote sensing, evapotranspiration, and meteorological datasets—and applies the InVEST Urban Cooling Model to generate the Heat Mitigation Index (HMI) for assessing the cooling capacity of urban blue-green spaces. Landscape pattern analysis, the Geographical Detector, and boosted regression trees are further employed to reveal the mechanisms through which landscape patterns influence cooling effects. The results are as follows: 1) In summer, surface temperatures in Xi’an are dominated by moderate-temperature zones. Urban heat islands are concentrated in the central urban area and the western industrial park, with a relatively stable spatial pattern; cool islands are mainly distributed along river corridors and in suburban croplands, and appear as scattered patches within high-density built-up areas. 2) The spatial distribution of HMI is highly consistent across different cooling distances: high-value areas outside the Third Ring Road are mostly distributed along rivers or concentrated in contiguous croplands, while high-value areas inside the Third Ring Road correspond to urban parks containing water bodies; low-value areas are primarily located in high-density built-up and industrial zones, forming continuous surfaces, and appear as linear belts in surrounding rural settlements. 3) The cooling effect of blue-green spaces results from the synergistic action of multiple factors. Landscape diversity and patch fragmentation are the core driving factors, each interacting with patch size to enhance cooling capacity. All factors exhibit threshold behavior, and their influence on cooling may be either promotive or suppressive depending on the range of their values.

Trajectory data is widely used to calculate spatial characteristics of human activities and to mine patterns of human behavior. When the time sampling intervals of the original trajectory data vary, the temporal observation scale of the moving object's location changes, which can affect the calculated human activity characteristics and analysis results, a phenomenon known as the temporal aggregation effect. Taking mobile phone data as a representative example, trajectory data is not specifically collected for human dynamics research; the varying time sampling intervals of the data result in widespread temporal aggregation effects. However, there is currently a lack of analysis on the temporal aggregation effects and their underlying mechanisms for typical human activity characteristics. To address this, this study utilized 123 days of intensive sampling mobile phone data from volunteers and selected six typical human activity spatial characteristics from four dimensions for analysis. The results show that: 1) There exists a temporal aggregation effect in calculating typical human activity spatial characteristics based on trajectory data. As the time sampling interval increases, the values of the indicators are generally underestimated, although the extent of underestimation varies across different indicators; 2) Indicators dependent on short-duration activities (e.g., daily travel distance, daily travel frequency, and daily travel spatial structure) are significantly affected, while those focusing on long-duration activities (e.g., maximum daily activity range, number of daily activity anchor points) are less affected. Comprehensive indicators (e.g., activity location entropy) are moderately affected; 3) When the sampling interval exceeds 30 minutes, the variation of indicators, except for daily travel distance, shows good consistency among individuals. These findings enhance the understanding of human activity spatial characteristics based on trajectory data and help improve the scientific foundation of decision-support systems.

This article takes the newly established Yellow River Estuary National Park as a case, explores the supply and demand of carbon sequestration services in the Yellow River Estuary National Park from the perspective of carbon neutrality and its decarbonization effect on the surrounding areas, and simulates the extraterritorial effect of carbon sequestration services in the study area through the ecological radiation force model, and explores its horizontal ecological compensation value from the perspectives of the compensating party and the compensated party, so as to provide some reference for the compensation of carbon sinks in national parks.The results show that: 1) The Yellow River Estuary National Park is rich in carbon sink resources, with a total supply of carbon sequestration services exceeding the demand. In addition to offsetting its own carbon emissions, there is sufficient surplus space to absorb approximately 15.4054 million tons of carbon dioxide from surrounding areas. 2) In addition to the Yellow River Estuary National Park, carbon supply and demand conditions in other counties and districts in Dongying City vary significantly. Only the Hekou District has a surplus space of 4.2328 million tons of carbon dioxide after meeting its own carbon sequestration needs to offset the emissions from other counties and districts. The Kenli District, Lijin County, Dongying District, and Guangrao County all have insufficient carbon sequestration services, and are relying on supplies from other regions to offset their unsequestered carbon. 3) The Yellow River Estuary National Park can build a carbon sink compensation and carbon emission trading system based on the balance of supply and demand of carbon sequestration services and the extraterritorial effect of carbon sequestration services based on the ecological radiation force model simulation, and promote the economic value transformation of carbon sink resources. In order to better realize the ecological protection and regional coordinated development of national parks, it is also of practical significance to effectively utilize the carbon sink function of national parks and enrich their sustainable development path.

The advancement of the United Nations Sustainable Development Goals (SDGs) of poverty eradication (SDG 1) and sustainable cities and communities (SDG 11) are facing the serious challenge of the complexity of urban poverty spaces in the Global South. Through a series of studies, this team integrated bibliometric (1 394 publications from 1939—2023), satellite remote sensing, and field survey validation data, mapped a 120-m-resolution map of urban poverty spaces covering 1 075 cities in 108 countries/regions in the Global South, and conducted a systematic analysis of the cold and hot spot regions of the research. The results show that: 1) urban poverty in the Global South was significant and spatially heterogeneous, with 423×10⁶ urban residents (44.76% of the total urban population) living in environmentally poverty spaces covering an area of about 46 927 km² (39.43% of the total urban built-up area), with South Asia, sub-Saharan Africa, and Latin America being the three most severely affected regions. 2) Existing research on urban poverty in the Global South was unevenly distributed geographically. Only 67 cities have been identified as hot pot cities having populations exceeding one million (average population size of 5.602×10⁶), and they are highly concentrated in low-and middle-income countries/regions. There are a total of 1 008 cold spot cities (accounting for 93.77%), which have smaller population size (average population size of 0.564×10⁶) but bear 60.15% of the total poverty population, widely distributed across regions such as sub-Saharan Africa and Latin America. 3) Urban poverty mapping and attention studies complement each other, uncovering regional differences in urban poverty and revealing the urgency and priority of poverty alleviation in different regions, thereby reducing costs and increasing efficiency in poverty alleviation in low-income countries/regions and small and medium-sized cities. By sharing poverty data, optimizing international aid, and promoting China’s poverty alleviation experience, it is possible to effectively advance the anti-poverty and sustainable development process in the Global South.

