Virtual cities and their built environments play a significant role in video games. Understanding their interactions with physical spaces and considering appropriate planning responses to this interaction are crucial for advancing digital twin technology and urban development in the digital age. Through qualitative and quantitative analyses of representative games such as Black Myth: Wukong, Genshin Impact, and SimCity, this study identifies a cyclical four-stage interaction pathway: (1) Perception: extraction of cultural symbols, (2) Re-organization: gaming-driven reconstruction, (3) Re-understanding: virtual urban areas understanding, and (4) Feedback: real-world application. Perception and Re-organization highlight that virtual space design does not merely replicate real-world spatial characteristics, but rather reorganizes them according to specific aesthetic and functional principles, thereby operationalizing Kevin Lynch's Image of the City theory. This design process is reflected in form and function perspectives. From a form-based perspective, games such as Genshin Impact exemplify how spatial distribution heterogeneity is evident, even in virtual environments. For example, an analysis of the in-game item distribution using the ht-index (value = 5) and log-log plots indicates that although the upper tail approximates a straight line, the lower tail exhibits a rapid decline, suggesting structured spatial heterogeneity. Similarly, a comparative analysis of Florence in video games versus its real-world counterpart supports the idea that virtual spaces selectively reinterpret, rather than mirror physical environments. From a functional perspective, city-building games, such as SimCity and Emperor: Rise of the Middle Kingdom, deconstruct cities into core elements (housing, industry, service facilities, geographic surroundings, and natural resources) and integrate these components through distinct game mechanics. Re-understanding and Feedback emphasize the influence of virtual cities on urban planning education and tourism. In particular, city-building games have a substantial, yet often underestimated, impact on urban planning practices, public participation, and collaborative projects. By lowering the knowledge barriers associated with professional urban planning, virtual cities offer an accessible platform for the public to engage with urban dynamics and foster a more informed and participatory planning approach. Similarly, video games significantly shape place perception in tourism. The immersive experiences provided by virtual cities can inspire players to visit real-world counterparts of game locations, resulting in phenomena such as 'anime pilgrimages.' Notable examples include the Fate series in Japan and the recent Black Myth: Wukong in China, both of which stimulated tourism by reinforcing place attachment through interactive storytelling and visual aesthetics. Based on this interaction pathway, we propose two planning recommendations. First, fostering interdisciplinary collaboration between urban planners, architectural scholars, and game designers can facilitate the dissemination of architectural and urban cultures on digital platforms. Second, leveraging the interactive and participatory nature of video games can enhance the public's understanding of urban systems, paving the way for game-based participatory planning and promoting multi-stakeholder engagement in urban development. This study contributes to emerging theoretical frameworks such as Digital Twins by elucidating the bidirectional relationship between physical and virtual urban spaces, thereby offering new insights into the evolving role of digital environments in shaping real-world urban experiences.

As the economy and culture evolve, and as residents increasingly value the relationship between parents and children, parent-child tourism has emerged as a significant component of the tourism industry. Parent-child travel groups such as parents, children, mothers, and children are becoming increasingly common. However, there is limited literature on the spatial flow of parent-child tourism from the perspective of geography; in particular, research on the differences in the network structure of parent-child tourism flows of different group types is relatively scarce. This study focusses on Chengdu, Sichuan Province, employing Complex Network Analysis, Geo-detectors, and additional methodologies to examine the structural characteristics of parent-child tourism flow networks across various demographic groups, including parents with children, mothers with children, fathers with children, and three-generation peers. It further investigates the factors influencing the network structure of parent-child tourism flows among these distinct group types. The study found that: (1) The parent-child tourism flow network of different group types has a significant hierarchical nature, and the parent-child tourism flow network is controlled by a small number of dominant nodes, such as Wuhou Temple, Jinli, and Kuanzhai Alley. Parent-child tourism groups have a strong preference for dominant nodes, among which the performance of the "father + child" tourism group is particularly obvious. (2) The parent-child tourism flow network of different group types is generally relatively loose, with good network accessibility and clustering, and the characteristics of the small world are obvious. In contrast, the small world characteristics of the "parent + child" tourism flow network are the most obvious. Father and mother participate in parent-child tourism together, and their tourism behavior and decision-making are more rational, and it is easier for "parent + child" tourism to maximize the benefits of rational economic agent. (3) There is a phenomenon of community structure in the parent-child tourism flow network of different group types, which is a weak community structure. This also shows, to a certain extent, that there are limited dominant nodes in the parent-child tourism flow network in Chengdu. (4) The concentration of tourist resources and the popularity of tourism were significant factors impacting the development of parent-child tourism flow networks across various group types, with the concentration of tourism resources being the most critical. Each influencing factor has a distinct effect. The concentration of tourist resources significantly influences the "father + child" tourism flow network, while the popularity of tourism predominantly affects the "parent + child" tourism flow network. Finally, this study proposes suggestions for building a diversified parent-child tourism route system, creating a parent-child tourism agglomeration area, and expanding the space and market scale of father and child tourism. At the theoretical level, this research enriches the research content and perspective of parent-child tourism flows and compensates for the one-sided nature of the existing research, overlooking the parent-child tourism flows of different group types. This study provides a useful and practical reference for the construction and management of parent-child tourism destinations and guidance for promoting the healthy growth of children.

