Urban–rural integration is a necessary way to realize the strategy of rural revitalization in the new era, and exploring the characteristics of the spatial correlation network of China's urban-rural integration and its formation mechanism is important for developing a comprehensive understanding of the spatial transmission mechanism of interregional urban-rural integration and provides a new policy perspective for the synergistic enhancement of the urban-rural integration level in each province. Based on China's interprovincial panel data from 2001 to 2021, the entropy method was applied to measure China's interprovincial urban-rural integration level, and the modified gravity model and social network analysis were used to explore the structural characteristics of China's spatial correlation network of urban-rural integration and its influencing factors. The results revealed the following: 1) During the study period, the level of China's interprovincial urban-rural integration showed an increasing trend, but the process of improvement was slow. Spatially, it showed a decreasing gradient from east to west, but the gap between the interprovincial urban-rural integration level gradually narrowed, with obvious spatial non-equilibrium. 2) China's urban-rural integration spatial association network became increasingly dense, complex, and close, and the main linkage flows of urban-rural integration occurred between geographically neighboring provinces and cities, such as Shanghai-Jiangsu, Shanghai-Zhejiang, and Beijing-Tianjin. The network connection was heterogeneous, and the network showed the characteristic of growth. However, the spatial connection of urban-rural integration did not reach the best level, and there is still much room for improvement. 3) Geospatial proximity, differences in the level of economic development, and urbanization had a significant positive effect on the optimization and evolution of the spatial linkage network of urban-rural integration, while differences in agricultural modernization and differences in advanced industrial structure showed a stage-by-stage effect over time. Differences in the scale of financial services did not have a significant effect. Accordingly, this study proposes countermeasures to optimize the spatial correlation network of urban-rural integration in China. Theoretically, it helps to deepen knowledge of the spatial effect and regional transmission of urban-rural integration in the geographical perspective. In practice, optimizing interprovincial urban-rural interaction and promoting cross-regional urban-rural integration development in a scientific and rational way are highly significant.

The construction of smart borders has become a key issue in ensuring China's border security, maintaining the country's geopolitical stability, and promoting sustainable development. Against the backdrop of a changing global security landscape, particularly the increasing likelihood of non-traditional security threats, such as cybercrime, terrorism, and environmental risks, the need for a more sophisticated technology-driven approach to border management has become ever-more pressing. By quantitatively analyzing the literature related to smart borders between 2001 and 2022, using CiteSpace software and the Web of Science database as a data source, we aim in this paper to provide a comprehensive review of the development of the field of smart border research, to assess the hotspots and themes of current research, and consider future directions in the field. The results of the study revealed that smart border research is still very much in its infancy, and although there has been a general upward trend in the number of published articles, the volume of relevant research is still comparatively low. Furthermore, the distribution of smart border research groups appears to be relatively decentralized, with only a small number of collaborative initiatives to date, and, as yet, no prominent networked group of authors, with a large proportion of the research being conducted in the United States, the United Kingdom, China, Canada, and Germany. Among the topics addressed in smart border research, border security appears to be the subject of most concern, with immigration management and intelligent surveillance being particular focuses of smart border construction. On the basis of our review, we identified six areas that are the primary focus of current smart border research, namely, the connotation of smart borders, smart border demand, smart border systems, early warning mechanism construction, re-bordering and intelligence, and border strategy and cross-border cooperation. As an emerging research field, despite the preliminary results, smart border studies are still facing problems relating to practical application, such as weak theoretical foundations, an insufficiently developed methodological basis, and conflict between "human defense" and "smart defense," Our findings highlight the need for future studies to focus on establishing a sound theoretical and methodological framework underpinning smart border research, building a smart border control system adapted to China's national conditions, strengthening the precise control and early warning research of border corridors, and examining the modes of multi-subject linkage and humanized governance. Through interdisciplinary integration, drawing on international experience, and promoting the innovation of technology and governance models, the construction of China's smart borders can effectively respond to both traditional and non-traditional security threats, and enhance the precision and efficiency of border management. Having surveyed the current state of smart border research, we propose the following steps to promote the development of China's smart borders. Firstly, smart borders should be comprehensively integrated into the national security strategy to ensure that the system meets China's specific border security needs. A smart border management model with Chinese characteristics should be constructed, emphasizing data sharing, technological interoperability, and coordination and cooperation among all parties. Secondly, with a view toward enhancing border management efficiency, it is recommended that interdisciplinary cooperation be strengthened, international best practices be drawn upon, and technological innovations be promoted. Given the efficient implementation of these measures, China will be able to respond more effectively to traditional and non-traditional security threats, ensure border security and efficient management, and thus maintain stability and sustainable development within an increasingly complex global security environment.

The Internet, one of the hallmarks of information technology, has had a profound impact on social life, enriching public social activities while simultaneously altering traditional patterns of social trust formation. While academic attention has been given to the role of internet usage in shaping social trust, there remains a lack of further clarification regarding the spatiotemporal evolution of social trust across provinces in China under the influence of the Internet, as well as the differentiated effects of various internet usage patterns on social trust. This issue warrants further in-depth exploration to gain a more nuanced understanding of the dynamics. Based on data from the China Family Panel Studies between 2016 and 2020, this study constructs a theoretical framework to examine the impact of Internet usage patterns on social trust. Investigated the spatiotemporal evolution characteristics of social trust in China and used an Ordered Probit model to analyze the effects of different Internet usage methods on social trust. The findings reveal that the development of the Internet has created more possibilities for constructing social trust across various dimensions, thereby broadening the channels through which social trust is formed. Moreover, it has enriched the avenues through which both trust in strangers and acquaintances is generated, highlighting the role of the Internet in facilitating the establishment of trust within and beyond familiar social networks. Second, social trust in China is primarily based on trust among acquaintances. The levels of trust in acquaintances across the Eastern, Central, Western, and Northeastern regions exhibit a spatiotemporal evolution pattern of "low-high-low." Moreover, trust in strangers increased significantly over time across all regions. Overall, the level of social trust demonstrated an upward trend, indicating a general improvement in the willingness to trust both familiar and unfamiliar individuals across the country. Third, different internet usage methods have varying effects on social trust. The positive facilitation effect of information transmission benefits trust in acquaintances and strangers, contributing to higher levels of social trust. This suggests that the role of the Internet in disseminating information is crucial for fostering trust across various social groups. Fourth, the "dual-sided" effect of online social networking, as observed in this study, is manifested in its deleterious impact on trust within established social circles while simultaneously exerting a constructive influence on trust in individuals outside one's immediate network, thereby exemplifying the role of the Internet as a double-edged sword, where its capacity to both enhance and undermine trust depends on the nature of the interaction and the context in which it occurs. This study has significant implications for the scientifically sound and rational utilization of the positive role of the Internet as well as for balancing the development of information technology with social progress. This emphasizes the need to align technological advancement with the broader goals of fostering social trust and promoting social development.

Analyzing the spatial relationship between urban spatial patterns and the thermal environment and quantifying zoning to regulate the urban thermal environment according to local conditions is essential. Previous research on the spatial heterogeneity of factors influencing thermal environments is lacking, and there are shortcomings in the actionability of thermal environment regulation. This study takes the main urban area of Wuhan as an example, based on multi-source spatial data such as Landsat-8 remote sensing images, urban land classification, and buildings, integrates geodetectors and a geographically weighted regression model (MGWR) to investigate the mechanism of the influence of the urban form on the thermal environment under the control unit at the global and local levels, and finally utilizes the K-mean clustering approach to perform impact zoning. First, the high-temperature areas in the main urban area of Wuhan are mainly located in the core area of the old city of Hankou and the Wuchang District, which are located on both sides of the Yangtze River, as well as in the industrial zones northeast and southwest of the city. In terms of land-use types, industrial, logistics and warehousing, and street and transportation had higher average surface temperatures, whereas water area, green space and square, and agricultural and forestry had lower average surface temperatures. Second, the three-dimensional (3D) building indicator had a greater overall impact on the thermal environment than the two-dimensional (2D) urban land-use type indicator. Building density (q = 0.479) was the dominant factor affecting the thermal environment. While the share of water area in 2D form had the strongest explanatory power, the other indicators were relatively weaker. Third, there was spatial heterogeneity in the impact of indicators on the thermal environment, with strong locally driven characteristics for indicators such as vegetation cover, percentage of industrial land area, and building density (BD). Finally, according to the MGWR regression coefficients of each indicator, the main urban area of Wuhan was divided into four types of impact zones, and the intensity and direction of the impact of indicators in different impact zones changed, which confirms the necessity of a zoning policy. 3D buildings form the dominant zone and the BD strong dominant zone are suggested to adjust the urban building form as the main goal, the percentage of water area and BD co-dominant zones are suggested to optimize the urban blue-green space as the main regulation goal to improve its cooling efficiency, and the integrated transition zone is suggested to synergistically optimize the 2D/3D urban spatial form. In conclusion, from the perspective of planning practice, combined with the different impact characteristics of each control area, we propose a differentiated control strategy combining "planning units + planning indicators," which provides a practical approach to optimize the climate-friendly urban form.

The outbreak of the coronavirus disease (COVID-19) pandemic, subsequent pandemic containment measures, and economic fallout have had a profound impact on people's employment choices, residential preferences, and travel habits. However, limited empirical studies have investigated longitudinal changes in the jobs-housing relationship, which is a critical intersection of these three elements during the global health crisis. Based on mobile signaling data from 2017 to 2022, this study employed visualization, employment activity compactness, and multinomial logistic regression to explore the multi-scale spatiotemporal evolution characteristics and causes of jobs-housing balance in Shenzhen during the COVID-19 pandemic. The results were as follows. (1) The spatial distribution patterns of residences and workplaces experienced the following evolutionary process: aggregation before the COVID-19 pandemic, dispersal during the strict control period of the pandemic, and, in the normalization phase, continuous dispersal in the first circle, as well as a rebound in the second and third circles. (2) Prior to the COVID-19 pandemic, jobs-housing relationships deteriorated; during the strict control period, employment self-containment remained stable, while cross-unit commuting distance significantly decreased, employment self-containment steadily improved, and cross-unit commuting distance returned to pre-pandemic levels. This trend is most prominently manifested at the 1 km grid scale across the three research scales. (3) Spatial heterogeneity affected the evolution trends of jobs-housing relationships before and during the pandemic, with public transportation accessibility and socioeconomic characteristics of residents being the main reasons for differentiation in evolutionary types. During the pandemic, regions with high dependency ratios, low average ages, and low educational levels exhibited delayed optimization of employment self-containment compared to regions with poor public transportation accessibility. Highly educated individuals were more likely to experience a continuous reduction in cross-unit commuting distances; migrant workers, older individuals, and female groups witnessed a decrease in cross-district commuting distances during the strict control period but a rebound extension during the normalization phase. The results contribute to a better understanding of the evolution of job-housing relationships during public health crises and provide support for future urban management.

