Investigations have revealed significant degradation of nearshore coral reef areas in the South China Sea in recent decades; thus, coral reef conservation is in urgent need of more scientific management insights. The health of coral reef ecosystems can be effectively assessed by utilizing the photosynthetic ecological parameters of zooxanthellae, which are symbiotic with scleractinian corals. In this study, six genera of scleractinian corals (Platygyra, Dipsastraea, Favites, Porites, Acropora, and Pavona) from Weizhou Island, Daya Bay, and Wanshan Archipelago in the northern part of the South China Sea were experimentally studied. Three physiological parameters, namely the density of coral symbiotic zooxanthellae, chlorophyll-a content, and photosynthetically effective quantum yield (Φ _PSII), were measured to understand the photosynthetic characteristics of scleractinian coral symbionts in relatively high-latitude corals, compare their intergeneric differences among different coral morphologies, and explore the ecological effects of environmental factors by analyzing spatial similarities and differences. The study results are as follows: First, a one-way analysis of variance and non-parametric tests based on the division of individual coral distribution areas showed overall significant spatial differences in the density and chlorophyll-a content of scleractinian corals' zooxanthellae from the Weizhou Island and Daya Bay (P≤0.01); no significant spatial differences were observed in the physiological parameters of photosynthesis for those from the Daya Bay and Zhuhai's Wanshan Archipelago; Redundancy analysis(RDA) analyses indicated that Sea Surface Temperature(SST) was the most important environmental factor affecting the density and chlorophyll-a content of the coral symbiotic zooxanthellae. Due to its unique geographical location and environmental factors, the ecological status of coral communities in the Daya Bay is well-maintained with higher density and chlorophyll-a content of symbiotic zooxanthellae in the relatively high-latitude sea area. Second, the density and chlorophyll-a content of the zooxanthellae of Platygyra from the Daya Bay were significantly higher than those of Acropora and Pavona. Coral morphology may be a key driver influencing the relationship between density and photosynthesis of the symbiotic zooxanthellae. Massive corals generally had higher symbiotic zooxanthellae density and chlorophyll-a content and showed greater tolerance to thermal stress than branching corals. Under similar morphologies, significant interspecific differences in the density of symbiotic zooxanthellae in corals were also observed, which may be related to their unique skeletal structures and physiological characteristics. These findings reveal that the physiological responses of scleractinian corals and their symbiotic zooxanthellae to environmental changes are not fixed, and that coral morphology and interspecific differences have complex effects on their ecological adaptations.

Coral reef systems are vital natural barriers that dissipate wave energy and protect coastlines. However, anthropogenic damage has severely compromised this protective function, necessitating restoration efforts such as submerged breakwaters. To understand the influence of discontinuous submerged breakwaters on wave hydrodynamics over reef flats, this study employed physical model experiments and numerical simulations. A series of irregular waves were tested under scenarios with and without a breakwater, systematically varying the key parameters: significant wave height, water depth over the breakwater crown, spectral peak period, and gap width. The results demonstrate that discontinuous submerged breakwaters reduce the hydrodynamic loads on reef flats by generating wave reflection and refraction, as well as by enhancing the viscous dissipation of rip currents at discontinuities with incident waves. Specifically, breakwaters reduce the infragravity wave energy and wave heights, wave-induced set-up on the reef flat, and maximum wave run-up on the back reef slope. The reduction in wave run-up and reef flat set-up is most significant under minimal significant wave height conditions. Increasing the water depth over the breakwater crown can lead to incomplete wave breaking, thereby causing a relative increase in the contribution of short waves to the total wave run-up. Increasing the gap width enhances the effectiveness of the breakwater in reducing both the run-up and set-up, while simultaneously weakening the resonance amplification of infragravity waves on the reef flat. Conversely, increasing the spectral peak period intensifies infragravity wave resonance. Finally, the complex hydrodynamics along the reef are revealed using the waves2Foam model in OpenFOAM to construct a three-dimensional numerical wave flume. The study found that abrupt rip currents are generated at the discontinuities of submerged breakwaters while simultaneously reducing the onshore flow velocity over the reef flat. In conclusion, discontinuous submerged breakwaters are a viable engineering measure for mitigating coastal hazards in degraded reefs by reducing damage to infragravity waves, wave set-ups, and wave run-ups. These findings provide essential mechanistic insights and quantitative guidance for designing effective reef restoration and protection structures that incorporate submerged breakwaters.

