In the era of financialization and global financial integration, the Global Financial Network (GFN) serves as a crucial analytical framework for comprehending the landscape and the dynamic evolution of global financial geography. While existing research predominantly focuses on international financial centers centered around New York and London, there remains a notable gap concerning local economies successfully integrated into GFN and the hierarchy and regionality of GFN. This study examines the overseas Initial Public Offerings (IPOs) of 79 Quanzhou enterprises to illustrate the key geographic units, network structures, and formation of GFN through intra-enterprise services and collaboration linkages. This study uses Gephi to analyze the network characteristics of global financial networks quantitatively. This study forms the layout of financial centers participating in overseas IPOs of Quanzhou enterprises through the Fruchterman Reingold algorithm. Moreover, this study measured the centrality distribution characteristics of the network using indices such as intermediary centrality and eigenvector centrality. This study selected 79 companies listed on overseas IPOs in Quanzhou from 1993 to the end of 2023 as samples. We confirmed that the FABS enterprise sample includes 50 securities firms, 21 accounting firms, and 56 law firms. From a spatial scale perspective, these FABS corporate offices are distributed in 26 cities worldwide. The cooperative network of FABS enterprises is a network matrix of 371×371, including 205 inter-city collaborations and 166 intra-city collaborations. In addition, from 2020 to 2022, we interviewed 50 interviewees to understand the process of Quanzhou’s integration into GFN. The interviewees of this study include executives of listed companies in Quanzhou, founders of relevant upstream suppliers, leaders of industry associations, and heads of relevant government departments. 1) Quanzhou enterprises, primarily rooted in traditional manufacturing, chose to list neighboring regional financial centers for overseas IPOs, thus contributing to the emergence of a regional GFN. Geographic conditions and industrial profiles of local economics are pivotal in understanding the formation of regional GFN. 2) Within the regional GFN established via Quanzhou’s overseas IPOs, Hong Kong emerges as the central node. Hong Kong serves not only as a key IPO destination but also as a crucial intermediary facilitating Quanzhou’s integration into the global financial landscape. Due to the perspectives of financing entities and financing regions, this study reveals how the location conditions and industrial characteristics of financing regions affect the formation of regional GFN spatial structure. This enriches the perspective of GFN research and, more importantly, deepens the understanding of the existing spatial structure of GFN centered around London and New York. Additionally, the spatial relationships within regional GFN among regional FABS enterprises, regional financial centers, and financing regions, reveal the inherent connections and behavioral patterns of cross-border financial actors. This case echoes the “with” relationship in existing GFN research at the regional scale. This study proposes the hierarchy and regionality of GFN, emphasizing the importance of regional GFNs in global financial flows and responding to the attention of economic geography to the regional transformation of global networks.
Knowledge spillover is a crucial concept for explaining innovation. As a form of knowledge, technology possesses a spillover effect. This study posits that technology enterprises provide technical critical support for modern financial industry development, while financial institutions procure these technical services through market. This process facilitates the establishment of cross-industry urban innovation linkages between technology and financial firms through technological spillover. Distinct from previous research that constructed urban innovation networks based on homogeneous activities or internal connections within the same industry, this study employs Python web scraping technology to collect transaction information and constructs a cross-sector urban innovation network. This transaction data details purchase of technologies—such as Blockchain, Artificial Intelligence, Big Data, Cloud Computing, and the Internet of Things (IoT)—by commercial banks from technology enterprises across cities in China (excluding the data of Hong Kong, Macao and Taiwan). Leveraging these transaction data for technologies applied in emerging FinTech business services, an inter-city FinTech network is constructed from a technology spillover perspective. Network analysis reveals: 1) A FinTech network has preliminarily taken shape in China. Although the network density is not high, it exhibits a core-periphery structure and possesses small-world properties; 2) The geographical concentration of core nodes in the network is pronounced, with transactional linkages closely associated with eastern cities. The core node cities demonstrate outstanding technological spillover capabilities and higher administrative ranks, with Guiyang emerging as a core node in the western region; 3) Distinct network patterns emerge across 3 major urban agglomerations, with differential technology absorption tendencies among 3 types of commercial banks; 4) Urban innovation capability, financial environment, economic development, administrative hierarchy, and transportation accessibility differentially impact technology absorption versus spillover effects. Technology demand-driven spillovers establish the foundation for cross-sector urban innovation networks. The FinTech network will not only provides new paradigms for deconstructing urban innovation systems but also poses new propositions for assessing the competitiveness of cities housing major technology enterprises under integrated finance-technology ecosystems.