This article investigates the inherent tensions between technology and institutional frameworks in smart city development across the Global South, advocating for a departure from Western-centric paradigms to construct a theoretically robust, locally adaptive, and critically reflective analytical framework. The study identifies two defining characteristics of Southern smart city practices: “technological catch-up”, driven by the imperative to bridge digital divides, enhance urban competitiveness, and respond to rapid demographic change, and “post-colonial critique”, which exposes how historical legacies of colonialism continue to shape contemporary technological adoption and governance structures in subtle yet enduring ways. Theoretical innovation is framed around integrating concepts such as spatial justice—addressing unequal distribution of digital resources across urban spaces—and digital sovereignty—safeguarding Southern nations’ control over data, technological autonomy, and regulatory authority—to redefine the dialectical relationship between technology and society. The research highlights the symbiotic interplay between informal economies (e.g., self-organized community networks, grassroots digital initiatives) and digital technologies, which challenges technological determinism and reveals a resilient development logic rooted in local adaptability and everyday practices. These insights deconstruct the linear narrative of technological progress, proving that Southern countries can balance efficiency with equity while pursuing differentiated urban modernities. By prioritizing context-specific innovations and inclusive governance, the Global South is reshaping the global knowledge production landscape, shifting from a passive “technology testing ground” to an active contributor of alternative urban theories and normative agendas. The study concludes by emphasizing the transformative potential of such frameworks to democratize technology, redirect smart cities toward social equity, and empower Southern nations to reclaim agency in global technological discourse. Through China’s practice of scale-sensitive smart cities and tripartite governance models, the research exemplifies how Southern-led innovations can challenge neoliberal techno-utopianism, alter dominant policy imaginaries, and foster pluralistic urban futures that reflect diverse socio-spatial aspirations.

Based on a bibliometrics analysis on existing literatures and a comparison of urbanization models among Europe, North America, Latin America, and Southeast Asia, this study constructs a “driving mechanisms-process-consequences” framework for analyzing urbanization. The framework adopts a time-series perspective and integrates three driving mechanisms: the primary driver of resource allocation, the fundamental endogenous and exogenous drivers, and “push-pull” interactive dynamics. Furthermore, it assesses urbanization across 5 aspects that evolve through different stages: economic development coordination, population migration, social integration, urbanization scale, and spatial representation. The post-1949 urbanization in China can be divided into three distinct historical stages. First, during the planned economy period from 1949 to 1977, cities primarily served industrialization needs. This resulted in a coexistence of incomplete urbanization and “counter-urbanization”. A distinct urban structure emerged, characterized by the intermingling of work-unit compounds and traditional residential areas, with factories and industrial zones located in the suburbs. Second, from 1978 to 2011, an era influenced by neoliberal policies, the combination of governmental macro-regulation and market forces generated a “new dualistic structure” within cities. This was defined by the socioeconomic divide between migrant workers and local hukou holders, as well as the spatial divide between the cheap, convenient housing of villages-in-the-city and high-end residential gated communities. Third, since 2012, China’s new-type urbanization has been defined by a reinforced governmental guiding role focusing on high-quality development. Strategies such as smart city initiatives, equitable public service provision, and ecological conservation have been emphasized. The people-centered approach to high-quality urbanization has provided critical guidance for charting a more mature course of urban development in China. As a result, a multipolar spatial pattern led by metropolitan areas and supported by the coordinated development of small and medium-sized cities and towns has come into being. In a word, the Chinese urbanization since 1949 has been a state-led process, though market forces have progressively intensified. It has shifted from a predominantly “push-driven” centralized one to a “pull-oriented” decentralized one. This transition has engendered a “neo-dualistic urbanization” paradigm, characterized by the simultaneous coexistence of pseudo urbanization alongside synchronous urbanization, of spatial concentration and decentralization, and of significant development gains with entrenched socio-spatial challenges. These features are fundamentally shaped by the evolving interaction between “push-pull” forces and “endogenous versus exogenous” dynamics. This study provides a valuable Chinese exemplar for understanding and theorizing urbanization in the Global South.

Destination image constitutes a vital component of a region's overall competitive strength. Building on the model of narrative comprehension and engagement and persuasion theory, this study examines the impact of internal and external realism in intangible cultural heritage bearers' media narratives on destination image, as well as the mediating role of media character identification. External realism refers to the extent to which the story aligns with the real world (regardless of whether the story is fictional). Internal realism refers to the coherence within the story itself in terms of logic, character motivations, and the continuity of events. Media character identification includes three dimensions: the audience's emotional resonance with the media character, perspective-taking, and motivation internalisation. In addition, destination brand awareness is introduced as a moderating variable in the research model. Partial least squares structural equation modelling (PLS-SEM) is used to validate the net effects of antecedent variables on destination image. Fuzzy-set qualitative comparative analysis (fsQCA) is employed to explore the configurational pathways leading to positive destination image evaluations. The results show that: 1) Internal realism has a significantly positive direct effect on destination image, whereas the direct effect of external realism on destination image is not significant; 2) Both internal and external realism positively influence destination image through the mediating effect of motivation internalisation, while the mediating effects of perspective-taking and emotional resonance are not significant; 3) Destination brand awareness moderates the relationship between internal realism and destination image; 4) Destination image is the outcome of multiple interacting factors, with four types of condition configurations having high explanatory power for the formation of a favourable destination image evaluation. This study proposes a “Narrative-Character-Destination Image” framework, offering implications for destination image construction.