This study considers the fishery industry in the coastal area of Fujian Province as an example, measures the resilience resistance of the fishery industry using output value and output, and constructs an analytical framework by combining the "Robustness-Resistance-Recovery" resilience assessment framework and the theory of institutional change to give explanations for the formation of the differences in fishery resilience. The four types of gradually deepening institutional changes are layering (thickening and positive layering), conversion, and displacement. The robustness dimension of resilience corresponds to thickening, the resistance dimension corresponds to positive layering, and recovery corresponds to conversion or displacement. Three main conclusions are drawn: 1) Under the influence of different types of shocks (the super-typhoon in 2006, the financial crisis in 2008, and the upgrading of the fishing industry in 2017), the output value fluctuates significantly owing to the dual effects of production and supply, and the output is more strongly affected by production and more drastically reflective of natural disasters. 2) A spatial regularity exists in the impact of regional crises (typhoons) on industrial resilience resistance; the closer to the disaster center, the poorer the performance of industrial resilience resistance. The economic and industrial transformation crises have a homogeneous effect on the fishery economy, and the spatial differences in the resilience of the fishery economy are more influenced by historical foundations and institutional evolution. 3) The 25 research units in coastal areas were divided into five categories. The spatial distribution of fishery resilience is affected by coastline length. High-resilience areas were mainly concentrated in the middle of the coastal region in the study units with longer coastlines. The resilience of the north and south ends improved from year to year, and the length of the coastline in the areas with lower resilience was shorter. Differences were noted in the performance of each region in terms of resilience to shocks, including robustness, resistance, and resilience, as well as differences in the depth of institutional change types. Regions that choose the right development path and the right mode of institutional change in a crisis are more resilient and help the region reduce resource constraints on fisheries development, even if it is a thickening of the original system that can defuse the crisis, whereas a few regions are less resilient in choosing a direction of institutional change that is separatedfrom the region's industrial base, where new development paths have yet to take root. This study highlights the importance of regional institutional change in the formation of fishery resilience, provides a new perspective on how institutional change affects economic activity, and uses quantitative methods to investigate the relationship between institutional change and industrial resilience. In addition, this study has important implications for disaster response and risk management, helping firms and governments better prepare for and respond to potential economic shocks.

Zen culture, a resort within the heritage of Eastern culture, is uniquely expressed through Zen tourism, which blends traditional Chinese culture with travel. This study constructs a theoretical framework of "space-situation-identity" and selects 32 non-religious tourists who participated in Zen tourism for the first time as research samples. Using qualitative methods, this study investigated how non-religious tourists construct and transform their identities through Zen tourism. The findings indicate that motivations for participating in Zen tourism include four dimensions: religious attraction, physical and mental relaxation, emotional connection, and self-discovery. This study constructs the "space-situation-identity" conceptual framework and applies it to Zen tourism. The framework reveals the following insights: "spatial contextualization" and "contextualization of identity" are two stages experienced by Zen tourists, corresponding to identity perception and acquisition, respectively. During these stages, the unique spatial characteristics of Zen tourism sites, regulation and guidance by unofficial organizations, and mutual influence among fellow participants significantly impacted the self-identity transformation and social identity acquisition of Zen tourists. "Identity contextualization" and "contextualization of space" are the two stages when Zen tourists return to the real world, leaving the religious Zen sites, corresponding to individual identity maintenance and identity constraints. In these stages, the identity maintenance of Zen tourists shifts from passive "construction by others" to active "self-construction." This study enriches the research on the identity and role evolution of tourists in religious contexts, emphasizing the need for further exploration of how tourists interact with their environment to form experiences, thereby providing more specific insights and understanding of religious tourism in postmodern society. Furthermore, this study investigates the Zen tourism experiences of non-Zen practitioners in major cities such as Beijing, Shanghai, Guangzhou, and Shenzhen, responding to and expanding existing theories of space, situation, and identity in tourism experiences. It constructs the "space-situation-identity" conceptual framework, highlighting that the identity transformation of Zen tourists involves multiple factors from space and situation, while their new identities influence the elements of space and situation. The interaction between space, situation, and identity is prevalent in various forms of religious tourism across different regions. Similar to this study, most religious sites create a series of sacred contexts through spatial designs and social scene construction. These contexts provide tourists with a new life order and inner meaning, thereby enhancing their religious identities. This study offers several suggestions for optimizing Zen tourism in China. First, organizers should select locations with beautiful natural environments, fresh air, and sites far from urban noise for Zen tourism and improve transportation, accommodation, dining, and wellness facilities to provide comprehensive physical and mental healing services. Second, in addition to experienced Zen instructors, organizers should invite relevant mental health experts to offer professional Zen guidance and psychological counseling to tourists. Third, personalized Zen tourism products should be designed to meet the diverse needs of tourists.

To build world science and technology power, industry, universities, and research institutes must complement each other in technological innovation. Currently, China has not yet fully shifted from a university- and research-centered to an enterprise-centered innovation system. Investigating and comparing the spatiotemporal changes and influencing factors of technological innovation efficiencies of firms, universities, and research institutes to optimize the allocation of regional innovation resources and improve regional innovation policy is important. Using 31 provincial-level administrative regions in China as decision-making units, this study measures and compares the spatiotemporal changes in technological innovation efficiencies and the factors influencing the technical inefficiencies of the three entities using GIS spatial analysis and Stochastic Frontier Analysis. The main findings are as follows. 1) The technological innovation efficiencies of firms, universities, and research institutes show a steady increase over the study period, with a 45–55% improvement space. Firms have the lowest technological innovation efficiency but the fastest growth rate in technological innovation efficiency. Firms are expected to surpass the technological innovation efficiency of research institutes in the next two years; however, there is still a large gap with universities, indicating that firms have not yet become key players in the innovation system. 2) The spatial differences between the technological innovation efficiencies of firms, universities, and research institutes are significant. Only a few provinces have formed a situation of industry-university research in tandem, suggesting a certain degree of spatial mismatch between technological innovation efficiency and regional economic development. Our analysis shows that regional differences in the technological innovation efficiency of innovation entities are closely related to regional innovation modes. 3) Technological inefficiency factors coexist in the regional innovation milieu and industry-university research cooperative innovation. The direction and magnitude of the impacts of exogenous environmental variables— infrastructure, market environment, labor quality, financial markets, and entrepreneurship—on technological inefficiencies vary with the type of innovation entity. Collaborative innovation among enterprises, universities, and research institutes has significant positive effects on technological innovation efficiency, except for research institutes technological innovation efficiency when collaborating with enterprises. The reason for the insignificant effect of enterprise-research institute collaborative innovation on research institutes' efficiency may be that both research institutes and firms consider technological application and development as the main goal of collaborative innovation, and collaborative innovation with firms crowds out the internal innovation resources of research institutes and inhibits their technological innovation activities. We contribute to the literature on regional innovation systems by comparing the differences in the technological innovation efficiency of the main innovation entities in the regional innovation systems of a transition economy. Our findings provide a basis for the rational allocation of technological innovation resources and the optimization of the regional innovation environment.

As a crucial capital intermediary, the securities industry has gradually become an integral part of financial markets and plays a vital role in shaping financial center cities. Although the securities industry of China has a relatively short history of development, its spatial structure has undergone a substantial transformation. Nevertheless, the existing research has yet to thoroughly investigate the spatial evolution of the securities industry, especially in terms of how institutional arrangements impact its spatial organization. This study systematically analyzes the establishment, exit, and headquarters relocation of securities companies across China from 1992 to 2022 and investigates the role of institutional arrangements in shaping the spatial configuration of the securities sector. The main findings reveal three critical insights. (1) The spatial distribution of securities company headquarters in China has evolved from a dispersed to a highly concentrated layout. During the formative years of the industry, most provincial capital cities in China established local securities companies, resulting in a relatively scattered distribution of headquarters across the country. However, as the industry expanded and matured, securities companies in smaller cities gradually relocated or shut down, and new establishments or relocations of securities companies became predominantly concentrated in Beijing, Shanghai, and Shenzhen, causing these three cities to gradually become the central hubs of the industry. (2) Institutional arrangements concentrated on key securities resources in a few selected cities, forming the foundational spatial structure of China's securities industry. From the early days of the industry, central government policies have played a decisive role in shaping the spatial organization of the securities sector. Shanghai and Shenzhen were designated the only cities legally permitted to host stock exchanges, granting them a unique infrastructural advantage that naturally fostered the growth and concentration of the securities industry. Beijing, the location of the China Securities Regulatory Commission, has been pivotal in shaping the spatial structure of the industry. The centralized regulatory and financial infrastructure, combined with preferential policies for key cities, has created a distinct pattern of spatial concentration, with Beijing, Shanghai, and Shenzhen forming the core centers of China's securities industry. (3) Institutional factors consistently influence the spatial dynamics of the securities industry across its developmental stages. From the early government-directed capital deployment to establish local securities companies to state-owned enterprises' involvement in managing high-risk securities companies during industry cleanups, institutional factors have been crucial in shaping the evolution of the industry's spatial distribution. Recently, regulatory interventions for foreign-invested securities firms, including policy-driven decisions regarding the location of their headquarters, have played a significant role in consolidating the industry within major financial hubs. These interventions, including preferential policies, mergers and acquisitions, and support for foreign investments, significantly altered the distribution of securities companies across China. The evolving regulatory landscape, along with China's unique institutional characteristics, has ensured that the country's securities industry remains highly centralized, with significant financial resources concentrated in key cities. This study theoretically addresses the gap in Western-focused perspectives by highlighting how institutional factors shape the spatial structure of China's securities industry. While the clustering of securities firms in financial centers may align with market trends, China's distinctive institutional framework has acted as a powerful force driving the spatial evolution of the industry. Thus, this study provides valuable insights into the dynamic spatial patterns of the financial sector within China's regulatory environment, contributing essential perspectives on the development of financial center cities and deepening our understanding of the mechanisms shaping financial center cities under China's unique institutional conditions.

Based on a literature review and policy analysis, this study analyzes the evolution of the regional governance regime in China since its reform and opening-up, and examines how this process has influenced the development of contemporary metropolitan areas. Multiscale spatial development strategies and regional governance regimes have been formed because of different development goals and visions in regional development. As a crucial mediating scale in China's regional governance, the construction of metropolitan areas has exhibited notable variation in governance subjects, structures, and developmental effects during different development phases. From the perspective of spatial governance goals, factor allocation means, and their scalar characteristics, this study categorizes China's regional governance into four periods since the reform and opening-up in the late 1970s: i) regional economic growth driven by development zones (1978-1993), ii) regional resource reallocation through administrative adjustment (1994-2000), iii) regional coordinated development through the development of industrial parks and new national-level areas (2001-2015), and iv) multi-level governance of urban agglomerations and metropolitan areas (2016-present). Governance forms and functional characteristics varied across different periods, contributing to a shift in China's regional governance from a centralized planned economy to a multilevel regulatory governance model. As metropolitan areas have become a key strategy in the new type of urbanization process, their development at different stages has exhibited different governance structures and functional characteristics. This study systematically reviews the evolutionary characteristics and driving factors of the regional governance stages and compares the first three metropolitan areas approved by the central government: Nanjing, Chengdu, and Fuzhou. It was found that the differences in regional governance across these stages shaped the functional development and vision of metropolitan areas. The Nanjing metropolitan area is under a multilevel governance stage, representing developed regions, characterized by advanced cross-boundary cooperation and a well-established coordination system between the central city and surrounding cities and counties. In this model, multilevel governments and non-governmental organizations actively participate in cross-regional governance, with market integration playing a leading role in metropolitan development. This has resulted in multidimensional development, such as the cross-boundary development of infrastructure, industries, and ecological protection. The Chengdu metropolitan area remains in a hierarchical governance stage marked by uneven regional development between the central city and the surrounding cities and countries. Consequently, government-initiated projects, such as ecological protection and infrastructure development, have been implemented, but the lack of market actors has constrained the development of the industrial division of labor and cooperation. This region has yet to form a unified resource allocation platform, which limits the flow of resources and development factors across administrative boundaries. The Fuzhou metropolitan area is characterized by industrial collaboration initiatives through intercity cooperative zones, and its central city has a weak influence on the surrounding cities and counties. Support from the provincial government facilitated the establishment of cross-boundary cooperative parks; however, excessive reliance on administrative mechanisms hindered the emergence of market-driven mechanisms. The capacity for regional functional integration and cooperation was relatively weak compared to the Nanjing and Chengdu metropolitan areas. A comparative analysis of the three metropolitan areas reveals that more economically developed regions tend to focus on functional integration among different cities and counties. Meanwhile, regions with uneven economic development emphasize coordinated development and improve ad hoc cross-boundary development issues. The interaction of government and market actors leads to distinct forms of regional governance and impacts the realization of metropolitan area functions.