Analysis of the spatiotemporal agglomeration trends of individuals' daily activities can contribute to gaining a better understanding of the temporal and spatial selection characteristics of residents' daily activities, and the utilization of urban space. This is of considerable practical significance for improving the living environment and enhancing the quality of life of residents in affordable housing in the context of the current era of optimizing existing stock. In this study. we examined a large-scale affordable residential area in Nanjing as an empirical case. Based on the perspective of "family division of labor" and the activity log data of the residents in the large-scale affordable residential area, we initially applied a spatial autocorrelation model to construct a spatiotemporal autocorrelation function, and depicted the overall characteristics of the spatiotemporal agglomeration of the daily activities of the residents in this area from the dual scales of "main urban area–residential area." In addition, we conducted a comparative analysis of the spatiotemporal agglomeration characteristics of different activities. In this context, we characterized and compared the spatiotemporal response patterns of the daily activities of residents in this type of residential area. We subsequently undertook theoretical derivation, interpretation and refinement of the temporal and spatial selection processes of the daily activities of residents in large-scale guaranteed residential areas. From the perspective of spatiotemporal agglomeration trends, our findings revealed that the spatial and temporal clustering of the daily activities of residents in large low-income residential areas is often closely associated with the intensity of family division of labor and spatial scale. Among these, the spatial and temporal clustering of daily activities under medium and high intensity division of household labor was observed to be more obvious at the main urban area scale, whereas daily activities under low and medium intensity division of household labor were more concentrated on the scale of residential areas. From the perspective of response mode, we detected clear difference between the temporal-family and spatial-family response patterns of all types of activities, particularly between work and non-work activities. From the perspective of the interpretive model, the temporal range of different activities can be ordered as maintenance activities > survival activities > free activities, and the interaction of the temporal response process mainly occurs between the medium- and high-intensity division of household labor. Moreover, the spatial scope of different activities can generally be ordered as survival activities > maintenance activities > free activities, and the interaction of the spatial response process is mainly reflected in the high-intensity division of household labor. By examining the spatiotemporal patterns and decision-making mechanisms of residents' daily activities. we can provide necessary guidance and a basis for the construction of an ideal living circle for residents in large-scale public welfare residential areas.

In this study, the variation law of nonlinear characteristic parameters of waves near islands and reefs with different slopes was examined through physical model tests. The main conclusions are as follows: (1) When a regular wave propagates to the shallow water area of the first reef flat, the peak becomes steep, the trough becomes flat, and the wave surface presents a shape similar to an elliptical cosine wave. The wave shallowing deformation near the reef flat steps reaches the limit, the amplitude increases significantly, and the front surface of the wave peak becomes steep and gradually asymmetric. The wave breaks on the second reef flat, the wave energy transfers from the main wave frequency to the high frequency, the traveling wave is regenerated, and an obvious secondary wave peak appears. (2) In the process of wave propagation from the far-sea end to the vicinity of the reef edge, because of the shallowing deformation, high-order constrained harmonics are generated, which makes the wave surface asymmetric along the horizontal axis and vertical axis. The amplitude of the wave skewness, asymmetry, and peak of the Usser number reaches a maximum near the reef flat step and then decreases rapidly on the second reef flat. The wave surface gradually approaches symmetry in the direction of the horizontal axis and the vertical axis. The amplitudes of the three nonlinear characteristic parameters increases with the increase in incident wave height and wave period and decreases with the increase in reef flat water depth. (3) When the nonlinearity of the incident wave is stronger, the asymmetry and skewness are larger. As the Eser number increased, the wave skewness showed a positive correlation with the increasing trend, while the asymmetry showed a negative correlation with the decreasing trend. A certain correlation was observed between the wave skewness and asymmetry on the reef flat with different slope and the local Ursell number. Based on this result, this study proposes a set of empirical formulas for wave skewness and asymmetry parameters on reef flat with different slope angle.This study enriches the hydrodynamic theory of complex coral reef coasts and lays a foundation for further research on the ecological environment protection and coastal evolution mechanism in the sea area near coral reefs. However, this study only discusses the variation law of wave nonlinear characteristic parameters near islands and reefs with different slopes under the influence of wave factor changes. In the future, the influence of differences of island topography on wave nonlinearity should be studied in greater detail.

Crown-of-Thorns Starfish (CoTS) are natural enemies of corals. Periodic outbreaks of CoTS and substantial feeding on corals lead to the degradation of coral reefs among the Indo-Pacific Ocean. Symbiotic bacteria play an important role in the development, reproduction, and digestion of CoTS. However, little is known about their composition and function. The pyloric ceca are the main digestive organ of CoTS. In this study, the composition and function of bacteria in the pyloric ceca of 15 adult A. solaris collected from the coral reef area of Xisha Islands were tested by high-throughput sequencing. A total of 833 bacterial OTUs were detected in the pyloric ceca, belonging to 26 phyla, 55 classes, 115 orders, 171 families, and 278 genera. The dominant phyla were Proteobacteria (94.50%), and the dominant genera were Vibrio (60.61%), Ralstonia (17.86%), and Photobacterium (6.64%). The symbiotic bacterial composition of other reef-associated organisms with different feeding habits, distributed in the Xisha Islands, were different. Composition of the pyloric cecal bacteria of CoTS were relatively similar to that of the coral symbiotic bacteria owing to the presence of some same bacteria genera in microbiome. Moreover, Vibrio was the dominant bacteria in both the pyloric cecal bacteria of CoTS and symbiotic bacteria of bleached Acropora solitaryensis, indicating high similarity. Therefore, the feeding habit of corals might be the important factor that affects the bacterial composition of the pyloric ceca of CoTS. The bacterial composition of the digestive tract of CoTS from the Great Barrier Reef of Australia and Japan showed the presence of Vibrionales, Burkholderiales, Rhizobiales, and Bacillales. However, significant regional differences were observed between the bacterial composition of the Xisha Island and Great Barrier Reef of Australia or Japan. Vibrio was more abundant in samples from the Xisha Islands than those from the Great Barrier Reef and Japan. This might be related to the massive coral bleaching events in the Xisha Islands from 2020 to 2021, which increased the relative abundance of Vibrio among the symbiotic bacteria of bleached corals. Additionally, as a potential Vibrio transmission vector, CoTS can pose a threat to the coral reef ecosystem in South China Sea. The results of bacterial function predict that their genome function was mainly focused on metabolism. The pathways with high relative abundance included carbohydrate, amino acid, cofactors and vitamins, and lipid metabolism. These results suggest that pyloric cecal bacteria may be involved in the daily physiological metabolic processes of CoTS. Thus, they might help digest corals by secreting hydrolytic enzymes. This study revealed the community composition, diversity, and affecting factors (feeding on coral) of pyloric cecal bacteria in CoTS from Xisha Islands, South China Sea.