With the advancement of the "Belt and Road" initiative, China's investment in Africa has increased steadily in recent years, and trade volume has expanded continuously. However, due to the frequent occurrence of armed conflicts in Africa, the security of China's overseas interests in the region has become an increasingly prominent issue. Based on the Armed Conflict Location & Event Data Project (ACLED), this paper employs research methods such as kernel density analysis, hotspot analysis, and multi-distance spatial clustering analysis to explore the spatiotemporal evolution trends of armed conflict events in Africa from 1997 to 2024, as well as their risk impact on China's overseas interests. The analysis reveals several important results: 1) At present, armed conflicts in Africa are mainly concentrated in regions such as Sudan, Kenya, Somalia, Nigeria, Burkina Faso, the eastern Democratic Republic of Congo (DRC), Morocco, and Tunisia, forming a pattern of multiple points of occurrence. In terms of organizational structure, the main driving forces behind these armed conflicts are armed opposition groups, terrorist organizations, and militia groups. Underlying factors such as ethnic differences, religious divisions, conflicts between farmers and herders, and competition for resources are the fundamental causes of these conflicts. 2) From 1997 to 2024, the spatial distribution of China's direct investment stock in Africa shows a transition from a "multi-point dispersed" pattern to a "relatively concentrated" one. Southern Africa, being distant from the core areas of conflict, is the most stable region for China's investment in Africa. In contrast, the escalating conflict situations in East, West, Central, and North Africa have gradually worsened the investment environment, leading to the continuous expansion of China's investment cold spots and revealing a clear tendency to avoid conflict-affected areas.3) Before 2011, armed conflict events in Africa involving China were relatively rare. However, since 2011, the number of such incidents has increased significantly. From a spatial perspective, the clustering of armed conflicts involving China has gradually intensified, with these clusters emerging in regions that were already severely affected by armed conflicts.In hotspot investment countries such as the Democratic Republic of Congo (DRC), Kenya, Burundi, Somalia, and Uganda, armed conflicts have become a significant threat to China's overseas interests. Although China's investment scale in conflict-stricken areas such as Nigeria, Sudan, the Central African Republic, and Ethiopia is limited, the severe conflict situation in these regions still poses significant security risks. In the long term, if conflicts in Africa are not controlled effectively, China's investment confidence will be undermined, leading to a reduction in overseas expansion, delays in projects, and hindrance of the high-quality advancement of the "Belt and Road" strategy. This paper systematically analyzes the impact of armed conflicts on China's investment in Africa, revealing the change trend of investment layout from high-risk areas to more stable and secure regions, thus filling a gap in research on the relationship between investment security and conflicts. Furthermore, by delving into the risk characteristics of conflict events involving China's interests, this study not only provides an in-depth analysis of these risks but also proposes targeted policy recommendations, offering both theoretical support and practical guidance for mitigating the adverse effects of armed conflicts on China's overseas interests. These findings provide new perspectives for future research and offer practical references for China's investment decision-making and risk management in Africa.