Technology transfer is an important way to promote technology sharing, optimize resource allocation, and improve the levels of innovation and overall efficiency. Existing research on regional technology transfer primarily focuses on eastern and developed regions of China, such as the Yangtze River Delta, Beijing-Tianjin-Hebei, Guangdong-Hong Kong-Macao, and the Pearl River Delta; therefore, inland regions are relatively underreported. The middle reaches of the Yangtze River are one of China's five national-level urban agglomerations. There is a gap between academic attention to its technology transfer system and the practice of regional development planning and construction. Against this backdrop, this study collected patent transfer information from 2010 to 2021 from the IncoPat patent service website and constructed intercity technology transfer networks in the middle reaches of the Yangtze River for four periods. Based on the application of network analysis methods and temporal exponential random graph models, the structural evolution and driving mechanism of intercity technology transfer in the middle reaches of the Yangtze River were quantitatively analyzed. The results showed that (1) Changsha and Wuhan were consistently at the core of regional technology transfer. After the release of the urban agglomeration development plan for the middle reaches of the Yangtze River, Nanchang emerged as a new growth pole. The leading roles of Wuhan and Changsha in this region were primarily supported by technology diffusion, whereas Nanchang's technology diffusion and absorption were relatively balanced. The three central cities organized three technology transfer communities through a hub network-shaped structure that was highly coupled with provincial boundaries, and the inter-provincial technology flows were weak. (2) The intercity technology transfer network in the middle reaches of the Yangtze River gradually evolved to be characterized by both a core-periphery hierarchy and small-world clusters. However, the polarization of the network weakened, whereas the clustering coefficient and transfer efficiency increased. Moreover, the technology transfer paths present a stable trend with slight changes, suggesting incremental innovation. (3) Intercity technology transfers are not only affected by innovation size, intercity spatial distance, and the provincial boundary effect, but also by the endogenous mechanism of network self-organization. The reciprocity, activity, popularity, and hierarchical transitivity of intercity technology transfers positively affect network development, and the stability effect is stronger than the innovation effect in the network evolution process. Based on these findings, policy suggestions for optimizing technology transfer paths are proposed from the perspectives of promoting inter-provincial technology flows, enhancing spatial spillover and sector integration, and taking advantage of the network self-organizing laws of preferential attachment and clustering development. This study contributes to the literature by applying network econometric models for panel data to the analysis of the influential mechanism of innovation networks and corresponding the statistical properties of networks at different scales to the variable specification of endogenous and exogenous driving factors. Empirical research has verified the applicability of this analytical framework and methods in innovation geography, which could also provide new findings from the endogenous micro-mechanisms of the network to better understand the processes of intercity technology transfer.

The population problem has always been an overall, long-term, and strategic issue facing China; the fertility rate can reflect the population problem, and the identification of the temporal and spatial evolution characteristics and driving factors of fertility rate is of great significance to the long-term balanced development of population and the coordination of human-land relationship. Based on the census data of 2000, 2010, and 2020, the Theil index, spatial autocorrelation analysis, and geographically weighted regression models were used to explore the spatiotemporal evolution characteristics and influencing factors of city fertility in China from 2000 to 2020. The results showed that: (1) Based on the perspective of time series characteristics, from 2000 to 2020, China's fertility rate presented a downward trend, the degree of distribution first increased and then decreased with the passage of time, the discrete trend between cities decreased, and the regional differences in fertility rate have narrowed. (2) Based on the perspective of spatial pattern, the fertility rate is high in the south and west and low in the north and east, whereas heterogeneity is obvious. Specifically, the west side of the Hu Line is higher than that of the east side, but the fertility rate fluctuation on the east side is higher than that on the west side. China's four major economic regions are in the order of Western > the Central> the Eastern > the Northeast, with fertility rates still declining in the Western and Northeast regions. Focusing on the five major urban agglomerations, the urban agglomeration in the middle reaches of the Yangtze River has the highest fertility rate, followed by the Chengdu-Chongqing urban agglomeration, the Beijing-Tianjin-Hebei urban agglomeration, and the Pearl River Delta urban agglomeration, with the Yangtze River Delta urban agglomeration having the lowest fertility rate. Overall, the H-H cluster agglomeration areas are mainly distributed in the southern and western regions of China, while the L-L cluster agglomeration areas are concentrated in the northern and eastern regions. (3) Based on the perspective of influencing factors, economic, policy, demographic, and social factors are always the key factors affecting fertility, with economic and policy factors generally having a greater impact on China's fertility rate. The spatial heterogeneity of economic factors represented by per capita GDP and urbanization rate is significant, the positive impact of policy factors in northern and eastern China is significant, the population quality and fertility rate in the west of the Hu Line are strongly negatively correlated, the population number and fertility rate in southeast China are positively correlated, the negative impact of marriage and childbearing on fertility on the east side of the Hu Line is greater than that on the west side, and the influence of the concept of raising children and preventing old age in some areas in the east is still greater.

Cities function as complex systems where subsystems interact to form higher-level urban complexes characterized by intricate nonlinear coupling relationships among various networks. Although a substantial amount of research on urban networks from the perspective of single-factor flow exists both domestically and internationally, such studies have limitations, as they do not fully capture the multifaceted nature of urban systems. Research on multi-city networks in China primarily examines the structural characteristics and dynamic mechanisms of networks with distinct attributes. While international studies have explored interactions and coupling effects among subsystems within complex systems, focusing on aspects like network robustness and cascading failures, relevant studies on urban networks remain relatively limited. This study proposes a comprehensive research framework called Correlation-Multiplex Coupling Networks-Coupling Linkage Effect Evaluation (CMC). Focusing on the coupling of enterprise and information networks in the Chengdu-Chongqing twin-city economic circle, this study further analyzes the coupling linkage effect between these networks. The results indicate that: First, there exists a complex nonlinear coupling relationship between information and enterprise networks, with a correlation coefficient exceeding 0.625 and different degrees of interactive coupling between nodes; second, from 2011 to 2020, there were notable differences in the core-edge structures of the three networks within the twin-city economic circle. Interactions between cities in core areas were more frequent than those in peripheral areas, displaying a prominent "rich man clubs" phenomenon and preferential links. The hierarchical structure and "Matthew effect" of the urban network were evident. The enterprise network evolved from a dual-core, single-strong link structure to a dual-core, multiple-strong-link structure, achieving a more balanced network over time. The information network transitioned from a single-centered structure around Chengdu to a weaker dual-core structure, with Chongqing as a secondary core. Third, from 2011 to 2020, differences in coupling and linkage effects between enterprises and information networks were significant, with node coupling and linkage primarily at medium to low levels. Link coupling and linkage were mainly at medium to high levels, and interactive linkage weakened over time. The "rich club" phenomenon in coupled networks was stronger than in information networks but weaker than in enterprise networks. Compared to enterprise networks, the "Matthew effect" of coupled networks was less pronounced. In 2020, due to COVID-19 impacts, coupling and linkage between enterprise networks and information networks were significantly weakened, and urban comprehensive capacity did not markedly improve. This study expands the research perspective on urban networks, enriching the field by using a multiplex network approach and coupling coordination model, providing a methodological reference for similar research in other regions and enhancing understanding of the linkage effects among urban subsystems.

Based on the analytical framework of geographical philosophy, this study investigated the production process at different stages, overall laws, ideological inspiration, and future issues of geographical knowledge production and practice in China. The main findings are as follows: First, philosophy is an important foundation supporting the production of geographical knowledge. The production of geographical knowledge should be seen as a process of content division and succession, in which new knowledge is gradually accumulated and there is movements towards wholeness. Second, in geographical knowledge production, geography reflects the actuality of knowledge through manifested features and reflects the reality of knowledge through unexpressed features. Geographical knowledge production exists dynamically in practice. Exploring the driving forces and processes of geographical knowledge production in practice can facilitate the comprehension of the existence and essence of geography. Only by coordinating stage differences in geography to achieve universal awareness can the effective function and ultimate pursuit of geographical philosophy be reflected. Third, in the future, China will inevitably enter a complex stage of development and practice, and "overlapping China" will require even more "overlapping geographical knowledge". Knowledge production and practice of geography require a comprehensive perspective that integrates wisdom from different temporal and spatial dimensions, establishment of clear philosophical ontology, epistemology, and methodology based on the changes and demands of the times, actively promoting the localization of geographical philosophy system construction to serve national strategic needs and high-quality socioeconomic development more effectively.

Given the real-world challenges in implementing the United Nations Sustainable Development Goals (SDGs), it is important to study and formulate a localized assessment indicator system for each SDGs to monitor the current status of sustainable development at different scales, identify problems, and develop countermeasures. Based on the "economy-society-environment" three-dimensional theoretical framework for sustainable development, this study deconstructs the connotation of SDG11 at the community level, and constructs an urban community sustainability assessment indicator system containing 7 goals and 13 indexes. In addition, by taking 602 sample communities in the built-up regions of Changsha as an example, this study utilizes multi-source big data to comprehensively assess community sustainability as well as the coupling coordination degree of the communities' economic-social-environmental systems. It is found that: (1) During the period 2010-2020, the degree of achievement of community SDG in Changsha falls in the "relative closeness" range, with a "core-periphery" spatial distribution from the high sections to the low ones. (2) Of the 7 goals, housing guarantee, disaster prevention and relief, and environmental governance are progressing well; public transportation and heritage protection are improving significantly; public space is rising slowly; however, planning management is less than ideal. (3) Based on the assessment results of the coupling coordination degree of the communities' economic-social-environmental systems, the sample communities are classified into three types: coordinated development, transitional development, and dysfunctional decline communities. Then, in addition to the zoning results of core, central urban, and suburban areas, a differentiated governance path is proposed. (4) The assessment indicator system has high validity and needs to be further enhanced with a larger number of empirical cases in the future. The research results enrich the theoretical system of community sustainability and technical means of assessment. The empirical part of the study takes the statutory communities in the built-up area of Changsha as the research object and carries out the assessment of community sustainability at three time points: 2010, 2015, and 2020. This help in grasping the temporal and spatial heterogeneity of community sustainability and its law of evolution at the city level and provide scientific support for carrying out refined urban planning and community governance. The data used in the indicator system mainly come from objective big data with temporal continuity, which is conducive for conducting longitudinal continuous tracking research and horizontal comparison research with other cities.