Bike-sharing has emerged as a crucial mode of short-distance transportation for urban residents due to its flexibility, convenience, and affordability. This paper analyzes the spatiotemporal data of bike-sharing in the central urban area of Shenzhen to explore usage patterns and characteristics, with the aim of optimizing bike-sharing system management and scheduling. Initially, we used statistical methods to conduct an exploratory analysis of the data, uncovering the temporal, spatial, and Origin-Destination (OD) flow characteristics of urban cycling. Following this, we applied a tensor decomposition model to the spatiotemporal correlation characteristics of bike-sharing data, enhancing our understanding of the spatiotemporal cycling patterns of residents in central Shenzhen. Bike-sharing usage in Shenzhen displays significant spatiotemporal patterns, with high-frequency usage areas on both weekdays and weekends concentrated in the mid-southern part of the Nanshan District, southeastern part of the Futian District, and southwestern part of the Luohu District. Notably, on weekdays, two distinct morning peaks were observed in bike usage, indicating a more diverse spatial travel pattern. During morning peak hours, bike usage is primarily concentrated in residential and commercial areas, while during off-peak hours, it shifts to areas around recreational facilities. By integrating the initial statistical analysis with tensor decomposition, we constructed a comprehensive model of bike-sharing usage that accounts for variations across different days of the week and times of the day. This model helps identify the most significant OD flows and their interactions over time and space. We also incorporated Points of Interest data to better understand the potential travel purposes of bike-sharing users, linking high-usage areas with specific types of destinations, such as business districts, educational institutions, and recreational areas. The findings of this study have important implications for urban planners and bike-sharing operators. The clear identification of high-usage areas and peak times can inform more efficient bike redistribution strategies, ensuring that bikes are available where and when they are most needed. Moreover, understanding the dynamic nature of bike-sharing usage patterns can aid in designing better infrastructure, such as dedicated bike lanes and improved parking facilities, that cater to the needs of bike-sharing users. Our research also contributes to the broader field of urban mobility studies by demonstrating the effectiveness of tensor decomposition in analyzing complex spatiotemporal data. Unlike traditional methods that may treat time and space independently, tensor decomposition allows for a more integrated approach, capturing the interactions between different dimensions of data. This provides a richer, more nuanced understanding of urban mobility patterns. Future research will aim to integrate other transportation datasets, such as public transit and ride-hailing services, to provide a more comprehensive view of urban mobility and further enhance the understanding of population flow dynamics in high-density urban environments.

The accelerated promotion of new urbanization has brought about population mobility, which has placed greater pressure on megacities in terms of inter-regional competition for high-quality resources in compulsory education and their carrying capacity. To achieve high-quality and balanced development of compulsory education, it is not only necessary to achieve a balanced allocation of resources in terms of quantity and structure, but also to pay attention to the spatial balanced distribution of quality. This study uses Wuhan, a central Chinese megacity, as a case. Integrating Point of Interest data of primary and secondary schools, educational resources, road network information, this study uses GIS methodologies, such as the nearest neighbor index, coefficient of variation, kernel density analysis, service area network analysis, and an improved 2SFCA method to evaluate the spatial distribution characteristics of compulsory education resources in Wuhan and the accessibility and resource distribution equilibrium across districts. In terms of spatial quantity equilibrium, although the distribution of primary and secondary schools in Wuhan's districts is relatively uniform, the resource density is biased towards the central urban areas and shows a single-center clustering, resulting in sparse resource distribution in the remote urban areas. In terms of spatial structural equilibrium, considering students' commuting modes, time cost and the matching of supply and demand, primary schools exhibit better accessibility and resource equilibrium than junior high schools. In terms of spatial quality equilibrium, the human, material, and financial resource allocation equilibrium of primary schools is generally better than that of junior high schools, and both primary and junior high schools in the remote urban areas are less balanced than those in the central urban areas. This imbalance in resource distribution is in conflict with the population expansion and uneven distribution in the urbanization process of Wuhan. Therefore, it is suggested that the future layout for compulsory education in Wuhan should be combined with regional functions, population size, and educational needs to strengthen the forward-looking allocation of educational resources and land use planning in the remote urban areas, optimize the educational layout of functional areas to adapt to population growth and enhance accessibility, and build a balanced system of teacher resource allocation to promote the high-quality and integrated development of compulsory education. This study builds a spatial analysis framework based on a three-dimensional perspective of 'quantity-structure-quality', which expands the research perspective of high-quality and equilibrium allocation of compulsory education resources, and the spatial accessibility analysis from the perspective of supply and demand provides methodological references for other megacities to optimize the layout and resource allocation of primary and secondary schools in different regions, and also enhances the understanding of the differentiated layout of compulsory education resources in different administrative districts of megacities.