In the context of an accelerating society, young individuals in contemporary cities face mounting psychological pressures and existential anxiety. This has led to an increasing demand for environments that offer therapeutic relief and emotional refuge. This study takes the "Time-Farm," an urban green space, as a case study to explore the construction of urban therapeutic landscapes, the perception of young individuals, and the ontological and epistemological foundations of healing. Drawing on Tim Ingold's dwelling perspective, this study examines epistemologies of human-nature relations, embodied and enmined practices, and the temporality of landscapes to propose a multidimensional analytical framework. This framework serves to interpret how landscapes can be healing for youth and offers a new explanatory approach for reconstructing subjectivity in an accelerated society. The findings suggest that therapeutic landscapes are not simply the result of static natural environments but are co-constructed through a relational epistemology that views human and non-human life as interdependent, cohabiting participants. In the Time-Farm, the therapeutic effect of space emerges from its founders' intentional rejection of anthropocentrism. Plants are not regarded as decorative objects but as co-dwelling beings with agency. Through sustained interaction and affective care, caregivers' non-representational practices fostered a shared coexistence epistemology that resonated with urban youths. As youth began to participate in the maintenance and experience of the space, their involvement signaled bodily engagement and an epistemic transformation: therapeutic feeling required the recognition of human–nature interdependence. This shift in understanding is a necessary precondition of ecological connections and emotional resonance. Moreover, the therapeutic process is deeply embedded in the convergence of embodied and enmined practices and temporal rhythms of the landscape. The young participants engaged in sensory-rich, emotionally resonant activities that activated bodily awareness and relational connections to a place. The therapeutic effect does not occur as an immediate experience but rather unfolds over time through repeated interactions, seasonal cycles, and the slow growth of living organisms. The temporality of the landscape mirrors the rhythms of individual transformations and supports sustained therapeutic effects. Theoretically, this study challenges the reductive paradigm that equates therapeutic effects solely with environmental conditions. Instead, it proposes a relational and procedural approach integrating epistemology, embodiment, and temporality. By employing Ingold's dwelling perspective, this study provides an interpretive tool rooted in environmental anthropology for understanding therapeutic landscapes. Practically, it offers insights for designing urban green spaces: therapeutic environments must move beyond the mere presence of greenery to foster relational understanding, embodied participation, and long-term interaction.As an urban green space, the Time-Farm demonstrates how therapeutic landscapes can be cultivated through cohabitative epistemology, integrated mind-body practices, and sustained care. The model of a "human-environment-life community" provides an ecologically holistic perspective on landscape-making and offers a fertile direction for theoretical innovation in future therapeutic landscape research.

Coastal sandy landforms, shaped by complex interactions among marine, atmospheric, and terrestrial systems, are ecologically sensitive yet underutilized tourism resources. Although considerable progress has been made in assessing tourism development potential in inland desert regions, current evaluation frameworks fail to capture the unique landscape features, ecological functions, and spatial constraints of coastal sandy environments. To address this gap, this present study constructed a multidimensional and adaptive evaluation system tailored to the characteristics of coastal sandy areas, using Pingtan Island in Fujian Province, China, as a case study, comprising three primary dimensions: resource element value, resource environmental condition, and resource development condition, and 25 evaluation indicators. Indicator weights were determined using a combined Delphi-analytic hierarchy process approach, ensuring expert consensus and logical consistency. To address the heterogeneity of data types and uncertainty in qualitative judgments, a fuzzy comprehensive evaluation method was employed, integrating quantitative indicators (shoreline length, dune diversity, air and water quality) and qualitative metrics (cultural value, recreational suitability, service level) obtained through remote sensing, field surveys, and public perception questionnaires. Empirical analysis of five typical coastal segments—Tannan Bay, Changjiang Ao, Liushui Town, Shanqi Ao, and Baiquan Mountain—yielded the following key results: 1) Among the three dimensions, the resource element value played a dominant role (weight = 0.6209), confirming its decisive influence on tourism suitability and spatial differentiation of development potential. 2) Tannan Bay and Changjiang Ao were rated as top-tier development zones because of their large sandy areas, diverse dune types, and high beach comfort levels. Liushui Town and Shanqi Ao were classified as medium-potential zones (third level), limited by either a small sandy scale or single landscape structure. Baiquan Mountain, characterized by weak resource endowment and minimal infrastructure, was rated as low-potential (fourth level). Several substantial contributions were made in this study. Theoretically, the applicability of tourism resource evaluation models to coastal sandy contexts was expanded, establishing a regionally adaptable framework. Methodologically, expert judgment was integrated with fuzzy logic to capture multisource and multiscale information, thereby accommodating both environmental sensitivity and development feasibility. Practically, a decision-support tool for zoning, investment prioritization, and policy guidance in ecologically fragile coastal zones was established. Future research should extend validation of the model across diverse coastal geomorphic types and incorporate emerging technologies, such as big-data analytics and machine learning, to improve the spatiotemporal precision and decision-making capacity of tourism development assessments.