The scale characteristics of the city, as well as its functional status in the associated network, jointly shape a new pattern of urban system development. Based on the inter-regional investment data of listed companies from 2005 to 2022, a directed weighted city network is constructed to characterize the network structure and evolution characteristics of the urban system. The measurement method of alternative centrality for directed weighted city networks is improved. According to the dual dimensions of the city size centrality and directed weighted alternative centrality, cities are classified into different levels. The panel vector autoregression model is used to explore the dynamic interaction effects of the economic scale, population size, and network status of cities. The results are obtained as follows: 1) The pattern of city network connectivity is gradually evolving from being driven by the dual core of Beijing and Shanghai to a multi core linkage radiation. The distribution of network connections has gradually achieved full coverage of the “Hu Huanyong Line” in the southeast area with dense and extensive network connections, and shows obvious spatial differences. The high-intensity investment connections are gradually occupying a dominant position. And the city network shows a distinct feature of “hierarchy and network”. 2) The “core-periphery” hierarchical structure of the spatial distribution of directed weighted alternative centrality is constantly manifested. The directed weighted alternative centrality of most cities continues to increase, evolving from being distributed only in the fourth level to the sixth level to covering all 6 levels. The number of capital agglomeration cities has increased significantly, and the asymmetric characteristics of nodes in the city network are significantly enhanced. 3) Under the dual dimensions of “size-network”, cities are classified into 5 grades: national core cities, national sub-central cities, regional core cities, regional sub-central cities and local general cities. The typical manifestations are the “scale-network” status matching type cities represented by Beijing, Xi’an, Suqian, and there are also the “scale-network” status non-matching type cities represented by Chongqing, Hefei, Luoyang, Zhoushan. 4) There is a significant sustained positive interaction effect between directed weighted alternative centrality and economic scale. The change of population size has a relatively long-term one-way effect on directed weighted alternative centrality, while the change of directed weighted alternative centrality has only a short-term positive effect on population size. The conclusions are helpful to deepen the understanding of the structural characteristics of urban system and provide reference for optimizing urban development strategy and promoting regional coordinated development.
Intercity relationships can be categorized into multiple types, with collaborative relationships and flow relationships being 2 of the main types. Collaborative relationships stem from cities with similar functions achieving economies of scale or with different functions achieving functional complementarity, while flow relationships arise from the potential differences between source and destination cities. This study, based on an analysis of the differences in the formation of collaborative and flow relationships, examines the structural and influencing factors of collaborative and flow networks from the perspective of venture capital relationships. The study finds that the differing mechanisms of these two types of network relationships lead to differences in the influence of distance and city size combinations. However, both types of networks exhibit a certain degree of similarity in reflecting the regional economic landscape, such as displaying similar hierarchical structures. Moreover, while two-way aggregated flow networks are relatively similar to collaborative networks, one-way flow networks can more accurately reveal the characteristics of flow relationships. By analyzing 20 311 venture capital events across 251 Chinese cities, we highlight that core cities like Beijing, Shanghai, and Shenzhen dominate both networks, yet their roles diverge: Shanghai acts as a capital supplier, while Shenzhen exhibits stronger capital outflow. The gravity model reveals that city size significantly enhances collaboration and capital flow, whereas geographic distance inhibits only the latter. Notably, directional flow networks uncover asymmetric patterns, with 144 cities solely contributing capital outflows. These findings challenge the conventional aggregation of bidirectional flows in urban network studies, demonstrating that unidirectional analysis better captures power dynamics in resource allocation. The study underscores the necessity of integrating relational typologies—such as collaboration versus flow—into urban network frameworks to refine theoretical interpretations of intercity interactions. Practically, policymakers should tailor strategies for capital-attracting versus capital-exporting cities to optimize regional economic synergies. This study distinguishes the pattern differences between collaborative and flow relations, highlighting the importance of differentiating relationship types in urban network research.