Urban Blue-Green Spaces (UBGS) are material carriers that support public life and expand social interactions. It is also a natural place to realize the spatial publicness. In the context of the ecological civilization, China has made specific achievements in constructing a UBGS. However, optimizing its spatial structure and improving the quality of the human environment is only the beginning. Enhancing its publicness and thus strengthening social cohesion, enriching cultural diversity, cultivating the public spirit, and realizing the well-being of humankind on a broader scale is the ultimate goal of UBGS. Drawing on the theories of the human-land relationship and landscape ecology, we established an evaluation system for UBGS publicness based on the "element-function-structure" framework. We used Changsha as an example to explore the UBGS publicness pattern characteristics and influencing factors. The study results are as follows: 1) A UBGS with high publicness should have three significant characteristics: accessible elements, selectable functions, and shared structures, which promote and expand public life and support other social connections. 2) The comprehensive indicator of UBGS publicness in Changsha showed a circular pattern, decreasing from the core to the periphery and a fan-shaped expansion relying on the water system. Regarding element accessibility, spatial accessibility was high in the core area and low in the suburbs. In contrast, quantity adequacy was low in the core area and high in the suburbs. In terms of functional selectivity, group inclusiveness was low along the Xiangjiang River in the core and center areas and lower on the east bank than on the west bank, whereas functional diversity was high in the core area and low in the suburban areas. In terms of structural connectivity and shareability, interactive connectivity shows a high core area, a low peri-urban area, and a wedge-shaped interlocking circle pattern in the transition zone between the core area and the peri-urban area, accompanied by a high belt characteristic along the scenic belt; the landscape connectivity shows a low core area, a high peri-urban area, and a pattern characteristic of the west bank of the Xiangjiang River that is higher than that of the east bank. 3) Social demand, economic boosts, and environmental support promote the spatial heterogeneity of the UBGS publicness. Based on the research results, improving the publicness of the UBGS in Changsha can be approached from the following aspects: first, increasing funding and policy support for the construction of the UBGS, expanding its scale, and improving its quality. Second, respecting the spatial distribution characteristics and activity patterns of the public and optimize the functional organization of the UBGS and the surrounding environment. Third, when constructing urban ecosystems, road systems, greenway systems, and public service facility systems, the construction of the UBGS should be considered comprehensively, and the coupling relationship between the UBGS and other urban subsystems should be enhanced. This study constructed a theoretical framework and evaluation system for assessing UBGS publicness and evaluated UBGS publicness on an urban scale. The results of this evaluation will promote the construction of livable cities and the implementation of the concept of sustainable urban development.

Hypothermia is a type of safety accident that is often neglected in field activities. Its occurrence is not only a medical problem but also a thermodynamic problem and involves a specific geographical environment. An effective way to improve public awareness of hypothermia risk is to analyze hypothermia accidents from the perspective of heat transfer and heat balance between the human body and the environment. However, few reports have been written on relevant research. Therefore, this study uses the heat balance theory to build a calculation model of the clothing thermal resistance required by the human body to maintain a normal body temperature. The two most serious hypothermia death events in Shilin, Yellow River, Baiyin, Gansu province, and Ailao Mountain, Yunnan province, in 2021 are used as cases for analysis. The theoretical clothing thermal resistance has been calculated according to the external ambient temperature and human activity conditions (including metabolic rate and consumption coefficient) at the time of the event. By comparing the actual clothing thermal resistance value of the human body with the model, the theoretical clothing thermal resistance value has been calculated to study the hypothermia risk of the human body in the incident environment. The results show that, in the death incident of the Shilin Marathon on the Yellow River in Gansu Province, the theoretical thermal resistance of clothing required by the human body to maintain a normal body temperature was between 0.72 and 4.45 clo under different temperature conditions (resting, walking, and long-distance running), while the actual thermal resistance of the clothing worn by the accident personnel was 0.32clo. The theoretical thermal resistance of the clothing is higher than that of the actual clothing, resulting in a high risk of temperature loss. Regarding the death event in the Ailao Mountain geological survey, the theoretical clothing thermal resistances required for the human body to maintain a normal body temperature under different temperatures while camping (sleeping), conducting field work, and mountaineering were 2.70-6.52 clo, 1.06-2.27 clo, and 0.55-1.75 clo, respectively. The actual thermal resistance of the clothing worn by the accident personnel was 1.86clo. During the accident, as long as the human body was in a climbing or working state, the difference between the theoretical and actual clothing thermal resistance was small, and the risk of hypothermia was low. However, while camping (sleeping), the theoretical clothing thermal resistance was higher than the actual clothing thermal resistance, and the lower the temperature, the greater the difference—especially at night when the temperature drops to its lowest point. At that point, the theoretical clothing thermal resistance could have been more than 3.5 times higher than the actual clothing thermal resistance, posing a serious risk of hypothermia. The results show the inevitability of hypothermia deaths in Shilin of the Yellow River in Gansu Province and Ailao Mountain in Yunnan Province. The insufficient prediction of hypothermia risk was the main cause of the hypothermia accidents. The calculation model constructed in this study can predict and evaluate the hypothermic risk of a certain outdoor activity in the future, provide a theoretical basis and research paradigm of thermodynamics and environmental science for improving public awareness about hypothermic risk, and is an effective means to prevent hypothermic accidents. Some measures and suggestions are provided for geographers engaged in long-term field investigation to avoid field hypothermia.

In the context of climate change, the escalating frequency of extreme weather phenomena has exacerbated the severity of compound floods in the southeastern coastal regions of China. Rising sea levels significantly contribute to the inundation of low-lying coastal urban areas. The quantitative assessment of compound flood risk offers scientific support for disaster prevention and reduction in coastal cities and for coastal management initiatives. Using Haikou City as a case study, the daily precipitation and maximum storm surge tide data from 66 typhoons that affected Haikou between 1960 and 2017 were utilized to construct compound flood combination scenarios. Based on the quantitative method of D-Flow FM (Delft3D-FLOW Flexible Mesh) numerical simulation, the potential risks of extreme rainfall and storm surge compound flood disasters under sea level rise scenarios were thoroughly investigated by integrating various scenarios. The findings revealed the following: 1) Storm surge was the primary factor contributing to compound flooding during typhoons, with the estuary of the Nandu River and the northern coast being the most affected. 2) In the scenario of maximum rainfall and storm surge combination, the inundation area of Haikou is about 148 km², which is approximately 15 times larger than the minimum rainfall and storm surge combination scenario. Moreover, in more than half of the inundated areas, the water depth exceeds 1 meter. 3) Under extreme rainfall and storm surge compound scenarios, the areas encompassing Haidian Island, Xinbu Island, and Jiangdong New Area were significantly affected by sea level rise. By 2100, the total flooding area is projected to reach about 203 km² under the RCP8.5 scenario. Sea level rise significantly amplifies urban flood risks, implying that coastal cities are poised to encounter heightened threats and manage future challenges. Through comprehensive comparisons of multiple rainfall and storm surge compound flooding scenarios under sea level rise, the temporal and spatial characteristics of the compound flooding risk were systematically evaluated. The results provide an important scientific basis for sustainable regional development, effective management, and prevention.

Typhoons are extreme weather phenomena that seriously affect the daily lives of residents and regular functioning of society. As one of the most typhoon-prone countries in the world, China is constantly affected by typhoons and their secondary disasters, which can cause significant casualties and economic losses. The extent of damage caused by typhoons is inversely proportional to the effectiveness of the emergency response. Therefore, accurate and comprehensive access to damage information is critical for rescue and recovery. Social media, which is characterized by low collection costs and rich content, is an important means of collecting disaster information. With the development of social media, it has become increasingly important to accurately and comprehensively identify social media texts related to typhoons. In this study, by combining typhoon attribute data and a multi-label classification method with Bidirectional Encoder Representations from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) models, a typhoon damage identification method based on Weibo texts and deep learning is proposed to identify the damage caused by severe and super typhoons that made landfall in Guangdong Province from 2010 to 2019. First, texts related to typhoon damage were identified from the massive Weibo texts and further classified into five damage categories: transportation, public, electricity, forestry, and waterlogging. The typhoon damage characteristics were comparatively analyzed using spatial distribution, time curves, and quantity curves. The results showed that the accuracy of typhoon damage classification was high, with an F1 score of 0.907 for identifying typhoon damage-related texts and 0.814 for further classifying them into five damage categories. Typhoon attribute data and multi-label classification methods have improved the accuracy and comprehensiveness of typhoon damage identification. Compared to the use of Weibo texts only and the single-label classification method, typhoon attribute data provide information on the geographic context of the typhoon at the time of the texts' release, and the multi-label classification method allows the texts to belong to more than one damage category. This study shows that there are differences in the proportion of damage caused by different typhoons, which are related to the intensity and track of the typhoon, as well as the development level of the affected areas. In addition, before the typhoon makes landfall, precautions lead to transportation and public-related damage. After the typhoon makes landfall, the typhoon damage shows single and double-peak characteristics, and the different characteristics reflect the changing trends and features of typhoon damage. This study provides a scientific basis for typhoon damage identification and disaster relief in Guangdong Province.

China has numerous islands and reefs with complex terrain that are heavily impacted by tropical cyclone disasters. High-resolution tropical cyclone wind-field simulations are beneficial for representing the spatial variations in wind speeds. It is important to conduct high-resolution simulations on relatively small islands and reef areas. To explore the differences in tropical cyclone wind field simulations at various spatial resolutions in the island and reef areas of China, this study compared the modeled wind fields of historical tropical cyclones in China's island and reef areas, which have complex terrains, including plains, peaks, valleys, and cliffs, at three spatial resolutions of 1 km, 90 m, and 30 m. The wind fields were modeled using land cover and elevation data of the three spatial resolutions as inputs and validated against observed winds at eight stations. Comparisons were made regarding the differences in wind speeds of tropical cyclones with a 100-year return period at three spatial resolutions. The results showed that: (1) the 30 m resolution achieves the best accuracy, with a root mean square error of 4.28 m/s, lower than those of 90 m and 1 km by 0.08 m/s and 1.04 m/s, respectively. (2) Different spatial resolution simulations showed that wind speed errors were related to terrain types. For example, on Zhujiajian Island, located in Zhoushan City, the 30 m resolution captured the spatial heterogeneity of winds better than the other resolutions, especially for mountainous, valley, and cliff terrains. Comparisons between the simulated wind speeds at 90 m and 1 km resolutions versus those at 30 m resolution indicate that the differences in the simulation percentages are as follows: 10.06% and 12.90% for peak terrain, 19.91% and 10.44% for valley terrain, and 18.57% and 19.01% for cliff terrain, respectively. Additionally, the 30 m simulation was more sensitive to transitions between windward and leeward slope terrains. (3) For the 100-year return-period wind speeds, the 30 m resolution produced the highest values and largest spatial variations. On Zhujiajian Island, the maximum wind speeds at 1 km, 90 m, and 30 m resolutions were 71.13, 73.18, and 79.97 m/s, respectively, and standard deviations of 3.88, 3.72, and 7.18 m/s. This study demonstrates the importance of using high-resolution data to simulate tropical cyclone winds in complex terrain. However, this study had some limitations. First, the terrain correction factors need to be optimized further. The assessment method provided by the building codes tended to overestimate the impact of the terrain correction factors. In the future, more accurate terrain correction factors could be obtained using computational fluid dynamics and wind tunnel tests. Second, because of the limited types of land cover data used in the calculations, the subdivision of certain land types when calculating the surface roughness is not sufficiently detailed. Additionally, different years of land cover data were not incorporated, making it challenging to reflect the variations in surface roughness. Remote sensing can be used in the future to determine the high-resolution spatial distributions of surface roughness.