Environmental regulation serves as a key policy tool for protecting tourism ecological security and achieving high-quality tourism development. On the basis of using entropy method to measure the intensity of environmental regulation and the level of tourism ecological security in China province from 2006 to 2021, this paper tests whether there is spatial autocorrelation between them with the help of spatial autocorrelation, and constructs a spatial Durbin model to explore the spatial spillover effect of environmental regulation on tourism ecological security. The empirical results demonstrate three key findings: 1) During the study period, the intensity of environmental regulation and the level of tourism ecological security grew strongly, and both showed a spatial pattern of strong in the east, medium in the middle, and weak in the west and northeast, and the characteristics of spatio-temporal heterogeneity were prominent. 2) The global spatial autocorrelation of environmental regulation intensity and tourism ecological security level is significant, and the local spatial autocorrelation results show that the environmental regulation intensity and tourism ecological security level are mainly“H-H” and “L-L” clustering type. 3) Environmental regulations contribute to local tourism ecological security improvement through dual channels: facilitating technological innovation progress and promoting industrial structure optimization. Furthermore, Environmental regulations generate positive spatial spillovers to neighboring regions via two transmission pathways: industrial gradient transfer effects, environmental policy demonstration effects. Notably, the analysis confirms that these spatial spillover effects substantially outweigh the direct local effects. These research outcomes provide valuable policy implications for formulating precisely targeted environmental regulation strategies to enhance ecological security protection while fostering sustainable, high-quality tourism development.

Rural tourism serves as a vital instrument for China's rural revitalization, playing a significant role in diversifying rural economies, promoting urban-rural integration, and achieving sustainable development. Based on the ‘institutional-cultural' coupling perspective and utilizing the CiteSpace bibliometric tool, this study systematically reviewed the literatures on rural tourism development in China from the CNKI and Web of Science (WoS) core databases (2000—2024). It comparatively analyzed the differences and commonalities in research stages, hot topic, and methodologies between domestic (Chinese) and international (English) contexts. The findings reveal that: 1) Research in both Chinese and English contexts shows rising popularity, yet with distinct stage characteristics. Domestic studies are policy-driven, forming a practice-oriented framework around rural revitalization, cultural-tourism integration, and common prosperity; international studies focus more on micro-level issues like sustainability, community empowerment, and rural gentrification, reflecting critical perspectives. 2) The dynamic interplay between institutions and culture constitutes the core logic of rural tourism development. Domestic research emphasizes the enabling role of policy rigidity in cultural capitalization, while international research examines the contest between cultural authenticity and institutional power under globalization. 3) There are significant methodological divergences: Domestic studies prioritize policy validation and quantitative analysis centered on industrial development, whereas international studies predominantly employ qualitative deconstruction, centering on communities and individuals. Key implications suggest that future research should deepen exploration in three critical dimensions: theoretical integration and framework innovation, methodological innovation, and thematic refinement and expansion. Particularly, there is a need for cross-disciplinary approaches that bridge the gap between policy implementation and community-based sustainable development models. Additionally, longitudinal studies tracking the socio-economic impacts of rural tourism could provide valuable insights for both academic and practical purposes.

Based on questionnaire surveys and structured interviews conducted in these communities, this study analyzes the formation mechanism of the intention-behavior gap in rural tourism participation among resettled households, employing the Logit-ISM model. The results reveal a pronounced divergence between willingness and behavior, with up to 67% of households exhibiting such a gap. Factors influencing the consistency include government policy promotion, development demands for rural tourism, mutual trust and support among households, and household labor capacity. 2 primary pathways underlie the intention-behavior gap: the direct cause stems from individual households' cost-benefit assessments based on economic rationality; the indirect cause involves insufficient support from social network resources constructed at both individual and community levels; and the root cause lies in the inadequate interaction and multidimensional support among individuals, communities, and the government. The weighing of economic rationality aimed at benefit maximization, combined with the overarching logic of social network embedding, provides a systematic explanation for the formation of this intention-behavior divide. Based on the above conclusions, the following suggestions are put forward respectively for resettled rural households, resettlement communities and grassroots governments: First, resettled rural households should strengthen their tourism service skills to make their own qualities match the local tourism development. At the same time, they should make good use of micro-financial loans and collective mutual aid funds to reduce economic risks. Second, the village committees of resettlement villages in resettlement communities should take the lead in establishing tourism cooperatives, foster trust and support relationships among resettled rural households, and strengthen the sense of community in resettlement communities. Third, local governments should attach importance to policy publicity, improve resettled rural households' awareness of the content and direction of local tourism development policies, establish and improve the supervision mechanism for the implementation of policies, effectively bridge the “last mile” in policy implementation, and help rural tourism policies take root in resettlement communities.

The TOD (transit-oriented-development) pattern is an important way to alleviate urban traffic congestion and improve intensive land use. It is also a key measure to promote the sustainable development of urban tourism and public transportation. Exploring the relationship between the TOD pattern and urban tourism helps to promote a positive interaction between public transportation construction and urban tourism development. Therefore, this study proposes an analysis framework of TOD urban tourism vitality (TOD-UTV) based on human scale, and verifies the impact of Nanjing's TOD pattern on urban tourism from two aspects of geographical environment and environmental experience. The results show that: 1) The distribution of TOD tourism vitality is high in the central urban area and low in the surrounding areas. 2) The change tendency rate also shows a pattern of improvement in the middle and a decrease around. 3) The dominant factor contributing to this result is the significant coupling effect of infrastructure construction such as land development, roads and transportation facilities around TOD in the core urban area and the service quality of commercial places such as tourism and entertainment. Therefore, enhancing the coupling effect of environmental factors around TOD is an effective strategy to promote a positive interaction between urban tourism and public transportation. This study provides a new framework for evaluating how the TOD pattern promotes urban tourism development, provides theoretical support for exploring the relationship between urban tourism and public transportation on a human scale, and provides insights for the positive interaction between TOD planning and urban tourism development.