As psychological research has expanded, the hegemony of vision in landscape studies has become increasingly challenging. As the second most critical sensory system after vision, sound has emerged as a key focus of theoretical inquiry. This paper focuses on individuals who have left their rural hometowns (hometown leavers) and used their auditory experiences as an analytical context. Drawing on in-depth interviews and using qualitative research methods such as coding analysis and semiotics, we uncovered the Xiangchou signification system of rural soundscape symbols and their operational mechanisms. We found that the perception of rural soundscapes by hometown-leavers followed a four-stage cognitive model: experience accumulation, representamen triggering, symbol reception and recognition, and meaning interpretation. First, the rural life experiences of hometown leavers formed the foundational prerequisites for awakening their perceptions of Xiangchou-related soundscape symbols. Their accumulated rural upbringing, inherited memories, and other lived rural experiences endowed them with a heightened sensitivity to sound symbols, which enabled seamless perception and reception. Second, during the symbolization of the Xiangchou soundscape, the perceptual trigger for the subject played an equally vital role. The activation and interpretation of sound symbols requires specific triggers. When respondents encounter sounds from their past, the unique timbre, pitch, or loudness of these sounds manifested as representamina, which overlapped with the imagined rural sound symbols stored in their minds. This overlap evoked a vivid sense of "as if it was yesterday," which propelled the symbolization process forward. Third, within the traditional village spaces etched in the memories of hometown leavers, complex sound symbols intertwined to form a distinct rural soundscape system composed of animal calls, natural noises, and sounds of human activity. These concrete sounds in the physical world acted as triggers to bridge the spatiotemporal divide between the soundscape symbols accumulated in the subjects' rural memory, stirring a rich array of rural recollections. Fourth, soundscapes characterized by greater abstractness and associativity focus on awakening and engaging the auditory culture. Through cognitive processing, the subjects transcended mere auditory perception to form interpretive meanings, which elevated the auditory experiences of hometown leavers to the emotional realm of rural sentiments via specific sounds. Following reception and recognition, the meanings of these soundscape symbols gradually solidified and assumed symbolic weight. Receivers with rural experiences endowed sound symbols with interpretive intent, mirroring them into four categories of Xiangchou soundscape units: sentimental attachment, pastoral leisure, rustic amusement, and seasonal busyness, thereby generating emotional resonances such as nostalgia, relief from pressure, longing for the future, and a sense of belonging. Compared with visual landscapes, soundscapes have greater penetrative power, significantly deepening the sense of belonging and identity of the hometown leavers toward their rural roots. This indicates that, during modernization, the eroded intimate connections between people can find psychological compensatory fulfillment through Xiangchou soundscapes. Xiangchou sound symbols allowed the hometown leavers to project their perceptions of their past rural life based on their unique auditory cultural field. Amid fast-paced urban life, their wandering souls were temporarily disengaged, healed, and comforted, thereby achieving a brief return to their spiritual haven through sound. The seasonal busyness soundscape centers on land as its core symbol, carrying the emotional memories and cultural totems of hometown leavers and acting as a spiritual bond for identity affirmation and the reconstruction of belonging. The rustic amusement soundscape, which has childhood games and local rituals as its symbolic anchors, awakened joyful memories and cultural identity, which became an emotional solace for hometown leavers navigating spiritual displacement.

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.

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

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

With the rapid development of urban regionalization and networking of high-speed transport, intercity travel has increasingly played a key role in China's economic and social development and socioeconomic functional connections. However, amidst global change and uncertainty, the event disturbance-oriented theory and empirical research on intercity travel is still insufficient to improve the ability of transportation systems to cope with disturbances. Since uncertainty is prevalent in transport operations, improving intercity travel behavior resilience (ITBR) and grasping the spatiotemporal pattern of demand-side intercity travel fluctuation to restrain risk is essential for resilient transport construction. Based on related theories and analysis methods of spatial interaction and intercity travel, this study refines the definition of ITBR. A measurement model of ITBR was constructed based on long-term intercity travel data and the general properties of disturbance events. Furthermore, COVID-19 disturbance was used as a case study to reveal the adaptive pattern of intercity travel and the spatiotemporal pattern of ITBR over three years. The results show that the evaluation of ITBR based on seasonal and holiday trends reveal spatiotemporal patterns of intercity travel fluctuations influenced by disturbance events. The impact of the COVID-19 pandemic on intercity travel is as follows: peak of the national pandemic > peak of the Omicron variant > peak of the multipoint fluctuation. The intensity of intercity travel decreased linearly with an increase in distance, and intercity travel during the three stages is lost by 0.86, 1.03, 1.15 percentage points, respectively, with an increase of 50 km. The average intercity travel distances of residents in these three stages were shortened by 52.55 km, 65.31 km, and 105.16 km, respectively. The value of ITBR decreased from the multipoint fluctuation period to the national pandemic period because of the Omicron outbreak. Overall, ITBR showed a gradual increasing trend during the study period. Meanwhile, ITBR in these three stages was characterized by obvious spatial differentiation and regional agglomeration. Compared to existing research, this study further expands existing research focusing on intra-city travel behavior resilience by exploring ITBR on the regional scale.