Urban agglomerations serve as crucial bridges facilitating the flow of cross-regional innovation factors and promoting technological spillovers among cities. Most existing literature treats urban agglomerations as the analytical boundary, overlooking the differentiated impact of urban agglomeration strategies on inter-city technology transfer. To address this, based on Chinese patent transfer data from 2001 to 2020, this study analyzes the overall characteristics and spatiotemporal dynamics of patent transfers within cities within 19 urban agglomerations, between urban agglomerations and their surrounding cities, and among cities in different urban agglomerations across four time periods. Utilizing a difference-in-differences model, the study examines the impact of urban agglomeration strategies on patent transfers at different scales, focusing on the coordination effect, agglomeration effect, and linkage effect of urban agglomerations. The study found that: 1) The scale and density of the patent transfer network in 19 urban agglomerations have been continuously increasing, with deepening connections and intensities. The network efficiency and accessibility have been continuously optimized, and the spatial distribution of the patent transfer network overall presents a pattern of ‘high in the east and low in the west’. 2) The spatial structure of the patent transfer network in urban agglomerations exhibits characteristics of polycentricity and regionalization, with the ‘diamond structure’ centered around Beijing, Shanghai, Guangzhou, and Chengdu-Chongqing gradually emerging. This structure forms a "hub-and-spoke" knowledge flow channel with other regional central cities. 3) The proportion of patent transfers across agglomerations has gradually increased, indicating that the spatial scope of knowledge innovation is expanding and the spatial heterogeneity of knowledge flows is decreasing. 4) The results of the difference-in-differences model verify that the urban agglomeration strategy can promote patent transfers within cities within the same urban agglomeration, between urban agglomerations and their surrounding cities, and between cities in different urban agglomerations. Overall, the implementation of the urban agglomeration strategy has not only played a significant role in regional development but also had a profound impact on inter-city technology transfer in China. This study analyzes the dynamic changes of patent transfer networks within and outside urban agglomerations from multiple dimensions and delves into the differentiated impact of urban agglomeration strategy implementation on China’s intercity technology transfer network. It provides new perspectives and ideas for understanding the evolution of intercity innovation networks and the future innovation development of urban agglomerations. Through this study, it is hoped that the spatial organization mechanism of technology transfer networks can be further deepened, providing scientific support for better promoting innovative integration practices in urban agglomerations and promoting technological innovation and high-quality economic development in urban agglomerations.
Current research on urban networks still has some shortcomings, such as insufficient analysis of industrial chains, neglecting the distinction between local and non-local embedding, and insufficient attention to industrial connections in the digital economy. In view of this, this article attempts to take the Chinese digital game industry as an analytical case. Based on the basic paradigm of urban network research, it starts from the perspective of industrial chain division of labor, focusing on exploring the urban network structure and cooperation models formed by the digital game industry through industrial chain division of labor. It further analyzes the industrial chain position and the evolution of local-global embeddedness of the Chinese digital game industry, thereby promoting the dialogue between urban network research and industrial chain theory and solidifying the analysis of the industrial connection connotation in urban network research. This study selected cooperation data at both the national and global scales from 2013 to 2023, involving 283 cities worldwide. Social network analysis was employed to measure the urban cooperation network structure of China’s digital games, and the internalization link index was used to analyze the differences in local and cross-city connections of game enterprises at different spatial scales. The findings are as follows: 1) The national-level city collaborative network of China’s digital gaming industry has a polycentric structure, reflecting the decentralized characteristics of the digital economy; at the global scale, there exist 3 collaborative models: “Overseas R&D and Publishing-Domestic Operation” (Model 1), “Domestic R&D-Overseas Publishing and Operation” (Model 2), and “Domestic Publishing and Operation-Overseas R&D” (Model 3). Model 1 has the largest network of cities, and Models 2 and 3 are expanding rapidly. 