The interaction and construction of urban relationship networks have always been the focus of attention for urban geographers. In the information age, the virtual space is the mapping and extension of the real space. The search and connection volume of online tourism information can be regarded as the hotspots of social development or represent the potential travel intentions of consumers. Through the analysis of the informal flow space network, certain reference value can be provided for the tourism industry development planning of various regions. Establishing cross-scale spatial linkages between individuals-regions from virtual space can complement traditional geospatial perceptions. In this paper, we obtain the frequency of tourism information co-occurrence in two cities and municipalities in Xinjiang in Baidu index, and use social network analysis to explore the spatial and temporal evolution of the spatial network structure of tourism information flow in Xinjiang. The results show that: 1) Urumqi City has certain advantages in terms of destination tourism information flow and relationship network, but it does not show the “siphon effect” in the traditional geographic network, but constructs a complex flow relationship network beyond the geographic boundary. This suggests that tourists' willingness to embark on multi-region travel, even travelling across longer geographical distances, is crucial for promoting the balanced development of Xinjiang's regional tourism. 2) In the relational network space, the core-edge network structure is not entirely horizontal, but is hierarchical, and the hierarchical categorization is not based on its own inherent resource strengths and weaknesses as a single measure, but rather depends on the number of connections between nodes. It can be seen that in the information flow space, establishing information links becomes one of the ways for edge nodes to enter the core subgroups. 3) The core-edge hierarchical structure shows a dynamic change process, which challenges the idea of “the strongest is stronger than the strongest”, and by connecting to the core nodes, the nodes that were originally regarded as peripheral nodes can also be promoted to the core nodes, such as Hotan and Kashgar. The dynamic nature of real-time “reshuffling” and replacement of the positions of each node in the network reflects the importance of observing the development status of cities from informal networks, and can provide new insights for establishing interactive development relationships among cities. This paper not only verifies the innovative idea that networks are hierarchical, but also reveals the dynamic process of hierarchical change through spatial and temporal evolution characteristics, which provides new insights into the establishment of interactive development relationships between cities and provides new practical insights for marginal tourist destinations to become core tourist areas.

Rural spatial governance constitutes a critical component of China's governance framework, serving to regulate the allocation of spatial resources in rural areas, optimizes the spatial development patterns of the countryside, and facilitates integrated urban-rural development. The development of rural industries is the core of the comprehensive revitalization of rural areas and also the key to evaluating the effectiveness of rural spatial governance. However, the development of rural industries in China still faces the crux of insufficient endogenous development momentum and weak endogenous development capacity. Therefore, taking the neo-endogenous development theory as a starting point and using qualitative research and spatial data analysis methods, this paper aims to systematically investigate the process and mechanism of rural industrial spatial governance through a case study of Jianhe Village in Jianhu County, Yancheng City. The key findings are as follows: 1) The industrial spatial governance of Jianhe Village has undergone a transition from bottom-up endogenous governance to top-down exogenous governance, ultimately leading to the neo-endogenous governance characterized by “up-down linkage, internal and external symbiosis”. Rural industrial spatial governance practices at each stage exhibit distinct policy-oriented characteristics. 2) The industrial space of Jianhe Village has witnessed significant resource reorganization, adjustment, and optimization of production space functions. It has also experienced the scale expansion and agglomeration of industrial development, shrinkage in traditional agriculture spaces, as well as expansion in glass industry, e-commerce, and service industry spaces. This transformation has led to an increasingly complex space with characteristics such as production-life, production-ecology, and production-life-ecology interactions. 3) Rural industrial spatial governance constitutes a continuous and dynamic practice process involving multiple actors. The industrial spatial governance of Jianhe Village is a systematic process that effectively integrates and adjusts internal and external development forces under government leadership while placing rural society at its core for coordination with market/society. The resource base serves as a critical foundation, while multiple governance actors function as fundamental decision-makers. Among these, governments act as guiding forces, while markets and societal actors serve as intermediaries for interest coordination, and endogenous rural actors constitute the core element.

Agriculture-related enterprises are representatives of the future advanced productive forces in rural areas, and industry revitalization is an important foundation for rural revitalization. Although there is extensive research on rural revitalization, research focusing specifically on rural industry revitalization is relatively scarce, and research concentrating on the role of agriculture-related enterprises in this process is even rarer. However, such researches provide a fundamental theoretical and practical support for advancing rural industry revitalization, exerting a profound influence on achieving comprehensive rural revitalization. The Yellow River Basin is a key region for population concentration and agricultural development in China, which makes it a significant area for research. Therefore, utilizing municipal panel data of the Yellow River Basin from 2011 to 2020, this paper explores the impact of agriculture-related enterprises development on rural industry revitalization based on the analysis of the development of agriculture-related enterprises and the level of rural industry revitalization. The results show that: 1) From 2011 to 2020, the development level of agriculture-related enterprises in the Yellow River Basin increased from 0.056 to 0.212, showing a spatial characteristic of “high in the northeast and low in the southwest”; 2) From 2011 to 2020, the level of rural industry revitalization in the Yellow River Basin increased year by year, from 0.273 to 0.411, with a spatial distribution of “high in the east and low in the west”; 3) Through the branding of agricultural products and the enhancement of human capital, the development of agriculture-related enterprises significantly promotes rural industry revitalization, and for every 0.1 increase in the level of development of agriculture-related enterprises, the level of rural industry revitalization will increase by 0.067. The increase in the scale, diversity, innovative, marketization and normative of agriculture-related enterprises has, to varying degrees, contributed to level, efficiency, structure and method of rural production. This paper explores the mechanism through which agriculture-related enterprises impacts rural industry revitalization, providing theoretical foundations for understanding their intrinsic relationship and offering references for rural industrial transformation and modernization.

Specialized villages are the boosters of industrial prosperity and an important hand for rural revitalization. Studying the level of specialized villages' resilience and its evolution characteristics is of great significance for optimizing the specialized villages system, enhancing the economic development of agricultural areas, and promoting the implementation of the rural revitalization strategy. Based on the sample data of 50 specialized villages from 2008 to 2017 tracking survey in Henan Province, this article measures the resilience level of specialized villages and explores its evolution characteristics by constructing a specialized villages resilience evaluation index system and combining it with mathematical and theoretical models. The study shows that: 1) 56% of the comprehensive toughness of specialized villages in Henan Province is negative, concentrated in the northern part of Henan Province, the comprehensive toughness of the southern part of Henan Province has increased by nearly 10%, the toughness of service-type specialized villages has declined significantly compared with that of other types of specialized villages, and the area of high value of toughness of agricultural-type specialized villages has shifted from the east to the south. 2) Institutional toughness contributes most to the comprehensive toughness of specialized villages. The ecological toughness of 78% of the specialized villages in Henan Province declined, concentrated in the east of Henan. The cultural toughness and ecological toughness in central Henan Province have both decreased by about 10%, and the cultural toughness and economic toughness in southern and western Henan Province have both increased by more than 35%, with growth hotspots evolving from central and eastern Henan Province to western and southern Henan Province. Industrial-type specialized villages' cultural resilience increased by 16%, but ecological resilience declined by nearly 14%. Service-oriented specialized villages' cultural toughness declined by more than 10%. 3) The cultural dimension is the main short-board element affecting the comprehensive toughness of each type of specialized villages, and the amount of export foreign exchange, the annual sales income of the leading industries, the annual average electricity consumption of rural households, and the per capita water area are specific limiting factors.