The construction and development of the metro have reshaped the activity spaces of residents and provided them with abundant opportunities to access various resources. However, existing literature often overlooks the impact of increased access to resources due to the metro system on housing prices. This study, based on residential transaction data from 2017 to 2019 obtained from Beike and metro line and station data from Chengdu, employed network analysis to define a 15-minute activity space for 56,999 residential samples in 2,609 neighborhoods around metro stations, serving as the basis for decomposing resource allocation. Subsequently, an XGBoost model was developed to explore the nonlinear impacts of accessibility and resource allocation at the neighborhood and cross-regional levels on housing prices. The results show that 1) the closeness centrality of the nearest metro station primarily affected housing prices. 2) Additionally, the relative importance of resource allocation on housing prices at the neighborhood and cross-regional levels was 34.60% and 19.55%, respectively, highlighting the significance of resource allocation at the cross-regional level. The development of the metro has reshaped residents' activity spaces, increasing access to various resources. The value of resources obtained through the metro has significantly affected residents' willingness to pay. Furthermore, resource allocation at the two levels reflected a different impact on housing prices. At the neighborhood level, the relative importance of factories and comprehensive hospital facilities was 8.02% and 7.47%, respectively. Meanwhile, the relative importance of parks and comprehensive hospital facilities were 4.85% and 3.86%, respectively, at the cross-regional level. 3) The relationship between accessibility, resource allocation characteristics, and housing prices is complex and nonlinear. Regarding accessibility, the travel time to the nearest metro station and housing prices exhibited a roughly U-shaped relationship, whereas the closeness centrality of the nearest metro station positively affected housing prices. In terms of resource allocation characteristics, different facilities had varying degrees of impact on housing prices at the neighborhood and cross-regional levels. Specifically, parks and primary and secondary schools at the neighborhood level showed an overall positive impact on housing prices, while factories, comprehensive hospitals, and shopping services at the neighborhood level generally suppressed housing prices. Additionally, business and financial service facilities at the neighborhood level showed an inverted U-shaped relationship with housing prices. At the cross-regional level, comprehensive hospital facilities and primary and secondary school facilities had opposite effects on housing prices compared to park facilities and shopping services. The impact of factories at the cross-regional level on housing prices was unstable. Business and financial service facilities at the cross-regional level demonstrated an inverted U-shaped relationship with housing prices, with a suppressive effect when the count of these facilities exceeded 423. The study findings provide valuable insights into sustainable metro development and rational resource allocation.