Coastal nebkhas are an important component of coastal sand dune ecosystems, widely distributed at varying scales, and the key subject of coastal aeolian geomorphology research. This paper systematically reviewed the morphological characteristics, developmental evolution, and dynamic processes of coastal nebkhas, summarizing the major advancements in research and technical methods both domestically and internationally. Key findings include: the establishment of dune developmental stages based on the correlation of dune morphological parameters (horizontal scale and height); the volume of coastal nebkhas is related to wind and sand activity, ocean dynamics, and biological factors; the dune formation mechanism is a coupled process consisting of wind-driven dynamics, sand source supply, and vegetation stabilization, with coastal environments indirectly influencing dunes through vegetation and wind-sand interactions; the relative importance of different factors varies across regions during dune development; airflow and its interaction with shrub dunes exhibit significant differences in various dune parts, with windward slopes generating reflective eddies that enhance wind speed, and leeward slopes forming horizontal and vertical vortices. Vegetation species type, coverage, density, and distribution all affect near-surface wind-sand movement, with the highest sand deposition typically occurring near vegetation on the windward slopes, where sand transport decreases. A technical approach combining observational and simulation studies has shaped the research, especially with the recent application of new technologies, such as Unmanned Aerial Vehicle measurement systems and computer simulations, which have significantly advanced the study of coastal nebkha morphology, airflow structure, and sediment transport patterns. However, current research faces three main limitations: an incomplete understanding of the development mechanisms of coastal nebkhas, and a need for deeper exploration into their dynamic mechanisms. In the future, the focus should be on combining traditional observations with modern emerging technologies to strengthen the study of the main limiting factors and their interaction mechanisms during the formation and development of nebkhas and deepen the understanding of their formation and development mechanisms in China. Through comprehensive field surveys, typical investigations, and morphological measurements of key distribution areas of coastal shrub dunes, multi-scale, long-term, continuous dynamic monitoring should be conducted. It is important to analyze the formation and evolution mechanisms of coastal nebkhas in different regions, providing a scientific basis for cross-regional dune management and protection. A comprehensive study of the joint action mechanisms of wind dynamics, hydrodynamics, particle adhesion, and biological forces is essential to reveal the spatiotemporal dynamic evolution patterns of coastal nebkhas in China, both annually and inter-annually. Furthermore, the influence mechanisms of vegetation ecological processes, human activities, and climate change on coastal nebkhas should be emphasized, addressing the gaps in domestic research and improving the research framework for coastal aeolian geomorphology in China.

Against the backdrop of rapid urbanization and escalating risks posed by extreme rainstorms, the complexity of urban hydrological systems and limitations of fragmented data-driven approaches underscore the necessity of constructing integrated frameworks to enhance rainstorm situation awareness. Traditional methodologies typically rely on isolated physical monitoring, digital modeling, or social response mechanisms and fail to address the interdependencies among physical infrastructure, informational technologies, and social systems. This study aims to deepen our understanding of how digital and intelligent technologies can be configured across a physical–informational–social ternary space to achieve robust urban rainstorm governance by identifying context-specific empowerment paths and their applicability to diverse urban typologies. Guided by the theoretical framework of the physical–informational–social ternary space, this study employs a mixed-method approach combining fuzzy-set qualitative comparative analysis (fsQCA) and Latent Dirichlet Allocation (LDA) modeling to investigate the pathways through which digital and intelligent tools empower urban rainstorm perception and to explore the disaster-affected characteristics of cities under different configurational paths. By tracking 35 typical Chinese cities, the fsQCA analysis reveals three differentiated empowerment configurations: (1) Balanced ternary space empowerment (G1), which achieves high-efficiency empowerment through three-dimensional collaboration among physical space data integration (including real-time sensor networks for hydrological monitoring), informational space intelligent analysis (including machine-learning-based risk prediction models), and social space emergency response (including interagency coordination systems), relying on dynamic interactions across the three domains. (2) Physically–socially dominant ternary space empowerment (G2): Grounded in core conditions of multisource data integration (combining meteorological, topographical, and citizen-generated data) and high disaster perception efficiency, this configuration incorporates peripheral conditions of server-side intelligence (including cloud-based data analytics) and user-side participation (including mobile application-driven hazard reporting), emphasizing data diversity and user-centric empowerment. (3) Physically–socially interactive binary space empowerment (G3): Empowerment is realized through the binary coupling of multisource data integration and high perception efficiency as the core conditions, prioritizing the technical synergy between physical monitoring and informational processing. Concurrently, a single-dimensional, low-empowerment configuration, which relies on isolated spatial data or technologies, is found to be insufficient for comprehensive disaster perception, thus empirically validating the necessity of ternary space configurational intersections. LDA topic modeling further demonstrates that different digital-intelligent empowerment patterns align with distinct disaster-sensitive city types: G3 suits hazard-sensitive cities (including Guangzhou), G2 matches vulnerable cities (including Xi'an), and G1 benefits exposure-sensitive megacities (including Beijing and Shanghai). Theoretical contributions of this study include constructing a "ternary space for urban rainstorm situation awareness" framework, which systematically analyzes the effects of digital-intelligent empowerment through the coupling mechanism of real-time physical space perception, intelligent informational space processing, and optimized social space decision-making—thereby transcending the limitations of traditional technological determinism. Methodologically, the research overcomes the constraints of single-method approaches by retaining fsQCA's strength in causal necessity analysis and integrating LDA's capability for semantic theme identification, forming a complete explanatory chain of "causal mechanisms-adaptive paths-type characteristics." At a practical level, this study proposes differentiated implementation strategies that provide both theoretical foundations and practical guidance for the digital and intelligent enhancement of urban rainstorm situation awareness.