Clarifying the evolutionary phenomena and patterns of geographical space is the theoretical prerequisite for achieving coordinated regional development. Current domestic and international research on the evolution of “Production-Living-Ecological Space” (PLES) in the rural areas of metropolitan coordinating regions is predominantly based on single spatial scales and public land use/cover datasets, with in-depth explorations centered on specific issues. A systematic framework that integrates spatial coupling structures, dynamic evolutionary phenomena, core drivers, and internal complex relationships has not yet been established. Moreover, there is a notable lack of empirical analysis supported by appropriate theories and feasible measurement methods. This study, grounded in Complex Adaptive Systems theory, develops a systematic analytical framework to investigate the evolutionary phenomena and patterns of PLES in the rural areas of metropolitan coordinating regions. It integrates methods such as the land use transfer matrix, spatial overlay, spatial autocorrelation, and the Pearson correlation coefficient, covering four dimensions: “aggregation patterns, evolutionary characteristics, evolutionary drivers, and internal relationships”. Using the rural areas in the Yinchuan Metropolitan Coordinating Region as an empirical case, this paper analyzes the spatial aggregation patterns, dynamic evolutionary phenomena, spatiotemporal flow of elements, and complex adaptive relationships of the PLES system since the stage of urban-rural integrated development.This study provides insights and references for numerous rural-related studies in metropolitan areas in the northwest region that share common characteristics.The findings demonstrate that: Within metropolitan regions, PLES in rural areas exhibits typified aggregation patterns; The evolution of these aggregation patterns is characterized by spatial self-limitation and multi-directional objectives, driven by core flow networks to form the primary pathway for spatiotemporal dynamic coupling of PLES.

In the era of financialization and global financial integration, the Global Financial Network (GFN) serves as a crucial analytical framework for comprehending the landscape and the dynamic evolution of global financial geography. While existing research predominantly focuses on international financial centers centered around New York and London, there remains a notable gap concerning local economies successfully integrated into GFN and the hierarchy and regionality of GFN. This study examines the overseas Initial Public Offerings (IPOs) of 79 Quanzhou enterprises to illustrate the key geographic units, network structures, and formation of GFN through intra-enterprise services and collaboration linkages. This study uses Gephi to analyze the network characteristics of global financial networks quantitatively. This study forms the layout of financial centers participating in overseas IPOs of Quanzhou enterprises through the Fruchterman Reingold algorithm. Moreover, this study measured the centrality distribution characteristics of the network using indices such as intermediary centrality and eigenvector centrality. This study selected 79 companies listed on overseas IPOs in Quanzhou from 1993 to the end of 2023 as samples. We confirmed that the FABS enterprise sample includes 50 securities firms, 21 accounting firms, and 56 law firms. From a spatial scale perspective, these FABS corporate offices are distributed in 26 cities worldwide. The cooperative network of FABS enterprises is a network matrix of 371×371, including 205 inter-city collaborations and 166 intra-city collaborations. In addition, from 2020 to 2022, we interviewed 50 interviewees to understand the process of Quanzhou’s integration into GFN. The interviewees of this study include executives of listed companies in Quanzhou, founders of relevant upstream suppliers, leaders of industry associations, and heads of relevant government departments. 1) Quanzhou enterprises, primarily rooted in traditional manufacturing, chose to list neighboring regional financial centers for overseas IPOs, thus contributing to the emergence of a regional GFN. Geographic conditions and industrial profiles of local economics are pivotal in understanding the formation of regional GFN. 2) Within the regional GFN established via Quanzhou’s overseas IPOs, Hong Kong emerges as the central node. Hong Kong serves not only as a key IPO destination but also as a crucial intermediary facilitating Quanzhou’s integration into the global financial landscape. Due to the perspectives of financing entities and financing regions, this study reveals how the location conditions and industrial characteristics of financing regions affect the formation of regional GFN spatial structure. This enriches the perspective of GFN research and, more importantly, deepens the understanding of the existing spatial structure of GFN centered around London and New York. Additionally, the spatial relationships within regional GFN among regional FABS enterprises, regional financial centers, and financing regions, reveal the inherent connections and behavioral patterns of cross-border financial actors. This case echoes the “with” relationship in existing GFN research at the regional scale. This study proposes the hierarchy and regionality of GFN, emphasizing the importance of regional GFNs in global financial flows and responding to the attention of economic geography to the regional transformation of global networks.

Knowledge spillover is a crucial concept for explaining innovation. As a form of knowledge, technology possesses a spillover effect. This study posits that technology enterprises provide technical critical support for modern financial industry development, while financial institutions procure these technical services through market. This process facilitates the establishment of cross-industry urban innovation linkages between technology and financial firms through technological spillover. Distinct from previous research that constructed urban innovation networks based on homogeneous activities or internal connections within the same industry, this study employs Python web scraping technology to collect transaction information and constructs a cross-sector urban innovation network. This transaction data details purchase of technologies—such as Blockchain, Artificial Intelligence, Big Data, Cloud Computing, and the Internet of Things (IoT)—by commercial banks from technology enterprises across cities in China (excluding the data of Hong Kong, Macao and Taiwan). Leveraging these transaction data for technologies applied in emerging FinTech business services, an inter-city FinTech network is constructed from a technology spillover perspective. Network analysis reveals: 1) A FinTech network has preliminarily taken shape in China. Although the network density is not high, it exhibits a core-periphery structure and possesses small-world properties; 2) The geographical concentration of core nodes in the network is pronounced, with transactional linkages closely associated with eastern cities. The core node cities demonstrate outstanding technological spillover capabilities and higher administrative ranks, with Guiyang emerging as a core node in the western region; 3) Distinct network patterns emerge across 3 major urban agglomerations, with differential technology absorption tendencies among 3 types of commercial banks; 4) Urban innovation capability, financial environment, economic development, administrative hierarchy, and transportation accessibility differentially impact technology absorption versus spillover effects. Technology demand-driven spillovers establish the foundation for cross-sector urban innovation networks. The FinTech network will not only provides new paradigms for deconstructing urban innovation systems but also poses new propositions for assessing the competitiveness of cities housing major technology enterprises under integrated finance-technology ecosystems.