Livelihood capital is the core element of sustainable livelihood development for rural households. Based on the survey data of 615 growers in the main rubber-producing areas of Hainan and Yunnan province, this paper constructs an evaluation system of rubber growers' livelihood capital within the sustainable livelihood analysis framework and calculates key indicators, such as farmers' livelihood capital index, livelihood activity diversity index, and household income diversity index. The multiple regression model and the mediating effect model are used to explore the influence mechanism of livelihood capital on the sustainable livelihood of rural households. The following three conclusions are drawn: (1) The accumulation of livelihood capital of rural households is conducive to enriching the structure of household livelihood activities and income sources, especially the accumulation of financial capital, which is more likely to improve the diversity of household livelihood activities. Regional differences exist in the impact of livelihood capital structures on rural household livelihood outcomes. Natural capital endowment has a significant effect on the income diversification level in Hainan, but there may be a "curse" effect in Yunnan. (2) Geographical characteristics, production decisions, and farming household characteristics significantly impact sustainable livelihoods. The altitude of the village and the distance from the county seat pose certain challenges for farmers in diversifying their livelihoods. Although the law of rubber tapping production may weaken farmers' production and business activities, it can better stabilize farmers' incomes owing to its strong flexibility in labor arrangements, which may be beneficial for diversifying livelihoods; however, it does not necessarily lead to diversified incomes. While the characteristics of poor households can help rural households gain policy support, building capacity is the key to achieving a sustainable livelihood. (3) There are intermediary effects of livelihood capital on livelihood activities and household income, but the mechanisms of action are different. For the diversity of farmers' livelihoods, 52.70% of the catalytic effect of livelihood capital is achieved by improving the ability to integrate livelihood capital. Optimizing household employment strategies contributed to the promotion of livelihood capital on the income diversification index, with a mediating effect of 30.52%. The main contribution of this study is to clarify how livelihood capital can achieve the goal of diversifying household livelihood activities and income by coordinating livelihood capacity and employment strategies. Therefore, to enhance the comprehensive livelihood capacity of rural households, the coordination capacity of livelihood capital, livelihood capacity building should be enhanced, and employment information channels should be expanded.

As the final layer for precipitation interception in forests, the litter layer is crucial to the vertical structure of forest ecosystems, situated between the forest vegetation and soil layers. Exploring the litter accumulation and water retention characteristics in different tropical rainforest stands is essential for assessing their water conservation functions. This study focused on three forest stands (primary forest, secondary forest, and rubber plantation) within Qixianling Hot Springs National Forest Park in Hainan, China. The immersion method was used to measure litter accumulation and water retention characteristics, exploring variations among these forest stands. Results revealed (1) significant differences in litter accumulation among the stands, with the primary forest having the highest litter accumulation (2.791 t/hm²), followed by the secondary forest (2.077 t/hm²) and rubber plantation (1.660 t/hm²). Litter moisture content followed the order: primary forest (57.57%) > secondary forest (48.33%) > rubber plantation (46.44%). (2) Regarding water retention and water retention rate, both primary and secondary forests showed an increasing trend with immersion time, with the primary forest exhibiting higher water retention and retention rates than the secondary forest. In contrast, rubber plantations showed no clear trends in water retention or retention rates over time. The relation between litter water absorption rate and immersion time followed a well-fitted power function. The maximum water retention capacities were in the order of primary forest (8.041 t/hm²) > secondary forest (6.251 t/hm²) > rubber plantation (4.896 t/hm²). (3) In terms of water absorption and water loss rates, the rubber plantation had the highest water loss rate, followed by the secondary forest and the primary forest. The maximum water loss was observed in the primary forest (5.225 t/hm²) > secondary forest (4.626 t/hm²) > rubber plantation (4.079 t/hm²), and the maximum water loss rates followed the order: rubber plantation (246.319%) > secondary forest (222.649%) > primary forest (189.748%). The forest litter layer's water retention capacity and storage are closely related, with larger litter reserves correlating with greater water retention. Therefore, among the three forest types, the maximum and effective water interception capacities exhibited the following trend: primary forest > secondary forest > rubber plantation. The maximum and effective interception rates show the pattern: primary forests ≈ rubber plantations > secondary forests. The water conservation function of litter is reflected in its water retention capacity and rate of water loss. Given that primary forests exhibit a higher water retention capacity and lower water loss rates, litter accumulation in primary forests is more conducive to forest water conservation functions. Hence, future efforts should focus on protecting litter from primary forests. Conversely, the litter in rubber plantations tends to have a higher rate of water loss, resulting in poorer water conservation. Therefore, future considerations should include planting understory vegetation in rubber plantations to enhance litter water-conservation capabilities and prevent soil erosion. These findings provide crucial theoretical guidance for forest management and the enhancement of water conservation in tropical regions.