Study of the history of Chinese geography has lasted for over a century, providing different historical interpretations to the two less studied fundamental issues of "the similarities and differences between China and foreign countries" and "the transformation from the ancient to the modern". Focusing on representative research, this paper explores the research presuppositions, methodology, and contents that are linked to them, revealing the evolution of research approaches for these two fundamental issues. Over the past century, four research approaches have formed in the study of the history of Chinese geography. First, the analogical interpretation approach, which used the connotation of traditional Chinese geography to understand modern geography introduced from abroad and concluded that modern Chinese geography was based on its ancient traditions, but only existed in the early 20^th century. Second, the reverse analogical interpretation approach, which aimed to construct an ancient Chinese geographical knowledge and disciplinary system that conformed to modern geographical standards. It had multiple understandings of "the similarities and differences between China and foreign countries" in the 1930s to 1940s, but became monotonous after the 1950s under the influence of Wang Yong's radical views, thereby reconstructing the ancient system of Chinese geography in the modern sense; this approach faced narrative obstacles in explaining its autonomous early modernization. Third, the restoration approach, which emerged in the 1990s, was based on criticizing the anterior monotonous approach. It restored the social, ideological, and cultural significance of ancient Chinese geography, namely the dynastic geography from the perspective of contextualism on the level of the history of ideas and constructed its content system. So far, the early modernization of Chinese geography relied on the explanation of the communication theory of social, cultural, and institutional transformation. Fourth, the circulation approach, a new breakthrough in the study of the history of Chinese geography, revealed the gradual early modernization of Chinese geography through the collision, integration, and renewal of Western geography with China as subject from the perspectives of global history and the history of the circulation of scientific knowledge, breaking through the narrative obstacles of the theories of communication and revolution regarding the early modernization of Chinese geography. Although each of the four research approaches has its own specific object of observation, the evolution of the critical layers constitutes a more comprehensive perspective for understanding the history of Chinese geography. Under the trends of global histories of science, it is necessary for the study of the history of Chinese geography to rethink the significance and nature of the two fundamental issues mentioned above to avoid the centralized frameworks and discourses, to emphasize the relationship between geographic traditions and the socio-cultural scenarios, to highlight the history of circulation of Chinese and Western geography on the level of the knowledge networks, and to reveal the tasks that deserve attention in the study of the history of Chinese geography.

Using images and interview data from the Nanzhi Street in the Songyang County, combined with K.-S. Lee's five-dimensional theory of food memory, this study explores the impact of media and commercialization on traditional food and local memory. This work analyzes how five factors—population hollowing, commercialization of preparation methods, standardization of sensory experiences, weakening of emotional connections, and uniformity—affect the relationship between food and local memory. It also discusses the mediating role of media as an intermediary factor. The findings indicate: (1) Loss of native residents: The departure of native residents has led to external operators maintaining emotional ties but failing to restore the community atmosphere. The demographic shift in the Nanzhi Street has transformed local memory from the emotional memory of native residents to the commercial memory of external operators. Media has simultaneously enhanced commercial vitality and accelerated the commodification and symbolization of local memory; (2) Differences in shop styles: There is a clear distinction between the styles of registered and non-registered shops. Registered shops preserve local characteristics but tend toward symbolic traditional appearances under policy support and media influence, while non-registered shops cater to influencer-driven culture, leaning towards commercialization. This dual influence maintains commercial vitality but also speeds up the commodification of local memory, reflecting the tension between preserving local culture and pursuing commercial development; (3) Changes in traditional food and sensory experiences: The preparation methods and sensory experiences of traditional food have changed to meet consumer demands, leading to differences in how tourists and locals perceive local memory. Media's simplified narratives and excessive commercialization reduce the cultural depth of local cuisine, reinforce stereotypes, and overlook the importance of craftsmanship and deep-rooted culture. These shifts not only affect consumer perceptions but also undermine the authenticity and completeness of local memory. Additionally, under the influence of commerce and media, traditional food has become increasingly standardized, with weakened artisanal techniques and local characteristics. Younger consumers are more exposed to adapted, standardized flavors, further simplifying the cultural essence of local cuisine and diminishing its role in cultural diversity and regional identity; (4) Impact of media on emotional connections: Media's influence on emotional connections is dual-faceted. For locals, private memories are made public, transforming traditional food from a familial emotional symbol into a symbol of local culture. For tourists, media transforms local memory into a commodified and emotionalized product, replacing personal connections with consumer-driven experiences. This shift reflects the commercialization of local memory and highlights the disconnect in emotional ties between locals and tourists, as private memories are gradually replaced by mass-consumption emotions. The work reveals the conflict between commercialization and local characteristics in the Nanzhi Street under media and policy guidance, emphasizing the importance of preserving local memory and emotional connections during urban transformation.