The scale characteristics of the city, as well as its functional status in the associated network, jointly shape a new pattern of urban system development. Based on the inter-regional investment data of listed companies from 2005 to 2022, a directed weighted city network is constructed to characterize the network structure and evolution characteristics of the urban system. The measurement method of alternative centrality for directed weighted city networks is improved. According to the dual dimensions of the city size centrality and directed weighted alternative centrality, cities are classified into different levels. The panel vector autoregression model is used to explore the dynamic interaction effects of the economic scale, population size, and network status of cities. The results are obtained as follows: 1) The pattern of city network connectivity is gradually evolving from being driven by the dual core of Beijing and Shanghai to a multi core linkage radiation. The distribution of network connections has gradually achieved full coverage of the “Hu Huanyong Line” in the southeast area with dense and extensive network connections, and shows obvious spatial differences. The high-intensity investment connections are gradually occupying a dominant position. And the city network shows a distinct feature of “hierarchy and network”. 2) The “core-periphery” hierarchical structure of the spatial distribution of directed weighted alternative centrality is constantly manifested. The directed weighted alternative centrality of most cities continues to increase, evolving from being distributed only in the fourth level to the sixth level to covering all 6 levels. The number of capital agglomeration cities has increased significantly, and the asymmetric characteristics of nodes in the city network are significantly enhanced. 3) Under the dual dimensions of “size-network”, cities are classified into 5 grades: national core cities, national sub-central cities, regional core cities, regional sub-central cities and local general cities. The typical manifestations are the “scale-network” status matching type cities represented by Beijing, Xi’an, Suqian, and there are also the “scale-network” status non-matching type cities represented by Chongqing, Hefei, Luoyang, Zhoushan. 4) There is a significant sustained positive interaction effect between directed weighted alternative centrality and economic scale. The change of population size has a relatively long-term one-way effect on directed weighted alternative centrality, while the change of directed weighted alternative centrality has only a short-term positive effect on population size. The conclusions are helpful to deepen the understanding of the structural characteristics of urban system and provide reference for optimizing urban development strategy and promoting regional coordinated development.

Intercity relationships can be categorized into multiple types, with collaborative relationships and flow relationships being 2 of the main types. Collaborative relationships stem from cities with similar functions achieving economies of scale or with different functions achieving functional complementarity, while flow relationships arise from the potential differences between source and destination cities. This study, based on an analysis of the differences in the formation of collaborative and flow relationships, examines the structural and influencing factors of collaborative and flow networks from the perspective of venture capital relationships. The study finds that the differing mechanisms of these two types of network relationships lead to differences in the influence of distance and city size combinations. However, both types of networks exhibit a certain degree of similarity in reflecting the regional economic landscape, such as displaying similar hierarchical structures. Moreover, while two-way aggregated flow networks are relatively similar to collaborative networks, one-way flow networks can more accurately reveal the characteristics of flow relationships. By analyzing 20 311 venture capital events across 251 Chinese cities, we highlight that core cities like Beijing, Shanghai, and Shenzhen dominate both networks, yet their roles diverge: Shanghai acts as a capital supplier, while Shenzhen exhibits stronger capital outflow. The gravity model reveals that city size significantly enhances collaboration and capital flow, whereas geographic distance inhibits only the latter. Notably, directional flow networks uncover asymmetric patterns, with 144 cities solely contributing capital outflows. These findings challenge the conventional aggregation of bidirectional flows in urban network studies, demonstrating that unidirectional analysis better captures power dynamics in resource allocation. The study underscores the necessity of integrating relational typologies—such as collaboration versus flow—into urban network frameworks to refine theoretical interpretations of intercity interactions. Practically, policymakers should tailor strategies for capital-attracting versus capital-exporting cities to optimize regional economic synergies. This study distinguishes the pattern differences between collaborative and flow relations, highlighting the importance of differentiating relationship types in urban network research.

Urban agglomerations serve as crucial bridges facilitating the flow of cross-regional innovation factors and promoting technological spillovers among cities. Most existing literature treats urban agglomerations as the analytical boundary, overlooking the differentiated impact of urban agglomeration strategies on inter-city technology transfer. To address this, based on Chinese patent transfer data from 2001 to 2020, this study analyzes the overall characteristics and spatiotemporal dynamics of patent transfers within cities within 19 urban agglomerations, between urban agglomerations and their surrounding cities, and among cities in different urban agglomerations across four time periods. Utilizing a difference-in-differences model, the study examines the impact of urban agglomeration strategies on patent transfers at different scales, focusing on the coordination effect, agglomeration effect, and linkage effect of urban agglomerations. The study found that: 1) The scale and density of the patent transfer network in 19 urban agglomerations have been continuously increasing, with deepening connections and intensities. The network efficiency and accessibility have been continuously optimized, and the spatial distribution of the patent transfer network overall presents a pattern of ‘high in the east and low in the west’. 2) The spatial structure of the patent transfer network in urban agglomerations exhibits characteristics of polycentricity and regionalization, with the ‘diamond structure’ centered around Beijing, Shanghai, Guangzhou, and Chengdu-Chongqing gradually emerging. This structure forms a "hub-and-spoke" knowledge flow channel with other regional central cities. 3) The proportion of patent transfers across agglomerations has gradually increased, indicating that the spatial scope of knowledge innovation is expanding and the spatial heterogeneity of knowledge flows is decreasing. 4) The results of the difference-in-differences model verify that the urban agglomeration strategy can promote patent transfers within cities within the same urban agglomeration, between urban agglomerations and their surrounding cities, and between cities in different urban agglomerations. Overall, the implementation of the urban agglomeration strategy has not only played a significant role in regional development but also had a profound impact on inter-city technology transfer in China. This study analyzes the dynamic changes of patent transfer networks within and outside urban agglomerations from multiple dimensions and delves into the differentiated impact of urban agglomeration strategy implementation on China’s intercity technology transfer network. It provides new perspectives and ideas for understanding the evolution of intercity innovation networks and the future innovation development of urban agglomerations. Through this study, it is hoped that the spatial organization mechanism of technology transfer networks can be further deepened, providing scientific support for better promoting innovative integration practices in urban agglomerations and promoting technological innovation and high-quality economic development in urban agglomerations.