China is frequently affected by tropical cyclones, which can lead to severe economic losses. Rapid disaster loss assessment is crucial for effective emergency response. A variety of factors affect tropical cyclone disaster losses, which can be roughly categorized into hazard, exposure, and vulnerability. In the past, traditional statistical methods were used as the main tools for disaster loss assessment. To explore the potential of machine learning models, we explored five algorithms: the Light Gradient Boosting Machine (LightGBM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Back-Propagation Neural Network (BP). The maximum gust wind and rainfall of tropical cyclones were selected to represent hazards, fixed capital stock data were used for the valuation of exposure, and the GDP of each county was collected to reflect capacity or vulnerability. In addition, river network density data were used as a simple proxy to demonstrate the contribution of flood-induced tropical cyclone rainfall. The relationship between these input variables and disaster loss at the county level was developed based on the data of 81 tropical cyclone events from 2009 to 2020 in Fujian Province. The performance of these models was compared using accuracy, precision, recall, and F1 scores. The accuracies of the LightGBM, RF, XGBoost, SVM, and BP models were 0.7946, 0.7726, 0.7628, 0.2518, and 0.2681, respectively. The main findings are as follows: (1) The performance of the ensemble learning algorithms (RF, XGBoost, and LightGBM) was higher than that of the individual classifiers (BP and SVM). The LightGBM model exhibited the best performance, with accuracy, precision, recall, and F1 scores >79%. (2) Maximum hourly rainfall and maximum wind gust are two of the most important loss-inducing factors, and fixed capital stock is a better proxy for disaster exposure than GDP. (3) The modeled losses are consistent with the actual losses under different but typical tropical cyclone events, indicating that the models can be applied to future tropical cyclone events impacting Fujian Province. However, this study had some limitations. First, some natural hazards, such as floods, storm surges, and waves, were not fully considered, which introduced uncertainty into the model results. Second, the emergency response capacity and actual actions taken among counties may have varied dramatically and were neglected due to data unavailability. In the future, hazard and vulnerability variables should be obtained to extend the model inputs. In addition, whether the model parameters trained with data from Fujian Province can be applied to other provinces remains unaddressed. In the future, to develop an operational model for the whole of coastal China, county-level data of all typhoon-prone areas in China with long-term time series are needed.

Islands are sensitive zones of sea-land interaction and typical ecologically fragile areas that are highly vulnerable to natural disasters, especially marine aquaculture, which is sensitive and at high risk to typhoon disasters; additionally, they are home to aquaculture households with high economic vulnerability to typhoons and poor adaptive capacity. This study focused on Liuheng Town of Zhoushan and the Dongtou District of Wenzhou, which were severely affected by Super Typhoon Lekima, and Gouqi Town of Zhoushan, which was severely affected by Typhoon In-Fa and Super Typhoon Chanthu, as case areas. Based on data acquired from 344 questionnaire surveys of aquaculture households and interview data from various related bodies, this study used factor analysis of mixed data and hierarchical clustering on principal components to identify the types of vulnerability of island aquaculture households to typhoon disasters and reveal the characteristics of each vulnerability type, as well as to identify the discriminative indicators of household vulnerability types, for analyzing the impact of typhoon disasters and other stressors on the vulnerability of island aquaculture households to typhoons. The results showed that the aquaculture industry and aquaculture households in the island areas showed high economic vulnerability, with most shrimp, crab, and shellfish mixed farming, algae, and mussel farming households suffering serious losses from typhoons. Second, differences in exposure, sensitivity, and adaptive capacity led to three different types and characteristics of vulnerability in aquaculture households. The degree of household exposure varied across aquaculture species, with mussels having the highest, algae the next highest, and shrimp, crab, and shellfish the lowest. Island aquaculture households showed outstanding sensitivity, as reflected in their high dependence on aquaculture, significant household human capital problems, relatively limited support from social networks, and frequent exposure to typhoon disasters. The adaptive capacity of households varied across aquaculture species, with mussel households having superior adaptive capacity, and shrimp, crab, and shellfish households and algal aquaculture households having relatively poor adaptive capacity. Third, the common influencing factors of aquaculture households' vulnerability to typhoon disasters are labor shortages, frequent typhoon disasters, and inadequate infrastructure. The differences among the significant discriminant indicators, such as the degree of exposure, aquaculture species, average annual household income, age and education level of the household head, social support, number and type of adaptation strategies adopted, and cost–benefit situation, are key to the formation of different vulnerability types. Finally, multiple stressors from the climate, ecosystem, economy and markets, society, institutions, and policies mutually interact to exert cumulative effects that increase the vulnerability of fishery ecosystems and the socioeconomic vulnerability of households in island regions. This study provides important empirical evidence for governments, aquaculture households, and other relevant stakeholders in island regions to reduce their vulnerability and increase their adaptive capacity.

Islands are sensitive zones of sea-land interaction and typical ecologically fragile areas that are highly vulnerable to natural disasters, especially marine aquaculture, which is sensitive and at high risk to typhoon disasters; additionally, they are home to aquaculture households with high economic vulnerability to typhoons and poor adaptive capacity. This study focused on Liuheng Town of Zhoushan and the Dongtou District of Wenzhou, which were severely affected by Super Typhoon Lekima, and Gouqi Town of Zhoushan, which was severely affected by Typhoon In-Fa and Super Typhoon Chanthu, as case areas. Based on data acquired from 344 questionnaire surveys of aquaculture households and interview data from various related bodies, this study used factor analysis of mixed data and hierarchical clustering on principal components to identify the types of vulnerability of island aquaculture households to typhoon disasters and reveal the characteristics of each vulnerability type, as well as to identify the discriminative indicators of household vulnerability types, for analyzing the impact of typhoon disasters and other stressors on the vulnerability of island aquaculture households to typhoons. The results showed that the aquaculture industry and aquaculture households in the island areas showed high economic vulnerability, with most shrimp, crab, and shellfish mixed farming, algae, and mussel farming households suffering serious losses from typhoons. Second, differences in exposure, sensitivity, and adaptive capacity led to three different types and characteristics of vulnerability in aquaculture households. The degree of household exposure varied across aquaculture species, with mussels having the highest, algae the next highest, and shrimp, crab, and shellfish the lowest. Island aquaculture households showed outstanding sensitivity, as reflected in their high dependence on aquaculture, significant household human capital problems, relatively limited support from social networks, and frequent exposure to typhoon disasters. The adaptive capacity of households varied across aquaculture species, with mussel households having superior adaptive capacity, and shrimp, crab, and shellfish households and algal aquaculture households having relatively poor adaptive capacity. Third, the common influencing factors of aquaculture households' vulnerability to typhoon disasters are labor shortages, frequent typhoon disasters, and inadequate infrastructure. The differences among the significant discriminant indicators, such as the degree of exposure, aquaculture species, average annual household income, age and education level of the household head, social support, number and type of adaptation strategies adopted, and cost–benefit situation, are key to the formation of different vulnerability types. Finally, multiple stressors from the climate, ecosystem, economy and markets, society, institutions, and policies mutually interact to exert cumulative effects that increase the vulnerability of fishery ecosystems and the socioeconomic vulnerability of households in island regions. This study provides important empirical evidence for governments, aquaculture households, and other relevant stakeholders in island regions to reduce their vulnerability and increase their adaptive capacity.

The dynamic risk assessment of typhoon disasters is an important decision-making basis for disaster response in the event of a major typhoon. Its goal is to dynamically predict the expected loss and disaster risk level caused by a typhoon so as to provide a basis for disaster risk early warning and emergency response. The traditional risk assessment model mainly fits the vulnerability curves of the hazard-affected bodies using historical disaster losses, and then establishes a disaster risk assessment model by coupling the risk of disaster factors, exposure, and vulnerability. However, the vulnerability curves generated by this method have problems of regional applicability, particularly in small-scale regions with small sample sizes available for fitting, leading to insufficient generalizability of the model. In addition, such models are complex and require phased hazard and vulnerability of the hazard-affected bodies research. Moreover, when employing the 3-element coupling process, it is difficult to consider other risk factors in the disaster system, such as hazard-formative environment and disaster prevention and mitigation capability. With the development of information technology, the availability of disaster risk factor data has been significantly improved, affording conditions for the fusion and application of disaster risk multi-source data. In recent years, many data-driven machine-learning models have been used to establish disaster risk assessment models. These models have the advantage that they can use large sample to improve the adaptability of the model, whereby the modeling process can consider more risk factors, the concepts of hazard and vulnerability are diluted, and the steps of model building are simplified. The integrated learning algorithm can not only improve the prediction accuracy, but more importantly, can be used to effectively evaluate the contribution value of the index to the final evaluation result. At present, China has established a six-level disaster reporting system at the national, provincial, municipal, county, township, and village levels, forming a long-term, high-precision database of disaster event cases since 2009, providing rich disaster loss information for the data fusion of risk elements. This study was based on 108 typhoon cases affecting five provinces in southeast China during 2009-2022. Nearly 4 000 county-level typhoon disaster loss samples were used to establish a dynamic typhoon risk assessment sample database that integrates 30 types of multi-source risk factor indicators. Six typhoon disaster risk assessment models were developed using the random forest algorithm to evaluate the affected population, emergency relocation population, crop-affected areas, collapsed and severely damaged houses, direct economic losses, and comprehensive risk level. Through the verification of actual disaster situations and model results, the overall accuracy of the disaster risk assessment results was found to be greater than 80%, indicating that the model has good generalizability and can be used for actual disaster assessment work. The experimental comparison shows that increasing the training sample size by 1-2 orders of magnitude can improve the accuracy of the model assessment by 3%-14%, indicating that the accumulation of disaster risk big data is of great significance in the study of disaster risk assessment. This study is expected to constitute a scientific reference for the quantitative analysis of the multiple impact factors of typhoon disaster damage and explore technical ideas for the application of disaster big data in risk management.