The first half of the 20th century was a critical period in the transformation of Chinese geography from tradition to modernity. The geography departments of higher education institutions, as the main organizations for research and teaching in Chinese geography at the time, reflected the developmental trajectory of geography in China. Although research has yielded certain scholarly achievements, three notable limitations persist in current academic investigations. First, it places excessive emphasis on "establishment" events while neglecting dynamic processes, such as "disciplinary restructuring," "institutional reorganization," and "closure," thus failing to fully capture the complexity of academic department development. Second, owing to incomplete historical materials, there are significant discrepancies in the statistical counts of academic departments, which often include non-geography departments or proposed departments that were never operational. Third, insufficient attention to geography departments in normal universities and their structural transformations within the discipline has resulted in an incomplete understanding of the pathways toward disciplinary specialization. This study adopts a chronological approach that integrates and utilizes diverse sources of materials, including the National Education Yearbooks, university statistical data, admission guides, institutional historical archives, memoirs, enrollment records, and contemporary research findings. Cross-validation identifies the years of establishment, restructuring, reorganization, and closure of geography departments, thereby clarifying their founding, restructuring, reorganization and closure processes. This study further analyzes their quantitative characteristics, developmental stages, institutional affiliations, and disciplinary structures. The research findings indicate the following: 1) Regarding the number of departments established, it has been confirmed that 52 universities and colleges founded 63 geography departments, a figure significantly higher than that reported in existing studies (Approximately 40). This discrepancy arises from two aspects: on the one hand, existing studies fail to fully account for the restructuring and reorganization of geography departments; on the other hand, eight previously overlooked geography departments in universities have been included. 2) The establishment process can be divided into four stages: 1904–1928 (initial establishment period), 1929–1936 (period of minimal expansion), 1937–1945 (period of moderate expansion), and 1946–1949 (period of slow expansion). The overall trajectory across these stages is characterized by slow growth amid frequent cycles of founding, restructuring, reorganization and closure, with fewer than half of the established departments remaining operational by the end of the period. 3) Regarding departmental distribution, the majority were located in universities and normal colleges, with a high proportion in normal colleges. From 1904 to 1928, geography departments were mainly located in normal universities, whereas a new trend emerged from 1929 to 1936, with their affiliation shifting toward the faculties of science in universities. 4) Regarding the disciplinary structure, significant differences exist between different types of institutions; university geography departments are primarily aligned with geology and meteorology. Clearly defined differences in disciplinary structure can be observed across different periods, especially pronounced between 1929–1936 and 1946–1949, where independent department characteristics emerged distinctly. Normal universities display a prominent association with history and geography, with earlier instances of interdisciplinary association with Chinese literature, history, and natural sciences. Through multisource historical evidence corroboration and chronological textual research, this study comprehensively illuminates the developmental process of geography departments in China. First, it corrects the number of geography departments, highlighting the academic contributions of marginal institutions. Second, it divides development into four stages, demonstrating the impact of warfare and policies on the rise and fall of these departments. Additionally, it tracks the transition from integrated to independent systems, illustrating the process of scientific development in geography. Ultimately, these findings provide a foundational basis for researching the history of modern Chinese geography, educational policies, and academic systems, while also offering historical references for contemporary disciplinary construction and institutional planning.

This study aims to broaden the research scope of the history of geography in China. The materials used for the study included Harm J. de Blij's profile (CV), website, autobiography, geography textbooks, and research papers, as well as reviews and research from geography peers. De Blij is a contemporary geography master in political geography, geography textbooks, geography education, and scientific communication in geography. He is a representative of the systems theory school of political geography. He wrote several renowned geography textbooks, including System Political Geography, Human Geography: Culture, Society and Space, Geography: Realms, Regions and Concept, which acted as television precedents for geographical education. and also served as an editor for Journal of Geography and the founding editor of National Geographic Research. He is keen on geographic public speech and has popularized geographical knowledge and concepts. He is probably best known for being the geographic editor of the ABC TV program "Good Morning America" and his high-end science communication books The Power of Place and Why Geography Matters. Because of its innovative character, System Political Geography has scholarly and pedagogical impacts. Most political geography books at the time were dominated by chapters describing the circumstances of selected world regions or reviews of different attributes of states, such as population, resources, and environment. Harm's book encouraged thinking about the conceptual underpinnings of different ideas in political geography: the functional approach and the unified field theory. Second, Harm's book systematically examined particular historical developments of colonialism, the rise of the nation-state, and so on. Third, Harm's book included substantial excerpts from original papers. Human Geography: Culture, Society and Space and Geography: Realms, Regions and Concept are two popular textbooks in Harm's textbooks that act as an introduction to Human Geography and Geography. The Chinese edition of Human Geography: Culture, Society and Space was published by Beijing Normal University Press in 1988, and is considered an important teaching reference for human geography courses. Harm also made important contributions to scholarship on the role of geography in public debate, publishing pieces in the Annals of the Association of American Geographers and Progress in Human Geography and encouraging academic geographers to reach beyond the confines of the academy. Harm's lifelong thinking about political geography culminated in his book Why Geography Matters, which was revised and expanded several years later (de Blij 2012). Harm set a good example of high-quality geography textbooks based on academic research, actively spreading and promoting geography thinking, and writing popular science works and newspaper column articles based on hot issues from the perspective of geography. We can learn a lot from Harm J. de Blij on the main three aspects.