Current research on urban networks still has some shortcomings, such as insufficient analysis of industrial chains, neglecting the distinction between local and non-local embedding, and insufficient attention to industrial connections in the digital economy. In view of this, this article attempts to take the Chinese digital game industry as an analytical case. Based on the basic paradigm of urban network research, it starts from the perspective of industrial chain division of labor, focusing on exploring the urban network structure and cooperation models formed by the digital game industry through industrial chain division of labor. It further analyzes the industrial chain position and the evolution of local-global embeddedness of the Chinese digital game industry, thereby promoting the dialogue between urban network research and industrial chain theory and solidifying the analysis of the industrial connection connotation in urban network research. This study selected cooperation data at both the national and global scales from 2013 to 2023, involving 283 cities worldwide. Social network analysis was employed to measure the urban cooperation network structure of China’s digital games, and the internalization link index was used to analyze the differences in local and cross-city connections of game enterprises at different spatial scales. The findings are as follows: 1) The national-level city collaborative network of China’s digital gaming industry has a polycentric structure, reflecting the decentralized characteristics of the digital economy; at the global scale, there exist 3 collaborative models: “Overseas R&D and Publishing-Domestic Operation” (Model 1), “Domestic R&D-Overseas Publishing and Operation” (Model 2), and “Domestic Publishing and Operation-Overseas R&D” (Model 3). Model 1 has the largest network of cities, and Models 2 and 3 are expanding rapidly. 2) Overall, Chinese cities are still in the middle and lower segments of the global digital gaming industry chain, with significant dependence on cities in the United States, Japan, and Europe in the R&D and publishing sectors. However, with the rapid development of Models 2 and 3, cities represented by Beijing, Shanghai, Chengdu, and Xiamen are continuously upgrading their positions in the global industry chain. 3) Over the past decade, the local-global connectivity of China’s core gaming cities has undergone significant spatial restructuring, mirroring the global industrial chain reconfiguration. Nationally, most cities have transitioned from localized to cross-city domestic collaborations, aligning with the delocalization trend in digital creative industries. Globally, Chinese cities demonstrate reduced external dependency, shifting from strong international-weak domestic ties to domestic-dominated collaboration patterns, with Shanghai emerging as the sole metropolis sustaining robust dual local-global linkages. These evolving spatial embeddedness patterns reflect the industry’s self-optimization and value chain upgrading trajectory. This study contributes to the dialogue and incorporation between industrial chain and urban network research. Future research needs to analyze in more detail the driving mechanisms, globalization strategies and local embedding patterns of Chinese cities’ participation in the division of labor in the global digital game industry chain through more in-depth enterprise surveys and industry chain analyses.

This study constructs a network based on investment data from listed companies among cities. It uses social network analysis and structural resilience indices to measure and evaluate the investment network structure and resilience in the urban agglomeration in the middle reaches of the Yangtze River. The results show that: 1) The urban agglomeration in the middle reaches of the Yangtze River is forming a triangular investment skeleton with Wuhan-Changsha-Nanchang as the vertex. The overall investment network density remains low but continues to grow. Cities play different roles in the network, and core cities are strengthening their control. 2) The investment network shows clear heterogeneity and hierarchy, making it vulnerable to shocks. However, it is gradually becoming more balanced and flat. 3) The network has strong matching resilience. Connections between nodes tend to be heterogeneous and diverse. Enterprise investment flows enhance the “robustness” of these connection paths through overlap. 4) The network has high and improving transmission efficiency. Overall, it demonstrates strong connectivity resilience. 5) The network shows some clustering. Investments mainly flow one-way from core cities to peripheral cities. This helps peripheral cities develop while reducing risks for core cities, improving the network’s structural resilience.

Accurately understanding the connotation and meaning of ecological interests in national territory space, explore the mechanism of the allocation of ecological benefits in national space, is the foundation for resolving spatial conflicts and optimizing the pattern of national territory space development and protection. Research has shown that: 1) The naturally formed spatial environment and the profit-seeking human mechanism, the market mechanism that plays a decisive role in resource allocation, and the policy mechanism for correcting market failure jointly affect the mechanism of ecological interest allocation in territory space. 2) The function of ecological benefit allocation in national territory space is to implement the structure of national land spatial planning, ensure the spatial redistribution of ecological benefits, and correct the profit seeking nature of market mechanisms. 3) The standardized spatial structure, rational allocation of public resources, and effective allocation of spatial rights are the predetermined benchmarks for ecological benefit allocation. At present, the spontaneous allocation of ecological interests in national territory space is characterized by prominent competition in spatial use, numerous misallocations of spatial resources, unequal spatial rights, and hidden concerns about the imbalance of secondary allocation boundaries. It is necessary to define the bottom line boundary of the ecological carrying capacity of the “three lines and one order” and the upper limit boundary of constraining government power for the allocation of ecological interests in national territory space, optimize the collaborative mechanism of ecological interests allocation in national territory space, reasonably allocate ecological interests at different spatial scales, and achieve the universal sharing of ecological interests.