Small tourism enterprises are pivotal in the development and evolution of the spatial dynamics of scenic tourism and are the principal contributors to tourism services and experiences. They constitute a tangible base and medium for developing tourism in scenic areas. However, amidst the challenges of the tourism crisis and disaster management, there is a noticeable deficiency in the theoretical focus and case study analysis concerning small tourism enterprises. This study delves into the effects of the COVID-19 pandemic on the tourism industry and its associated sectors. It emphasizes small tourism enterprises in the Xijiang Qianhu Miao Village scenic region, drawing from case observations and field research alongside comprehensive interviews to gather authentic data. This study utilizes the proceduralized grounded theory to elucidate the inherent principles and mechanisms behind the organizational resilience of small tourism enterprises facing the pandemic's impacts. Additionally, it pinpoints the critical elements influencing the development of organizational resilience in these enterprises. The findings reveal the following: 1) The interplay between organizational capabilities and influential factors collectively elucidates the genesis and robustness of organizational resilience among small tourism enterprises in scenic areas, with resilience emerging and intensifying through the synergistic influence of internal and external organizational elements. 2) Organizational capabilities represent the intrinsic rationale and conceptual framework underlying the development of organizational resilience in small tourism enterprises. Such resilient organizations exhibit fundamental abilities such as environmental observation, impact forecasting, crisis response, and reflective learning. In essence, small tourism enterprises adapt by monitoring and recognizing shifts in the external milieu, predicting the duration and ramifications of the pandemic, and crafting proactive strategies in response to pandemic-induced challenges based on external changes and internal shortcomings. Throughout the pandemic, new insights were assimilated into the operational and developmental strategies of small tourism enterprises through ongoing reflection, summarization, and learning. Prompt adaptations in business approaches contributed significantly to cultivating and reinforcing organizational resilience. 3) Initial resources, social capital, and support initiatives foster organizational resilience among small tourism enterprises in scenic locales. These components are crucial for ensuring organizational survival, enhancing resilience potential, and sculpting organizational resilience. Specifically, foundational resources such as property ownership, operator expertise and skills, and surplus funds are vital for building organizational resilience during a pandemic. Concurrently, the relational networks between small tourism enterprises and their stakeholders, alongside social capital stemming from operators' power dynamics and identity within the tourism context, markedly strengthen organizational resilience. Furthermore, tourism relief policies and interventions that modify tourist influx and business sustainability within scenic areas play a pivotal role in enhancing the resilience of small tourism enterprises. This study broadens the theoretical understanding based on case studies of organizational resilience in small tourism enterprises amid the pandemic. It offers theoretical insights and practical guidance for the ongoing management and adaptive regulation of these enterprises during tourism-related crises and disaster management scenarios.

River hydraulic engineering plays a substantial role in maintaining the water-energy-food-economy nexus and coping with climate change. The co-construction of carbon peaking, carbon neutrality goals, and ecological civilization presents new demands for the development of river hydraulic engineering. Building upon an overview of the development of river hydraulic engineering, particular attention has been paid to its impact on the carbon cycle process. A review of the research on carbon cycling indicates that the carbon cycle of river hydraulic engineering is primarily influenced by geographical location, project scale, and operational management, whereas the evaluation results of carbon balance are significantly affected by differences in calculation methods, evaluation systems, and data discrepancies. Analysis of the carbon balance of reservoirs nationwide also revealed that China's reservoir CO₂ flux was slightly higher than the world average, whereas the CH₄ flux was lower. The total carbon storage in reservoir sediments in China is approximately 2.103 billion tons, rising at a rate of 76 million tons per year. Estimation results of carbon emissions reduction in hydropower projects indicate that water conservancy projects have significant functional benefits and demonstrate a noticeable "carbon sink" effect on the energy structure. Assuming that hydropower is entirely replaced by thermal power, hydropower reduces approximately 3,984 Tg (CO_2eq)/a of carbon emissions from the power system, of which small hydropower accounts for approximately 6%. This study also explored policy-oriented issues in the development of river hydraulic engineering, assisting in elucidating the challenges and demands faced by river hydraulic engineering during the period of multi-objective co-construction. These challenges include balancing ecological friendliness to enhance carbon sequestration, ensuring food security, harnessing water resources for economic purposes, maintaining policy continuity, and increasing government credibility. Recommendations for the future include ensuring policy continuity, deepening research on enhancing data sharing, conducting fundamental research, and strengthening multiscale integrated systematic studies. It is necessary to establish a unified carbon balance evaluation system, conduct in-depth research on process-based mechanisms and cumulative effects, and explore the synergy between research, application, and policy development. These efforts will actively promote the innovative development of river hydraulic engineering within the context of ecological civilization construction and the achievement of the "dual carbon goals".