2) Overall, Chinese cities are still in the middle and lower segments of the global digital gaming industry chain, with significant dependence on cities in the United States, Japan, and Europe in the R&D and publishing sectors. However, with the rapid development of Models 2 and 3, cities represented by Beijing, Shanghai, Chengdu, and Xiamen are continuously upgrading their positions in the global industry chain. 3) Over the past decade, the local-global connectivity of China’s core gaming cities has undergone significant spatial restructuring, mirroring the global industrial chain reconfiguration. Nationally, most cities have transitioned from localized to cross-city domestic collaborations, aligning with the delocalization trend in digital creative industries. Globally, Chinese cities demonstrate reduced external dependency, shifting from strong international-weak domestic ties to domestic-dominated collaboration patterns, with Shanghai emerging as the sole metropolis sustaining robust dual local-global linkages. These evolving spatial embeddedness patterns reflect the industry’s self-optimization and value chain upgrading trajectory. This study contributes to the dialogue and incorporation between industrial chain and urban network research. Future research needs to analyze in more detail the driving mechanisms, globalization strategies and local embedding patterns of Chinese cities’ participation in the division of labor in the global digital game industry chain through more in-depth enterprise surveys and industry chain analyses.
This study constructs a network based on investment data from listed companies among cities. It uses social network analysis and structural resilience indices to measure and evaluate the investment network structure and resilience in the urban agglomeration in the middle reaches of the Yangtze River. The results show that: 1) The urban agglomeration in the middle reaches of the Yangtze River is forming a triangular investment skeleton with Wuhan-Changsha-Nanchang as the vertex. The overall investment network density remains low but continues to grow. Cities play different roles in the network, and core cities are strengthening their control. 2) The investment network shows clear heterogeneity and hierarchy, making it vulnerable to shocks. However, it is gradually becoming more balanced and flat. 3) The network has strong matching resilience. Connections between nodes tend to be heterogeneous and diverse. Enterprise investment flows enhance the “robustness” of these connection paths through overlap. 4) The network has high and improving transmission efficiency. Overall, it demonstrates strong connectivity resilience. 5) The network shows some clustering. Investments mainly flow one-way from core cities to peripheral cities. This helps peripheral cities develop while reducing risks for core cities, improving the network’s structural resilience.
As the world’s longest border road spanning 10 051 km from Xinjiang to Guangxi, China’s G219 Border Road epitomizes a linear tourism destination integrating ecological, cultural, and mobility functions. This study constructs a tourism corridor experience system framework comprising 4 core dimensions: 1) landscape resources, 2) catering and cuisine, 3) hotel accommodation, and 4) self-driving services. Deploying a mixed-method approach combining spatial resource visualization, network spatial structure analysis, and field investigations, we dissect the resource distribution patterns and tourism flow dynamics along the G219 corridor. Our findings reveal three critical insights: Firstly, the G219 manifests as a mobility-dominated linear system characterized by spatial viscosity, flow aggregation, and path radiation. Its structural uniqueness arises from the “node-zone” interaction, where key attractions concentrate tourism flows while roadside service clusters extend spatial stickiness through multi-day stays. Secondly, the network nodes and tourism flow along the route are the core elements that characterize the tourism corridor and its impact. Therefore, there are significant differences in tourism resources, geographical space, and self driving service systems among 4 provinces/regions along the G219 Border Road for self-driving tour. Thirdly, the image of tourism corridors is the driving force that attracts the flow, process, and velocity of self-driving tourists during their travels. We argue that optimizing the G219 requires differentiated spatial governance: 1) Node enhancement, upgrading gateway facilities to anchor tourist flows; 2) Zone integration: weaving greenways, ethnic villages, and cultural assets into thematic itineraries; 3) Cross-regional coordination: standardizing self-driving services while preserving segment uniqueness. This study contributes to linear tourism theory by validating the “corridor-system” framework in border road and offers actionable models for trans-provincial tourism planning. Future research should quantify flow-service mismatches and assess socioecological impacts of corridor-driven development.