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) produced by microorganisms such as bacteria are important tools for reconstructing past climatic and environmental changes. However, previous works on brGDGTs mainly focus on various proxies based on their distributions, whereas environmental controls on their concentration remains unclear. This hampers our proper understanding on the climatic significance of brGDGT concentration in geological records as well as the seasonality of brGDGT proxies. This study investigated brGDGT concentration in surface soils in different regions of China and analyzed its correlations with environmental factors. The aims were to: 1) Explore environmental controls on soil brGDGT concentration, 2) Verify whether soil brGDGT concentration can be used as a paleoclimatic proxy, and 3) Clarify the seasonal bias of brGDGT-based paleotemperature proxies in soils. Totaling 273 natural soils were collected during 5 fieldtrips from 5 regions including: the Chinese Loess Plateau and its surroundings, North China to Northeast China, South China, the Shandong Peninsula, and the Northeast Tibetan Plateau. The correlations between brGDGT concentration and aridity index (AI), soil pH, and mean annual air temperature (MAAT) were analyzed. For the whole surface soil dataset, brGDGT concentration showed stronger correlations with AI and soil pH (r = 0.81 and −0.74, respectively) than that with MAAT (r=0.10). For the 5 different regions, brGDGT concentration all correlated positively with AI and the correlations were strong or moderate (0.94>r>0.42). On the other hand, the correlations with pH or MAAT were generally weaker and not stable. Specifically, brGDGT concentration correlated negatively with soil pH with r ranging from −0.17 to −0.75, except for a positive correlation (r=0.98) for soils collected from the Shandong Peninsula, while negatively with MAAT with r ranging from −0.12 to −0.94, except that no correlation (r=0.02) was observed for soils collected from the Chinese Loess Plateau and its surroundings. The strongest and most consistent correlations between brGDGT concentration and AI across regions and the whole dataset indicate that soil moisture is the controlling factor for brGDGT production in surface soils. Therefore, we propose that variations in brGDGT concentration in geological records, such as loess-paleosol sequences, can potentially be used to indicate past drying and wetting events. Moreover, our results imply that the seasonal bias in brGDGT-based paleo proxies, traditionally believed to reflect the seasonality of temperature, can also be influenced by seasonal changes in soil moisture (precipitation).

Severe air pollution disrupts traffic, poses significant health risks, and adversely affects economic development. Therefore, systematically analyzing the causes of severe pollution in typical urban areas and accurately predicting the occurrence of severe pollution events is of considerable scientific and practical importance. The northeastern region of China, a major hub for heavy industry and agriculture, is characterized by its northernmost latitude and longest heating period, making its emission sources and meteorological conditions highly representative. This study focuses on Baicheng City, a plain-type city in Jilin Province, and utilizes multi-source data from 2015 to 2022, including air quality, meteorological, satellite, and remote sensing data. Through a systematic analysis of the underlying causes of severe pollution events, we identified the most effective machine learning algorithm for predicting PM_2.5 concentrations during such events.The results indicate that, prior to 2017, Baicheng City experienced a high frequency of severe pollution events, primarily occurring in late autumn, early winter, and deep winter. However, after 2017, the number of severe pollution days significantly declined. Severe pollution events were classified into four primary types: local emission-driven, transmission-dominated, meteorologically-induced, and composite pollution, with composite pollution being the most prevalent. A machine learning-based prediction algorithm was developed using air quality, meteorological, and remote sensing data during severe pollution episodes to forecast PM_2.5 concentrations in Baicheng. Among the tested models, the XGBoost algorithm demonstrated the best performance, with an R² of 0.92 and a root mean square error (RMSE) of 24.6 µg/m³, significantly outperforming other algorithms such as Random Forest (R²=0.87) and Support Vector Machine (R²=0.67). This study provides a straightforward, accessible, and highly accurate process and algorithm for predicting severe pollution events in plain-type cities of northeastern China, offering valuable insights for the effective management of atmospheric environmental conditions.

The study of functional division within urban agglomerations holds paramount significance in optimizing the urban system and promoting the coordinated development of large, medium, and small cities. While existing research predominantly examines the pattern of functional division from the perspective of urban functional disparities, there is a notable dearth of studies focusing on the relational aspect of inter-city functional linkages. By integrating functional monocentric-polycentric theory, supply chain relationships, and urban network analysis, this paper establishes a functional division model and delineates partitioning methods alongside corresponding thresholds, and conducts empirical analysis of data from the supply chain of Chinese listed companies across 19 urban agglomerations in China, offering a comprehensive understanding of functional division within urban agglomerations. The main findings are as follows: 1) The functional division linkage patterns from the supply chain perspective can be divided into centrifugal monocentric pattern, centripetal monocentric pattern, and balanced polycentric pattern. Furthermore, these division linkage patterns effectively discern the structure of urban agglomerations in China, with each linkage pattern linked to the hierarchical structure of functional linkages and the stage of development within urban agglomerations. 2) The centrifugal monocentric pattern is dominated by urban agglomerations with sparse functional linkages and the stage of optimization and upgrading, such as Lanzhou-Xining, Ningxia along the Yellow River, and Huhhot-Baotou-Ordos-Yulin. The centripetal monocentric pattern is dominated by urban agglomerations with less-connected functional linkages and the stage of development and growth, such as the Pearl River Delta, Chengdu-Chongqing, and the Central Plain. The balanced polycentric pattern is dominated by urban agglomerations with well-connected functional linkages and the stage of optimization and upgrading, such as the Yangtze River Delta, the Shandong Peninsula, and the middle reaches of the Yangtze River. 3) Diverse urban agglomerations adhere to distinct evolutionary pathways in terms of functional division patterns, while most pattern evolution occur between centrifugal monocentric pattern and centripetal monocentric pattern, evolutions between monocentric pattern and polycentric pattern are relatively rare, indicating that the current functional division relationship in China’s urban agglomerations is primarily characterized by a core-city-led monocentric pattern, with the formation of polycentric pattern facing a certain threshold. By scrutinizing the functional division linkage pattern of China’s urban agglomerations through the lens of supply chain dynamics, this paper contributes to expanding the scope of regional division studies beyond attribute data and lays a solid foundation for subsequent research grounded in related data analysis.