China has numerous islands and reefs with complex terrain that are heavily impacted by tropical cyclone disasters. High-resolution tropical cyclone wind-field simulations are beneficial for representing the spatial variations in wind speeds. It is important to conduct high-resolution simulations on relatively small islands and reef areas. To explore the differences in tropical cyclone wind field simulations at various spatial resolutions in the island and reef areas of China, this study compared the modeled wind fields of historical tropical cyclones in China's island and reef areas, which have complex terrains, including plains, peaks, valleys, and cliffs, at three spatial resolutions of 1 km, 90 m, and 30 m. The wind fields were modeled using land cover and elevation data of the three spatial resolutions as inputs and validated against observed winds at eight stations. Comparisons were made regarding the differences in wind speeds of tropical cyclones with a 100-year return period at three spatial resolutions. The results showed that: (1) the 30 m resolution achieves the best accuracy, with a root mean square error of 4.28 m/s, lower than those of 90 m and 1 km by 0.08 m/s and 1.04 m/s, respectively. (2) Different spatial resolution simulations showed that wind speed errors were related to terrain types. For example, on Zhujiajian Island, located in Zhoushan City, the 30 m resolution captured the spatial heterogeneity of winds better than the other resolutions, especially for mountainous, valley, and cliff terrains. Comparisons between the simulated wind speeds at 90 m and 1 km resolutions versus those at 30 m resolution indicate that the differences in the simulation percentages are as follows: 10.06% and 12.90% for peak terrain, 19.91% and 10.44% for valley terrain, and 18.57% and 19.01% for cliff terrain, respectively. Additionally, the 30 m simulation was more sensitive to transitions between windward and leeward slope terrains. (3) For the 100-year return-period wind speeds, the 30 m resolution produced the highest values and largest spatial variations. On Zhujiajian Island, the maximum wind speeds at 1 km, 90 m, and 30 m resolutions were 71.13, 73.18, and 79.97 m/s, respectively, and standard deviations of 3.88, 3.72, and 7.18 m/s. This study demonstrates the importance of using high-resolution data to simulate tropical cyclone winds in complex terrain. However, this study had some limitations. First, the terrain correction factors need to be optimized further. The assessment method provided by the building codes tended to overestimate the impact of the terrain correction factors. In the future, more accurate terrain correction factors could be obtained using computational fluid dynamics and wind tunnel tests. Second, because of the limited types of land cover data used in the calculations, the subdivision of certain land types when calculating the surface roughness is not sufficiently detailed. Additionally, different years of land cover data were not incorporated, making it challenging to reflect the variations in surface roughness. Remote sensing can be used in the future to determine the high-resolution spatial distributions of surface roughness.

Myanmar is a key neighbor for China and an important link in advancing the "Belt and Road" initiative, contributing to both domestic and international economic flows. Despite the border closures and restrictions imposed during the COVID-19 pandemic, the New China-Myanmar Indian Ocean Corridor has seen substantial progress. However, this development has not garnered the attention it deserves, as both national and Yunnan provincial governments continue to prioritize the China-Myanmar Economic Corridor (CMEC). This oversight results from an incomplete understanding of the changes in Myanmar's geopolitical landscape since 2000. Using a framework for national geopolitical landscape analysis, this study examines Myanmar's basic national conditions, principal relationships, and inherent contradictions, revealing how Myanmar's geopolitical landscape has evolved due to the interplay of internal and external factors, cross-field interactions, and strategic games played by multiple geopolitical actors. Specifically, the study discusses the period from 2000 to 2010, characterized by external pressure and internal stability, and the years from 2011 to 2021, marked by external conflict and internal turmoil. The evolving geopolitical landscape in Myanmar has created favorable conditions for building the New China-Myanmar Indian Ocean Corridor. From a geopolitical perspective, this paper explores the reasons behind the necessity of this new corridor and suggests a re-evaluation of China's spatial planning for major infrastructure projects in Myanmar given the country's shifting geopolitical context. The corridor's feasibility—whether measured by distance, time, costs, spatial distribution of domestic ethnic armed conflicts, or Myanmar's post-pandemic economic trends—suggests it is highly workable. In the short term, the new corridor can complement the China-Myanmar Economic Corridor, progressing concurrently; in the long term, it could gradually replace it as the main route for China-Myanmar trade. This study not only enhances understanding of the New China-Myanmar Indian Ocean Corridor but also provides a scientific rationale for its vigorous promotion.

The rapid growth of social media has introduced new concepts and technical approaches for disaster management. This paper reviews the characteristics of social media data and its application potential in disaster management research, providing a new research perspective for the field of disaster management. Taking the impact of Typhoon Doksuri in Fujian Province in 2023 as a case study, this research employs Latent Dirichlet Allocation (LDA) topic modeling to analyze the practical application effectiveness of social media data at different stages of disaster management from three perspectives: the spatiotemporal distribution of posts, trend analysis of different types of entities, and evolution of topic content. These findings indicate that the synchronous relationship between the popularity of related topics on Weibo and the impact of a disaster event confirms the effective application of social media data in disaster management. By monitoring the dynamics of information dissemination on social media, we can determine the occurrence status and impact scope of disasters in real time. During disasters, different user types have different foci. Individual users tend to focus more on the restoration of living facilities and the supply of relief materials, whereas organizational users concentrate on disseminating information about disasters and emergency response measures. The information provided by different types of users can provide a more comprehensive and diversified perspective on disaster perceptions for disaster management. Analysis of the evolution of topic content can reflect the evolution of emergency response dynamics and public attention needs in different cities at different stages of disaster management, thereby developing more practical emergency response strategies. Through the mining and analysis of social media data, this study recognizes the entire process of disaster occurrence from the perspective of social media data, thereby enriching the relevant theoretical and empirical research. Future research could be conducted from perspectives such as utilizing other multisource data, integrating machine learning and deep learning technologies to enhance the accuracy of topic information extraction, and exploring the application of social media data to post-disaster emergency rescue and infrastructure support.

Catastrophe insurance is an important financial tool to mitigate the risk of catastrophes. After the 2008 Wenchuan Earthquake, China accelerated its exploration of a catastrophe insurance system. As one of the most natural disaster-prone provinces in China, Guangdong experiences frequent rainstorms and typhoons. Severe natural disasters have not only led to significant losses to economic development and people's lives, but have placed considerable financial pressure on governments at all levels. To promote the transformation of government functions and use of catastrophe insurance as a modern financial tool to cope with major natural disasters, Guangdong has conducted pilot work since 2016 to explore and experiment with different aspects of catastrophe index insurance. This includes the design and application of insurance systems and products. The pilot work achieved remarkable results and formed the Guangdong catastrophe index insurance paradigm. However, few studies have examined the development and application of catastrophe index insurance programs in Guangdong Province. This paper describes the research and design process, data, and key methods of typhoon catastrophe index insurance in Guangdong, in accordance with the specific catastrophe index insurance practices. Furthermore, the application of the current catastrophe index insurance program from 2016 to 2023 is reviewed. Additionally, the advantages, characteristics, and shortcomings of the program are systematically analyzed, and potential directions for improvement in the future are discussed. Several notable conclusions were drawn from this study. First, the typhoon catastrophe index insurance, which is based on the circular catastrophe box and uses typhoon intensity levels as a stratification criterion for the payout structure, offers a straightforward methodology, easy recalculations, readily accessible data, and transparent results. Second, this form of insurance facilitates rapid claim settlements, incurs low operational costs, and effectively mitigates moral hazard. Third, the existing typhoon catastrophe index insurance program may encounter high basis risk and underestimate the severity of typhoon hazards, particularly in the context of climate change and the situation wherein a single typhoon impacts multiple municipalities. Finally, improvements to the current typhoon catastrophe index insurance program in Guangdong could be achieved by more deeply and comprehensively analyzing the spatial and temporal patterns of typhoon events, incorporating additional parameters with clear physical meanings, and refining the probability distributions of typhoon disaster events. The insights outlined in this paper may potentially enhance understanding among scholars and practitioners of typhoon catastrophe index insurance programs and provide guidance for extending catastrophe insurance in other typhoon-prone areas.

A brief review of the development of ethnogeography over the past century and geography-oriented theories of minzu over the past 30 years shows that ethnogeography, which is a prominent subdiscipline of geography in the first half of the 20th century, is being eroded to an "important but not conspicuous" field in China. Geography-oriented theories of minzu highlight the significance of "geography" to the development, integration and identification of minzu, whereas the understanding of "geography" is complicated and diverse, and a direction for establishing ethnogeographical theory has not been proposed. Meanwhile, narrow ethnogeography as an independent research field or subdiscipline is devoid of a systematic theoretical system. Considering both modern and contemporary geographical perspectives as well as geography-oriented theories of minzu, three accessible approaches that can strengthen the integrity of ethnogeography and promote the integration of geographical disciplines are proposed. First, the theoretical system of broad ethnogeography could be integrated through a "state-region-place" framework. Second, the multidimensional interpretations of minzu could be bridged with disciplinary traditions of natural science, social science, and humanities to form a threefold "nature-society-humanities" interpretation system. Finally, geographical theories of minzu that emphasizes connection, mobility, and transformation could be developed from the perspective of geography as a discipline rather than a subject. The integrity of ethnogeography will be demonstrated through bridging the gaps among theories, interpretations, and knowledge, and the influence of geography will be extended. More importantly, minzu and nations are understood, not interpreted, geographically.

Owing to historical reasons, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) features a unique "one country, two systems" institutional framework. Facilitating the integration and connectivity of transportation among Hong Kong, Macao, and the Mainland is crucial for the high-quality development of the GBA. Previous studies about borders have primarily focused on national (supranational) or administrative boundaries within a country's territory. However, studies on the unique institutional differences in the GBA are insufficient. Additionally, most studies do not perform dynamic border effects measurements using big traffic flow data. This study utilizes toll-collection data from highways in the GBA for 2021 and 2023, as well as cross-border traffic data, to construct a traffic-flow network for the GBA. Complex network analysis and border-effect measurement methods are employed to investigate the spatial structure of the GBA traffic-flow network and its dynamic changes in border effects. The results indicate that, in terms of the overall spatial structure of traffic flow in the GBA, the network exhibits a unique "dual-core edge" structure, with the Guangzhou-Foshan, and Shenzhen-Dongguan-Huizhou regions serving as dual cores. In contrast, the overall coverage and connectivity strength of the passenger-flow network are higher than those of the freight-flow network. Regarding the dynamic changes in the spatial structure of traffic flow from Hong Kong and Macao, the coverage and density of the traffic-flow network in 2023 are significantly higher than those in 2021. Traffic flows from Hong Kong and Macao have begun to extend beyond the border toward the northern regions, thus accelerating the integration of transportation within the GBA and forming a spatial pattern of "cross-strait connectivity and all-area interconnection." However, because of their peripheral positions in the traffic network and the presence of border effects, the importance of Hong Kong and Macao in the GBA traffic-flow network remains relatively weak. Based on the dynamic measurement results of border effects, the obstruction coefficients between Hong Kong and the Mainland, as well as between Macao and the Mainland, are significantly higher than those between various counties within the Mainland. The obstruction coefficients for passenger vehicles are generally lower than those for freight vehicles. Following the outbreak of the pandemic, the obstruction coefficients of the GBA traffic-flow network have increased dynamically, thus indicating a reduction in obstructive border effects. This study expands the quantitative research framework of border effects in traffic-flow networks, thus promoting integrated transportation development in the GBA and facilitating its integration development goals.