As an important component of the Yangtze River Delta Economic Belt, the basin of the Yangtze River in Anhui Province faces dual pressures of economic and social development as well as ecological environment conservation. From the perspective of endangered species, constructing ecological network is of great value for the flow of regional geographical elements and the coordinated development of social and economic factors. Therefore, this study used the MaxEnt model to determine the sources based on the habitat and environmental data of cranes from 2000 to 2020. The Circuit Theory was used to construct ecological network. The results indicated that: 1) The area of sources decreased from 103.48 km2 to 52.61 km2 from 2000 to 2020, with a decrease of 49.16%. 2) From 2000 to 2020, the number of corridors decreased by 48.15%, the total length of corridors decreased by 47.69%, the number of pinchpoints decreased by 22.73%, and the ratio of barrier points to corridor length increased by 56.10%. The integrity of ecological network reduced. 3) From 2000 to 2020, theα index decreased by 45.90%, and the network connectivity decreased. Theβ index decreased by 27.46%, and the network gradually simplified. 4) The results of the impact factors for the ecological network indicated that the main impact factors of resistance surface are population density, slope, and Shannon Diversity Index, while the main impact factors of current are Shannon Diversity Index, population density, and Landscape Shape Index. This study will provide important references for the optimization and management of the ecological network in basin of the Yangtze River in Anhui Province.
Exploring the causal relationships among various elements in surface processes and quantifying their causal effects are crucial for understanding the laws of surface changes. In recent years, the rapid development of remote sensing technology and causal inference research has provided opportunities and possibilities for revealing the interaction patterns in multi-scale surface processes based on remote sensing observation data. However, research on causal relationships, causal effects, and causal inference in the field of geoscience is still in its infancy, and the study of the causal mechanisms and laws of multi-scale surface processes still faces many challenges. This article first reviewed the research progress of the theoretical framework and methods of causal inference. Then, we explored the possibility of temporal causal inference methods in attributing surface vegetation changes through experiments. Finally, we summarized the opportunities and challenges faced by causal inference in the study of surface processes. The research results showed that: 1) Causal relationship discovery and causal effect assessment are urgent needs and frontier hotspots in the current research and development of surface processes. However, they still face many challenges, such as overly strong causal assumptions, difficulties in identifying false causal relationships, and a lack of verification datasets. 2) Experimental results based on the spatiotemporal change process of surface vegetation in Yunnan Province from 2001 to 2020 showed that the temporal causal inference methods had a significant effect in discovering the causal relationship and assessing the causal effect of surface vegetation cover changes. Experimental results showed significant causal relationships and lag effects between vegetation and climate factors. Among these factors, temperature and surface temperature are the primary influences on surface vegetation changes in Yunnan Province. At the same time, vegetation has obvious feedback effects on climate factors. 3) In the context of big geographical data and large geoscience models, the construction of datasets to support the verification of causal inference of surface processes, causal inference of spatiotemporal coupling and the interpretable machine learning approaches will be the future development direction.
Lake surface water temperature (LSWT) is a crucial physical parameter in lake ecosystems and an important indicator of climate change. Studying the spatiotemporal variation patterns of LSWT in China over long-term time series and exploring the driving factors behind these changes hold significant scientific importance for understanding the impacts of future climate change on lake ecosystems. Furthermore, such research provides valuable insights for formulating practical and effective lake ecological management measures. This study systematically analyzed
As a core production factor in the era of digital economy, data elements play an important driving role in the carbon emission reduction efforts of various industries. This paper selects 30 provinces (autonomous regions and municipalities) in China from 2013 to 2022 as research samples to explore in depth the incentive effect and spillover effect of data elements on agricultural carbon emission reduction. First, an ordinary panel regression model is used to analyze the incentive effect of data elements on agricultural carbon emission reduction. Then, a mediating effect model is employed to test the transmission mechanism between data elements and agricultural carbon emissions. Finally, a spatial Durbin model is applied to analyzing the spatial spillover effect of data elements on agricultural carbon emissions. The following conclusions are drawn: 1) Data elements have a significant environmental incentive effect, which can promote regional agricultural carbon emission reduction. 2) In the inhibitory effect of data elements on agricultural carbon emissions, there exist mediating roles of supervision effect, resource effect, and cost effect. 3) Data elements have a significant spillover effect on agricultural carbon emissions, that is, while inhibiting local agricultural carbon emissions, data elements can also inhibit agricultural carbon emissions in adjacent regions. Based on the above analysis, this paper puts forward practical suggestions from three aspects: technological innovation, policy formulation, and data supervision.