With the increasing integration of urban public transportation modes, the demand for first- and last-mile travel has become an urgent issue. Owing to its convenience and affordability, bike-sharing has been recognized as an effective solution for addressing this need. To better understand the demand for intermodal trips involving bike-sharing and conventional buses, this study focuses on the spatial heterogeneity of such trips. A method based on bike-sharing density was proposed to identify intermodal trips near bus stops. The spatial distribution of these trips was then analyzed. Geographically Weighted Regression and Multiscale Geographically Weighted Regression models were employed to examine the effects of land use, population, socioeconomic attributes, transportation environment, and destination accessibility on intermodal trip demand. Spatial variations in these effects were also assessed. The results indicated that the density of bike-sharing trips near bus stops followed a consistent pattern. The density decreases with increasing distance from the stop, and the rate of decline exhibits a "U-shaped" pattern. A buffer radius of 50 m was identified as the optimal threshold at which the rate of decrease was minimized. Trips within this radius accounted for approximately 17.1% of all bike-sharing trips. In Shenzhen, intermodal trips were primarily concentrated in southern Longhua, western Luohu, Futian, and central Nanshan. Secondary concentrations were observed in Guangming and Bao'an districts. The spatial distributions of trip origins and destinations showed minimal differences, indicating a relatively balanced distribution. This distribution aligns with the overall pattern of bike-sharing activities. The explanatory variables exhibited significant spatial heterogeneity in their effects on intermodal trip demand. Shopping facilities, hotel accommodations, cultural and educational institutions, GDP, and distance to the city center were found to have positive effects. Among these, the influence of shopping facilities was particularly notable in the central areas, with weekdays' coefficients concentrated around 0.057 and more dispersed on weekends. The impact of hotel accommodations was dispersed across weekdays and weekends. Cultural and educational facilities had a weekday coefficient concentration of approximately 0.098, whereas the weekend effects were more scattered. GDP demonstrated the highest positive influence among all variables, with coefficients of 0.176 on weekdays and 0.150 on weekends. The coefficients for distance to the city center were relatively concentrated at 0.110 and 0.233 on weekdays and weekends, respectively. By contrast, residential land-use density, road network density, and stop proximity exhibited inhibitory effects. Coefficients for residential land-use density were -0.020 on weekdays and -0.018 on weekends. Road network density showed coefficients of -0.020 and -0.010, respectively. The effect of stop proximity varied more spatially. Additionally, tourist attractions have time-sensitive effects, suppressing intermodal trip demand on weekdays and promoting demand on weekends. It is suggested that designated bike-sharing parking zones be established within a 50-m radius of bus stops to reduce the transfer walking distance. On weekdays, more bikes should be deployed near schools and residential areas; on weekends, the deployment should focus on scenic areas and bookstores. These findings help to delineate the effective spatial scope of intermodal trips and reveal how various built environments and socioeconomic factors shape trip patterns. The results offer practical insights for improving the coordination between bike-sharing and conventional buses, enhancing the overall efficiency of public transport and increasing its appeal to commuters.

Historical physical geography is a discipline that investigates the changes in various natural factors within geographical environments during historical human periods. The establishment of modern Chinese historical geography was profoundly influenced by Western historical geography theories and methodologies, particularly those of the Anglo-Americans. However, the English-speaking academic world lacks a distinct disciplinary framework analogous to that of "historical physical geography" (such as the term "historical physical geography" itself remains exceptionally rare). This discrepancy relates to the fact that historical physical geography, a crucial component and subfield of Chinese historical geography, originated from knowledge exchanges with Soviet theoretical frameworks in the early 1950s. The organizational model of "task-driven disciplinary development" fundamentally catalyzed the establishment of historical physical geography in China and significantly accelerated the modern transformation of Chinese historical geography. While domestic academia has robustly defended the legitimacy of historical physical geography through arguments addressing institutional structures, disciplinary alignment between geography and historical geography, essential differences between natural and human geography research paradigms, and the richness of Chinese historical archives, it remains undeniable that the disciplinary orientation that emerged in the 1950s directly adopted Soviet conceptual frameworks and theories. Furthermore, an academic approach that overlooks the practical realities of Soviet historical geography while seeking to ground the theoretical essence solely within the Chinese context necessitates potential revision and deeper exploration. This study examines the core theoretical contributions of Soviet historical geography during the same period. A comparative analysis of Sino-Soviet developments in historical physical geography reveals that China's "task-driven disciplinary development" model served as the practical foundation for its establishment. Despite direct conceptual influences from Soviet scholarship, Chinese historical physical geography has independently shaped its theoretical framework under specific historical conditions, largely achieving innovation and constructing an autonomous knowledge system, thereby advancing the discipline's comprehensive modernization. As a product of the Sino-Western intellectual synthesis, reconstructing the evolution of Chinese historical geography using a country-specific comparative approach holds significant methodological value in research on the geography of scientific knowledge.