Under the influence of information technology and high-speed transportation networks, which compress space and time, the region's population has achieved large-scale fluidity. Examining the temporal heterogeneity of intercity travel networks and its influencing mechanism can help optimize regional spatial organization and provide a scientific basis for regional integrated development. Based on Baidu migration data from January to April 2023, this study uses a PPML(Poisson Pseudo Maximum Likelihood) gravity model and interaction term testing to compare the scale, pattern, and influencing factors of intercity travel networks during weekdays, weekends, and holidays in the Yangtze River Delta region. The results indicate the following: 1) The intercity travel network in the Yangtze River Delta region exhibits temporal heterogeneity characteristics. During weekdays, intercity travel primarily consists of cross-city commuting and business trips, with the lowest daily average scale. This forms a V-shaped intercity travel structure covering Shanghai, southern Jiangsu, Northern Zhejiang, and Southern Anhui. The positive effects of destination city population size and economic status on intercity travel are enhanced. On weekends, intercity travel is dominated by business trips and leisure activities, and residents tend to take shorter trips, which means that intercity distances pose greater hindrances to intercity travel. During holidays, intercity travel is primarily for leisure and entertainment and for visiting friends and relatives, with the highest daily intensity. The promotional effect of destination city population size on intercity travel is weakened, and intercity travel is less hindered by intercity distances. Compared to the effects of geographical distance, economic status, and population size on the scale of intercity travel during weekdays, travel duration, or geographical distance, tends to pose a greater hindrance on weekends and a lesser hindrance during holidays. The promotional effect of economic status is intensified on weekends but diminishes during holidays. Meanwhile, the promotional effect of population size weakens both on weekends and during holidays.2) Push–pull factors encompass the level of urban development and the incentives that trigger individual travel. In terms of urban development level, indicators such as population size, economic status, and industrial structure reflect the comprehensive strength and development status of a city, influencing its ability to serve as both a starting and destination point for intercity travel. From the perspective of various individual travel incentives, residents pay more attention to various urban resources such as income levels, public service quality, and tourism resources to meet their personal needs for production and living. The primary types of population movements vary across different time periods, shifting between cross-city commuting, business travel, and leisure and entertainment. As a result, the dominant factors among push-pull elements also change, leading to significant variations in the effectiveness of each factor. Intermediate obstacles are the key factors limiting intercity travel. On the one hand, while the level of integration in the Yangtze River Delta region continues to improve, and transportation facilities are gradually improving, geographical distance remains a crucial intermediate obstacle. On the other hand, administrative and cultural differences between different provinces increase residents' adaptation costs, forming "invisible barriers" that hinder cross-province population interactions. The hindrance posed by intermediate obstacles to intercity travel also varies across different travel periods. The effects of push-pull factors exhibit temporal heterogeneity. The small-world characteristics of the intercity travel network during weekdays are more evident, and the central city has a more prominent structural core status. On weekends, the geographical proximity of the intercity travel network improves, with close "center-hinterland" connections and enhanced inter-provincial boundary effects. During holidays, the overall intensity of the intercity travel network increases, with the most significant increase in medium- and long-distance cross-provincial travel. The provincial boundary effect and spatial proximity effect decrease, weakening the structure of the intercity travel network.

Public transportation is a vital means to alleviate urban congestion. Despite substantial investments in public transit infrastructure in China, the development of urban public transportation has been unsatisfactory, with many city residents still favoring car travel. The extensive use of personal vehicles occupies limited road resources, thus exacerbating traffic congestion and environmental pollution. The built environment extensively influences residents' travel choices. Existing studies often describe the characteristics of the built environment from the perspective of the origin, destination, and public transit stops, lacking attention to the out-of-vehicle segments before and after using public transit; moreover, they mainly focus on the built environment faced by transit riders, without fully considering the alternative transit chains for car travelers. Accordingly, this study adopts a trip chain perspective. Combining resident travel surveys and streetscape data from the main urban area of Wuhan, and simulating travel paths using Baidu Maps, this study uses a random forest model to comprehensively analyze the impact of the built environment at the origin, destination, and out-of-vehicle segments on the choice between public transit and private vehicle. The results indicate the following: (1) The performance of the random forest model is superior to that of the traditional Logistic model, and it can reveal the nonlinear relationship between the built environment and travel behavior. At the same time, considering the out-of-vehicle environment also better understands the competitive environment between public transit and private vehicle, thereby improving the model's predictive ability, (2) the built environment is the main factor influencing the preference for public transit, and the out-of-vehicle environment's influence on travelers is no less than that of the built environment at the origin and destination. The preference for transit and built environment factors exhibit a nonlinear relationship, with some factors having different impacts at the origin and destination. Specifically, the population density, intersection density, and transit stop density at the origin and destination have very similar effects on the preference for transit, while the land use mix and job density differ. The proportion of roads and fences in the out-of-vehicle environment show a clear threshold effect, while the proportion of sidewalks and visible green index exhibit a saturation effect. (3) The mechanisms by which the built environment influences the choice of public transit and private vehicle can be summarized into three categories: elastic adjustment, limited support, and direct drive. These findings reveal the effective range of built environment factors in enhancing the attractiveness of transit, providing more rational and precise targeting for policy-making. This study addresses the issue of insufficient detail in the built environment in current research, incorporating the out-of-vehicle environment and alternative modes of travel into the analysis framework of transit preference, providing more intervenable built environment factors to enhance the attractiveness of transit, and offering insights for integrating nonlinear impact relationships into urban planning practice.

High-speed rail (HSR) stations can influence the expansion of the surrounding construction land. However, relevant studies face three main limitations: influence scope estimation lacking a theoretical foundation, less focus on whether the impacts of HSR stations on construction land expansion vary, and misjudgment of the drivers of HSR stations on construction land expansion. To address these research questions, this study first conducts a literature review to theoretically analyze the influence of HSR stations on the surrounding construction land expansion and then identifies the ideal curve for the influence distance of HSR on construction land expansion based on location theory and distance decay theory. Using the 24 stations of the Hainan Roundabout Railway (HRR) as an example, we revealed differences in the influence of various HRR stations on construction land expansion through GIS technology, buffer analysis, and nonlinear fitting to quantitatively analyze the expansion of construction land around HRR stations, identifying the impact range and direction of different HRR stations on the expansion of construction land. Building on the identification of heterogeneous impact results, the study further employed Geodetector to analyze the factors and reasons for the differentiated results of construction land expansion around different HRR stations from four dimensions: attributes of the socioeconomic environment, location conditions, HRR station attributes, and natural conditions. The results show that: (1) after the construction and operation of each HRR station, the surrounding construction land has expanded; the Hainan Eastern Ring HSR (the East Ring) has increased 1.70 km² around each station per year and the Hainan Western Ring HSR (the West Ring) has increased 1.25 km² around each station per year. (2) The changing trend of construction land expansion around 20 of 24 HRR stations conforms to the ideal curve, with the impact range of construction land expansion concentrated within 0.5 km-3.5 km, and the influence intensity of impact ranging from 0.06 km² to 6.64 km². (3) The impact directions of construction land expansion around 20 HRR stations are mainly in three types of directions: "HSR-main urban area," "HSR-town center," and "HSR-scenic spot." This is because the expansion of construction land around HRR stations is not only influenced by the spillover effects of the stations, but also by the traction effect of the main urban areas, town centers, or tourist areas where the HRR stations are located. The stations along the East Ring of Hainan mainly expanded towards the main urban areas, whereas the stations along the West Ring of Hainan mainly expanded towards town centers. (4) Differences in the scope of the influence of each HRR station on the surrounding construction land expansion were mainly related to several variables, ordered as follows: socioeconomic environment, location conditions, attributes of the HRR station, and natural conditions. The GDP density of the towns where the HRR stations were located had the highest impact intensity at 0.51, followed by population density at 0.49, whereas the average elevation had the lowest impact intensity at 0.12. This study analyzed the mechanism and ideal curve of construction land expansion around HSR stations, establishing a logical basis for studying the spillover effects of HSR stations. In addition, this study analyzes the various impacts of HSR stations on the expansion of surrounding construction land and the reasons for these differences, providing a scientific basis for the current operation and future location of HSR stations. This study also offers methodological insights into the impacts of other infrastructures on the expansion of construction land in surrounding areas.

Air cargo is an important component of transportation and plays a vital role in the efficient allocation of high-quality resources on global and regional scales. Air cargo contributes significantly to regional economic development by strengthening inter-regional cooperation and resource integration. However, air cargo geography has received relatively less attention from the research community. Existing studies have analyzed the spatial pattern of air cargo using a limited cross-sectional data from selected years, lacking an analysis of its influencing factors. Based on spatial statistics and panel data of air cargo, this study explores the evolution process and characteristics of China's air cargo pattern on a 20-year time scale and quantitatively reveals its key influencing factors. The research findings are as follows: 1) Air cargo in China has transitioned from the rapid development stage to the stable development stage in the past 20 years; 2) Air cargo volume in China is mainly concentrated in the eastern region, and in the past 20 years, China's air cargo center of gravity has been generally located at the junction of Anhui, Henan, and Hubei provinces, showing a spatial displacement trend from Henan to Anhui to Hubei; 3) The pattern of air cargo network in China remains relatively stable, forming a rhombic structure with Beijing, Shanghai, Guangzhou, and Shenzhen as the core; 4) Air cargo development in China is influenced by factors such as urban scale, industrial structure, and ground transportation development. Among them, urban economy, transportation, warehousing, postal and telecommunications industry, and technological investment have a significant positive impact on air cargo volume, whereas the wholesale and retail trade industries have a significant negative impact. For air logistics hubs, the influencing factors are consistent with those of the entire sample airport. However, for non-aviation logistics hubs, population size and research and technology services have a significant positive impact, whereas ground transportation accessibility has a significant negative impact. This study enriches the long-term time-series analysis and quantitative research content in the field of air cargo and has significance for the development of air transportation geography and the construction of a strong civil aviation industry in China.