Coastal areas are now economic zones with strong comprehensive strength, high population density, and strategic significance due to rapid urbanization. Nevertheless, urbanization is also a major contributor to local ecological pressure overload, which has significantly altered the regional carbon cycle process. Developing strategies to attain carbon neutrality requires an understanding of how the urbanization process affects the carbon balance. In this study, we evaluated the effects of urbanization rate and nine urbanization process characterization elements on the carbon balance of 53 prefectural-level coastal cities between 2003 and 2022 using structural equation model and geographically and temporally weighted regression. The findings indicate that: 1) Over the past two decades, the carbon balance of coastal areas has exhibited distinct regional distribution characteristics. Northern coastal cities have mostly become net carbon emitters, while southern cities generally act as carbon sinks. 2) Urbanization has a net negative impact on carbon balance, indicated by a total effect of −0.178. The effect size of the characteristic elements of urbanization level was land use (−0.556), ecological quality (0.345), population size (−0.212), energy consumption (−0.277), environmental governance (−0.029), industrial structure (−0.102), technological innovation (−0.006), economic growth (−0.080), and foreign investment (−0.129). 3) The urbanization rate, land use, population size, and other factors have varying impacts across different coastal cities, contributing to the spatial heterogeneity of the carbon balance. Among them, according to the annual change trend, the regression coefficient of the urbanization rate has been increasing over the past two decades. Hence, to achieve a win-win situation between socio-economic development and ecological and environmental protection, it is imperative to strengthen the guidelines of green urbanization, implement the differentiated carbon balance reconstruction strategy, and promote the sustainable development of coastal areas.
The China-Russia crude oil pipeline (CRCOP) is a major strategic energy corridor for China, greatly ensuring the country’s energy security. It is located in the Great Khingan region of Northeast China, traversing areas of permafrost and seasonally frozen ground, making it highly susceptible to frost heave hazards. Therefore, timely monitoring and evaluation of its stability are of great importance. In this study, we used Sentinel-1B 12-day-span differential interferograms between 2016 and 2021 to monitor ground surface deformation along the CROP. After correction and stacking of differential interferograms, multi-year average deformation during the freezing season along about 1 000 km CRCOP corridor region was firstly obtained. Analysis showed that 17% of the land surface in the 20 km buffer zone along the pipeline had an average frost heave greater than 20 mm, with strong frost heave areas (deformation greater than 50 mm) accounting for 3%. By segmenting the pipeline into 1 km intervals and analyzing the deformation of the terrain each segment traverses, we found that the number of pipeline segments traversing significantly frost-heaved ground accounted for 17% of the total number of segments, with strong frost heave segments (deformation greater than 50 mm) accounting for 1%. Significant frost heave was observed in the northern regions from Mohe Station to Tahe Station, and wetland-affected areas near Heihe, Qiqihar, and Daqing City in the south. Using a geographical detector to analyze environmental factors affecting frost heave, combined with statistical analysis of frost heave at ponding sites, it was revealed that soil moisture conditions are the most significant factor affecting frost heave. The frost heave deformation monitoring results and spatial pattern analysis presented in this study provide valuable references for engineering construction and maintenance of CRCOP.