As an important economic form for the innovation and development of human society, since the 21st century, the low-altitude economy has become one of the key ways to promote China's modern industrial development, with its unique charm and broad application prospects. Research on the low-altitude economy of manned vehicles has a long history. However, this research is still growing; and there are many ambiguities within the human-cultural research of low-altitude economies. Therefore, it is necessary to review the existing results so as to promote the development of a theoretical and methodological system for low-altitude economic research. Based on data from the Web of Science (WOS), Scoups, and CNKI databases with the low-altitude economy as the research theme, the CiteSpace software was used to comprehensively sort out the publication status, research content, and research lineage of domestic and foreign low-altitude economy research. This study analyzes and summarizes the characteristics of the publication, subject matter, and characteristics and trends of the various phases. The results show that: (1) Although the leading figures and research teams of domestic and foreign low-altitude economy research have initially appeared, there are fewer cross-institutional academic contacts and a broad academic consensus is yet to be formed. (2) There are also differences in the development history and research characteristics of domestic and foreign low-altitude economy research, but in the early stage of the research, the focus is mainly on general aviation. It then moves to a new era of drone dominance that is centered on the low-altitude economy after 2010. (3) As is, foreign studies have focused on, for example, the exploration of UAV models and their engineering technology, UAV traffic management systems, UAV application scenarios. On the contrary, Chinese studies focus on the reflection and summary of the reform of low-altitude airspace, construction of UAV systems and their industrial development, etc. (4) The directional shift of the low-altitude economy from the natural space to the human-cultural space is an important feature in this growth period but the current low-altitude economy research on human culture is still in the trial phase. Therefore, it is recommended that scholars establish a scientific system suitable for the development of low-altitude economies in China, expand research perspectives and interdisciplinary cooperation, and strengthen extensive communication and exchanges among scholars, which helps construct a diversified inter-institutional, interdisciplinary, and inter-geographical cooperation network. In addition, it will deeply excavate the human-earth relations and spatial organization concepts in the study of low-altitude economies and integrate natural-social-economic-humanities perspectives on intelligent, synergistic, and sustainable development of UAVs, as well as systematically expose the UAV industry chain, UAV-related supporting facilities, market consumption, and public attitudes. This study aims to accelerate the high-quality development of China's low-altitude economy and comprehensively promote its modern development.

With rapid societal development, economic growth, industry, agriculture, and human activities, large amounts of sewage rich in nitrogen, phosphorus, and other nutrients are produced. This causes eutrophication in lakes and reservoirs, leading to frequent algal blooms that pose a serious threat to aquatic ecosystem stability and drinking water safety. Chlorophyll-a (Chl-a) concentration, a core indicator of algal biomass and the degree of eutrophication in water bodies, correlates positively with algal bloom outbreaks. However, Chl-a concentration variance under the influence of multiple factors displays highly nonlinear characteristics. Traditional prediction models are unsuitable for relationship analyses between environmental factors, generally producing low prediction accuracy with weak applicability. To address this challenge, we proposed a short-term chlorophyll a concentration prediction method based on multi-scene segmentation, and constructed a prediction model with enhanced adaptability by recognizing the characteristic laws of different environmental scenarios to improve the accuracy of Chl-a concentration prediction. By analyzing the laws influencing various factors, we proposed three partitioning strategies: 1) factor interaction and scene partitioning by analyzing connections between key environmental factors and adopting K-means method to partition these scenes, 2) diurnal difference scene partitioning based on diurnal cyclicity of algal physiological activities, dividing the data into two scenarios, and 3) trophic state scenarios, based on Trophic Level Index. A water body is divided into three trophic categories: anaerobic, mesotrophic, and eutrophic. Three machine learning models (Random Forest, Gradient Boosting Decison Tree, and eXtreme Gradient Boosting) using multi-scenario classification and a linear regression model were each adapted to perform short-term prediction of Chl-a concentration. The multi-scenario partitioning strategy proposed in this study substantially optimized model prediction performance. Factor interaction scenario partitioning yielded the best prediction results, with an overall RMSE(Root mean square error) prediction average of 0.0045, improving prediction accuracy by 4.26% compared to that of the unpartitioned scenarios. Overall improvement in prediction accuracy from diurnal and nocturnal scenario partitioning was limited. Its overall RMSE prediction average was 0.00474, improving prediction accuracy by 0.9%. In eutrophic scenario, the four prediction models (RF, GBDT, XGBoost, and linear regression) exhibited respective RMSEs of 0.0034, 0.0036, 0.0035, and 0.0039, with RF model giving the highest prediction accuracy. In summary, we propose an innovative short-term prediction model to improve the accuracy of low Chl-a concentration predictions in complex situations, providing a new paradigm for intelligent modeling and precise governance. The data obtained using a multi-scenario delineation system revealed the dynamic coupling mechanisms between the diurnal biological rhythms in a water body, nutrient grading, and the interaction of water quality factors. The idea of this study effectively solves the problem that the traditional prediction model can not meet the current prediction needs. This study can provide a systematic analysis for the prediction of cyanobacterial bloom, and can provide technical reference and theoretical support for the multi scenario prediction of Chl-a concentration.This study not only clarified the driving law of Chla concentration change under different scenarios, but also promoted the transformation of simplifying the analysis of complex problems of water environment, providing a new perspective for the mechanism research of complex water environment system.

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.

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.

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.