The rapid development of information technology has triggered an explosion of data, marking the era of big data. A wide range of transportation big data has been used in urban space and travel behavior studies since the beginning of this century. Mobile phone signaling data in particular have many advantages: they have prevalent spatial and temporal coverage, high tracking stability, satisfactory resolution, and low cost. The description of urban phenomena and the analysis of their forming mechanisms using mobile phone signaling data are thoroughly studied by previous research. The next course of action is to tackle specific urban problems. This study summarizes the application progress of mobile phone signaling data in job-housing relationships and travel behavior studies, discusses the application prospects of mobile phone signaling data in transportation carbon emissions research based on past applications and the existing literature on low-carbon transportation, and proposes a research framework and several future directions for studies using mobile phone big data to examine job-housing relationships, travel behavior, and transportation carbon emissions. We first provide a brief introduction to the features of mobile phone signaling data in comparison with other commonly used data types, including their type, content, and spatial-temporal resolution. We then review the existing applications in job housing and travel research. Regarding the jobs-housing relationship, prior studies employ mobile phone signaling data to detect the spatial distribution of workplaces and residences of urban dwellers, analyze jobs-housing relationship features and urban spatial structure characteristics, and examine the factors influencing jobs-housing relationships. Regarding travel behavior, studies employ mobile phone signaling data to identify stays and trips, infer trip modes, detect trip routes, and explore the universal laws of human mobility. Next, we also discuss how mobile phone signaling data can be applied to transportation carbon emissions research. Indeed, mobile phone signaling data can be used in the calculation of transportation carbon emissions and analysis of the relationships between urban spatial structure, individual travel behavior, and transportation carbon emissions, and its wide coverage and large sample size can be exploited to fill research gaps and problems that have yet to be resolved using traditional traffic datasets. Finally, we present a research framework underlining the indirect and direct effects of the jobs–housing relationship and travel behavior on transportation carbon emissions. We also propose future directions in study contents and methodological innovations by recommending long time-series longitudinal studies, large-scale comparative studies, and new population and transportation phenomena. We further recommend fusing multi-source big and small data, incorporating machine learning algorithms into traditional statistical analyses, and constructing digital twin models. Examining the jobs–housing relationship, travel behavior, and transport carbon emissions using mobile phone signaling data is essential for clarifying the interactions between urban and regional structures, travel behavior characteristics, and transport carbon emissions. It has important implications for emissions reduction and sustainable development in the context of proposing carbon peaking and carbon neutrality goals.

Research on urban spatial networks based on "flow" data has become a new paradigm in the assessment of urban spatial connections and the delineation of metropolitan influence areas in urban geography and territorial spatial planning. Research on urban connections in Chongqing focuses primarily on districts and counties within the city's administrative region, utilizing passenger or cargo flow data to study the spatial structure of the network within Chongqing. However, few studies have been conducted on cross-provincial administrative regions between Chongqing and its neighboring areas, which does not align with the actual influence of Chongqing's metropolitan area. Based on highway traffic passenger flow data, this study employs social network and GIS spatial analysis methods to study the urban network spatial structure between Chongqing and its neighboring areas from the perspective of passenger flow connections. The results indicate the following: (1) Chongqing's central urban area serves as the absolute core of the urban network, with Changshou, Jiangjin, and Bishan as important nodal cities. Fuling, Bishan, and Changshou exhibit notable accessibility within the network, while Fuling, Qianjiang, Jiangjin, and Wanzhou play prominent intermediary roles. There are no prominent regional nodes outside Chongqing's administrative area, and the growth poles for the development of the Chengdu–Chongqing Economic Circle need further cultivation. (2) The passenger flow network between Chongqing and its neighboring areas exhibits a three-tiered axial connection, with the overall network displaying a distinct radial characteristic. The urban clusters in northeastern Chongqing form a distinct band-shaped axis along the Yangtze River with Chongqing. The urban clusters in southeast Chongqing and their neighboring areas exhibit radial axes, with relatively weak connections to the central urban area. Some areas in Guang'an and Dazhou have overcome provincial administrative boundaries, and the network hierarchy is distributed according to "4(level 1)+15(level 2)+18(level 3)." (3) The cohesive subgroups between Chongqing and its neighboring areas demonstrate a high degree of geographical proximity, forming a "core–periphery" structure. This reflects the significant influence that factors such as spatial distance and road extensions exercise on the road passenger transport network. Conducting research on the spatial structure of cross-administrative urban networks from the perspective of highway passenger flow holds significant theoretical and practical value for enriching research on the spatial structure of cross-administrative metropolitan areas and promoting the linkage between Chongqing's metropolitan area and its surrounding regions.

Implementing preferential policies for bus transfers is an important measure for promoting the development of public transportation. Although public transportation extends the travel time of passengers, the preferential policies reduce the travel costs to a certain extent. On the basis of IC card data of public transport, an income method model was constructed to evaluate the cost of passenger flow transfer time after the implementation of the preferential transfer policy in Xiamen and compare it with the reduced fees due to the policy regulations. To better assess the overall benefit of bus transfer travel, the transfer passenger flow was divided into four categories: transfer zero cost passenger flow, transfer additional cost passenger flow, transfer extra time cost passenger flow, and transfer extra time+cost passenger flow. The spatial distribution characteristics of various types of passenger flow are analyzed from five aspects: station, line, traffic area, density of travel starting and ending points, commuting and non-commuting of travel. With regard to stations, a large number of different types of passenger flowed into the area centered on Yueyang Community. As regards route, No. 24 mainly gathered a large number of different types of passenger flows. As regards transportation areas, numerous different types of passenger flows gathered in the transportation communities around the subway and the island's Bus Rapid Transit (BRT) lines. In terms of OD point density, each station of Rail Line 1 and the BRT stations had large numbers of passengers at the starting or ending points. In terms of commuting and non-commuting behaviors, the activity range of various passenger flows during commuting was smaller, the span was shorter, and the cross-island passenger flow was relatively small. In contrast, the passenger flow during non-commuting behavior showed a more evident cross-island trend, and the span was generally longer. This study devised a new passenger flow classification method to evaluate the effectiveness of a preferential policy for bus transfers. Further, it affords a reference for public transport operators to better comprehend the needs and behaviors of passengers and accordingly formulate more effective policies and measures.

Urban agglomerations are the main spatial carriers of national and regional urbanization development. The study of their spatial association networks is of great significance for optimizing the allocation of urban resources, promoting the process of regional integration, and facilitating the high-quality development of urban agglomerations. The Yangtze River Delta urban agglomeration (YRDUA) is one of the most economically active regions in China. Its spatial association network structure was the main feature of economic and social development in China's "14th Five-Year Plan." Based on the perspective of flow spaces in terms of both the city and township scales, multi-source data were used in this study and included online car-hailing origin-destination travel data, combined with complex network models and a quadratic assignment procedure, to analyze the structural characteristics and driving mechanism of the spatial association network of the YRDUA. Results show that: 1) spatial association network based on online car-hailing flow in the YRDUA has spatial dependence and hierarchical characteristics, and intensities of network association are mostly coupled with levels of economic development; 2) spatial association network in the YRDUA displays spatial spillover effects, leading to an overall pattern of high equilibrium in southern development and strong single-point development capacity in the north; 3) the structural features of spatial association network in the YRDUA differ between townships and urban scales, with some high-level townships in certain transportation networks failing to exert their driving role at the urban level; and 4) economic development status, population vitality, the level of urban construction, and administrative division ownership and geographical location differences between townships have significant impacts on the spatial association network structure in terms of the township scale. The differences in administrative divisions are most important. Online car-hailing travel data were used in this study to effectively supplement the links between township streets within and between cities. This data also revealed intercity links. Thus, the development characteristics of spatial units on different scales were reflected, and research and social management needs were satisfied on a fine scale. In addition, by introducing spatial big data and analyzing the influence mechanism from various aspects, such as socioeconomics, the driving factors of the spatial network of urban agglomerations were systematically identified at the small-scale level, which will help with more reasonable planning within the city and play a role in the development of urban agglomerations by enhancing the attractiveness of individual cities. This study expands the research perspectives on the cooperative development of urban agglomerations on different scales, providing theoretical references and practical support for the promotion of the coordinated development of urban agglomerations as a whole.

The Fourteenth Five-Year Plan of China has proposed the acceleration of the construction of a strong transport nation. The Outline for the Construction of a Powerful Transportation State emphasizes that it is necessary to focus on the general objective of the construction of a powerful transportation state and create a "123 traveling and transportation circle in the country" and reach the new standard of 1-hour commuting metropolitan area, 2-hour connecting urban agglomeration, and 3-hour coverage of the major cities in the country, which determines the importance of the accessibility of urban agglomeration in the strategy. The high-speed railway network in the twin-city economic circle of the Chengdu-Chongqing region enhances inter-city accessibility and has a spillover effect on socioeconomic development. Starting with HSR network accessibility, in this study, the evolution of the accessibility pattern after the opening of the HSR in 2015, 2020, and 2025 was analyzed using the shortest inter-city travel time, weighted average travel time, and daily accessibility index. Based on the gravity model used to measure the economic reinforcement effect generated by HSR network accessibility, the spatial Durbin model was used to explore the spillover effect of HSR network accessibility on the tertiary industry's economic development from 2015 to 2020. The study results demonstrate that the HSR network improves the level of urban accessibility, narrows the gap of accessibility level between cities, weakens the regional accessibility circle structure, and exhibits significant corridor effect. The HSR network generates a significant spatiotemporal convergence effect. The direction of spatiotemporal convergence of core cities is to expand uniformly to their surroundings, and the direction of expansion of edge cities is mainly to spread along newly opened HSR lines in the form of a belt. The improved accessibility of the HSR network will strengthen regional economic ties, narrow the gap between the attractiveness levels of non-core cities, and enhance the twin-core phenomenon. Increased accessibility is conducive to the economic development of the tertiary industry in neighboring cities, with an increase of 1 percentage point in the accessibility of the high-speed rail network in the neighboring region, leading to an increase of 0.3088 in the local tertiary industry. An increase in the tertiary economic level of neighboring cities will inhibit the development of the local tertiary economy, which may be because the Chengdu-Chongqing region is now more competitive than cooperatives in terms of urban relations; therefore, regional development is still in the siphoning stage. The possible contribution of this study is reflected in the use of accessibility as the core research and explanatory variable to explore the economic spillover effects of accessibility of high-speed rail networks in typical case regions. It aims to reveal the impact of high-speed rail network accessibility on the economy and industry, summarize the theory of spillover effect, and provide a theoretical reference for high-speed rail construction, regional planning, and economic layout optimization.

Chinese people have become important international buyers of second homes in many destination countries, particularly Malaysia, Thailand, and other Southeast Asian countries. In the past decade, the aging population and the quest for a better life have become pressing concerns in China and have triggered an increase in transnational second-home purchases in other countries. However, despite the significant and rapid growth of transnational second homes in China, little is known about the nuanced relationship between buying motives and life satisfaction. Current studies in the Western context offer limited theoretical and practical implications for Chinese transnational second homes because Chinese buyers exhibit different motives and have a distinct understanding of a good life. Based on the push-pull theory, this study examines Chinese transnational second-home buyers' motivation and life satisfaction and the relationship between these two constructs. Data were drawn from 340 Chinese transnational second-home buyers of R&F Princess Cove in Johor Bahru, Malaysia. Structural equation modeling (SEM), Importance-Performance Map Analysis (IPMA), and multi-cluster analysis (MGA) were used to process the data. Our empirical results show that, in comparison to Western second-home buyers, Chinese second-home buyers' tourism and residential experiences and overall life satisfaction are significantly affected by pull motivations, while push motivations exhibit less influence. Among all the dimensions of push motivations, the natural and tourism environment, cultural and life atmosphere, and service facilities are crucial motivations in order of priority. Economic factors (such as prices and cost of living) also influence but are not the most important factors. Both tourism and residential experience significantly affect Chinese second-home buyers' overall life satisfaction, with residential experience exhibiting a higher influence. Women and larger second-home groups value residential experiences more than other groups, while smaller buyers value travel experiences more. This study provides new evidence for future studies on Chinese transnational second homes and responds to the current academic discussions on second-home buyers' motives in transnational contexts. Finally, this study has practical implications for domestic second-home destination construction and marketing.