The rapid development of digital technologies has made digital narrative an emerging and important means for the protection and utilization of cultural heritage. This new form of interpretation not only provides fresh opportunities for the preservation and presentation of heritage resources, but also exerts significant influence on the development of heritage tourism and on tourists’ heritage responsibility behavior. Building on the perspective of digital affordance and the cognitive-affective personality system theory, this study constructs a mechanism model to examine how the affordance of cultural heritage digital narrative affects tourists’ heritage responsibility behavior. To empirically test the model, the research adopts structural equation modeling and combines it with qualitative data obtained from semi-structured interviews, thereby investigating how different dimensions of cultural heritage digital narrative affordance exert influence through cognitive and emotional pathways. The findings indicate 3 main results. First, under the setting of cultural heritage digital narrative, the digital affordance can be conceptualized as comprising physical and cognitive dimensions, both of which show significant positive impacts on tourists’ heritage responsibility behavior. Second, destination psychological ownership together with destination image serve as mediating variables, jointly transmitting the effects of physical and cognitive affordance on tourists’ heritage responsibility behavior. Third, destination familiarity plays a positive moderating role in this relationship: when tourists possess a higher level of familiarity with the destination, the positive influence of digital affordance is strengthened, while lower familiarity weakens the relationship. In conclusion, this study supplements existing theoretical research by identifying the digital antecedents of tourists’ heritage responsibility behavior and by clarifying how digital affordance functions through emotional and cognitive mechanism. At the same time, it provides practical reference for cultural heritage managers, demonstrating how digital technologies can be effectively applied in heritage protection and in the development of heritage tourism.
The pervasive influence of digitalization is profoundly reshaping global production networks and international trade dynamics, elevating the strategic importance of ports as critical nodes in digitally integrated supply chains. Consequently, the synergy between the digital economy and geography has become a crucial nexus of study. This study addresses the significant challenges hindering the digitalization of Chinese ports, including ill-defined strategic roadmaps, a lack of effective multi-scale coordination among stakeholders, and the underutilization of advanced technologies in practical operational scenarios. Compounding this, the existing academic literature has yet to provide a comprehensive framework to guide these transitions. To fill this gap, we investigate the core issues of the coupled development between ports and digitalization. Through a comparative case study of leading international ports, we identify and categorize 3 distinct digitalization pathways: 1) Innovation-driven, which is propelled by internal R&D and technological breakthroughs; 2) Scenario-integrated, which focuses on applying digital solutions to specific, practical operational contexts; and 3) Ecosystem-collaborative, which is driven by synergistic partnerships among a wide array of port-city stakeholders. Building upon the theory of post-generational evolution, we propose a holistic coupling model conceptualized as the SUSTAINS framework: Space (the integration of physical and virtual port realms) + Union (fostering deep collaboration and data-sharing alliances) + Scale (harmonizing governance and operations across local, regional, and global levels) + Transformation (managing the organizational and technological shift) = Sustainability (achieving long-term economic, environmental, and social viability). This model provides a novel theoretical lens and a practical roadmap, aiming to advance the discourse in digital economic geography and empower policymakers to build the resilient, intelligent, and sustainable ports of the future.
There are numerous traditional villages in China. Most of them are concentrated in mountainous and hilly areas, which are the organic integration of agricultural and ecological culture. During the formation and development of village, cherishing water resources has always been the core idea of adapting and changing the environment. Based on the traditional ecological thoughts, spatial planning concepts, and landscape adaptability theories, the water adaptive research framework of spatial morphological characteristics and landscape mode in the mountainous tradintional villages can be constructed by the methods such as spatial analysis, morphological quantification and landscape visualization. Taking Baojing County in Xiangxi as an example, the differences of water adaptability in villages can be sorted out, including spatial distribution, morphological pattern and landscape pattern. The result shows that: 1) Traditional villages are usually located in relatively low altitude river valleys, exhibiting obvious characteristics such as living by water, facing the sun, and building on gentle slopes. They are not only convenient for water use, but also effective in flood control and drainage, water and soil conservation, which reflects the wisdom of site selection for harmonious coexistence between humans and water. 2) Under the influence of complex water environmental factors, traditional villages can be classified into 3 typical spatial forms: belt shaped, cluster shaped, and finger shaped. With the development of the economy and society, the village space structure exhibits distinct differentiation characteristics. For example, the villages of belt shaped are usually crossed by a small river, and the development relies on cultivated land economy. The villages of cluster shaped are usually built in the river bay area, and the development relies on forestry economy. The villages of finger shaped are usually far from the river but adjacent to ponds, and the development relies on terrace economy. 3) Based on typical topography, 3 water adaptive landscape models can be summarized to deal with drought and flood, such as “forest-village-farmland-river” in flat area of mountains, “forest-orchard-village-river” on the hillside, “forest-village-farmland-pond” on the mountain plateau.
Ice and snow tourism is an important engine to stimulate the vitality of the ice and snow economy and promote the high-quality economic and social development of ice and snow cities. Previous studies have mostly focused on single factor impact analysis or empirical strategies to explore the tourism development of ice and snow cities, with few exploring the logic and path of ice and snow city tourism development from a systematic perspective of multiple factors. Therefore, based on the TOE (technology-organization-environment) framework, this paper utilizes fuzzy set qualitative comparative analysis (fsQCA) to comprehensively analyze the key influencing factors of the high-quality development of tourism and its grouping paths in 15 key ice and snow cities across the country: Harbin, Zhangjiakou, Shenyang, Jilin, Changchun, Urumqi, Hulunbuir, Mudanjiang, Heihe, Chifeng, Chengde, Yichun, Qiqihar, Fushun, and Beijing. The results show that: 1) The high-quality development of ice and snow city tourism is the result of the linkage of multiple factors. A single factor is not the key factor restricting the high-quality development of ice and snow city tourism, but the complex combination of multiple factors is an effective path for the high-quality development of ice and snow city tourism. To promote the high-quality development of tourism in ice and snow cities, it is necessary to pay attention to the linkage and adaptation of multiple factors at the same time. 2) There are 4 types of driving paths for the high-quality development of ice and snow city tourism, which can be divided into technology-driven, technology-organization dual driven, technology-environment dual driven and technology-organization-environment balanced driving according to the core conditions of each combination path. The combination of different antecedents forms a variety of driving types, indicating that there are diversified combination paths and driving types for the high-quality development of ice and snow city tourism. 3) The technical factors composed of technical infrastructure, smart culture and tourism platform, and ice and snow equipment manufacturing technology are the core factors for the high-quality development of ice and snow city tourism, indicating that technical factors play a relatively common role in promoting the high-quality development of tourism. This study can enrich the theoretical research on the high-quality development of ice and snow economy and tourism to a certain extent, and also provide academic support and decision-making reference for the high-quality development of ice and snow city tourism.
Conservation tillage is widely recognized for its critical role in promoting soil conservation and sustainable agricultural development. However, its potential suitability has not been systematically assessed across different regions. In China, the rational utilization of straw resources and the suitability analysis of conservation tillage in the Songnen Plain are essential for fostering sustainable agricultural development in the region. In this study, the improved Vegetation Photosynthesis Model (VPM) was employed to estimate straw yield in the Songnen Plain using the Google Earth Engine (GEE) platform. This analysis incorporated Sentinel-2 time-series remote sensing imagery, air temperature, radiation data, and harvest indices from the literature. Remote sensing imagery was used to extract vegetation growth and moisture status, while temperature and radiation data simulated biophysical processes within the model. For model validation, the study compared remote sensing estimates with measured data and county-level statistics. Subsequently, conservation tillage potential of the Songnen Plain was assessed by defining and applying conservation tillage conditions in conjunction with the estimated straw yield and climate data. The results indicated that the correlation coefficient (R 2) between the estimated straw yield and county-level statistics for 2022 was 0.93, with a root mean square error (RMSE) of 175 200 t. TheR 2 between measured and estimated straw yields was 0.62, with an RMSE of 936.4 kg/hm2, demonstrating that the improved VPM model provided more accurate straw yield estimations. Based on climate conditions and straw yield, 94.93% of the Songnen Plain is suitable for conservation tillage. This study confirms the validity of the VPM model in estimating maize straw yield and evaluates the potential for conservation tillage in the Songnen Plain. The findings provide scientific data to support the comprehensive utilization of straw resources and the implementation of regional conservation tillage, offering a theoretical basis for the sustainable development of agriculture.