Accelerated development of modern society has harmed people's physical and mental health. It has become a trend to achieve physical recovery and spiritual reshaping through the deceleration of tourism. However, further research is required to understand how consumers experience and realize time deceleration in the context of tourism. In this study, Lijiang acient town, which has the unique charm of a slow-living experience in the eyes of tourists, was selected as the case study, and the text materials of online travel notes and interviews were used. The coding method of grounded theory was adopted to analyze the connotation and occurrence mechanism of the slow-living experience. The results were as follows: 1) The slow-living experience of ancient town tourism is an immersive experience in which tourists visit the tourist destination of the ancient town and enjoy the passage of time under the influence of spiritual arousal of relief needs, memory, and emotion. 2) Time practice, space practice, and adding meaning to life are the main ways of a slow-living experience, which run through the entire process of tourists' slow-living on-site experiences. 3) The slow-living experience of ancient town tourism includes four stages: spiritual arousal, state relaxation, life immersion, and value realization. Each stage is interconnected and promotes the realization of tourists' deceleration experiences. The theoretical value of this study is that through the explanation of the slow-living experience model, the occurrence mechanism of tourists' slow-living experience was discussed in detail, and the core proposition of how tourists experience and realize deceleration was answered. Among them, the slow-living experience emphasizes the drive of spiritual arousal, relaxation of physical and mental states, immersion in life at the time and space levels, and sublimation of leisure value. This realization process differs from other types of tourism experiences. In addition, this article emphasizes that time practice, space practice, and adding meaning to life can create leisure value, emotional value, and a spiritual sense for tourists' time use and promote the depth of tourists' slow-living on-site experience. The research conclusions provide guidance for tourism development of ancient town tourism. Ancient town tourism operators should focus on tourists and formulate targeted programmes according to their behavioral trends. However, the extensibility of slow-living experiences should be considered comprehensively. Operators should consider the influence of other tourist destination landscapes on the slow-living experience, pay attention to the correlation between the two, create a relaxed and lazy slow-living atmosphere for tourist destinations, and stimulate tourists' environmental awareness. This can provide tourists with an excellent slow-living experience and promote the sustainable development of tourist destinations. Overall, starting from the micro level of tourists, this study constructed a slow-living experience model in the context of ancient town tourism, providing a new perspective and practical guidance for a deeper understanding of tourists' experiences.

Traditional village culture is an important part of rural culture as well as a precious heritage and historical memory of the Chinese nation, and its effective inheritance and sustainable development have attracted much attention. However, traditional village culture is often in a disadvantaged position in the process of urban-rural cultural exchanges, and the cultural adaptation problem of traditional village residents creates difficulties for the integration of urban-rural culture and the development of traditional cultural inheritance in China. In the context of traditional village conservation and tourism development, the cultural adaptation of traditional village residents is related to the resolution of the contradiction among traditional village development and conservation, the realization of the residents' good life, and the realization of the creative transformation and innovative development of traditional culture. Based on the literature on cultural adaptation, case summaries, and long-term field research experiences, this study clarifies the practical objectives of the cultural adaptation of tourism-driven traditional village residents, refines the process mechanism of their cultural adaptation by combining dimensions and processes, and explores the integration path of cultural adaptation based on positive psychology. The results show that first, the process mechanism of cultural adaptation of the residents of tourism-driven traditional villages can be investigated by combining the context of the evolution of urban-rural relationships in China and the U-curve theory of cultural adaptation. During the period of foreign culture entry, residents' external actions are actively cooperative, although their internal perceptions show foreign culture biases and development opportunity expectations. During the period of cultural clash and adjustment, conflicts and contradictions in daily life and behavioral expressions of residents are frequent, causing negative internal psychological emotions and cultural assimilation. The goal of the cultural integration period is that after a series of conflicts, residents will actively cooperate in their external behavior, and will be able to pass on their culture and seek progress. In terms of internal perceptions, residents will have increased psychological satisfaction, cultural confidence, and positive and open cultural perceptions. Further, borrowing from the research concept of positive psychology, we created a positive social organization system with three aspects: government macro-control, coordination of multiple groups, and a preventive supervision mechanism; a positive personality trait system with three aspects: cross-cultural interaction skills, ownership concept, and flexible and open cultural cognition; and a positive emotional experience system with three aspects: cultural identity, positive gaze of visitors, and community care. Based on the above systems, corresponding countermeasures to be taken at different stages of the cultural adaptation process are proposed to construct an integrated path of cultural adaptation for residents of traditional villages. This study explores the process mechanism and integration path of cultural adaptation of traditional village residents to deepen the interactive logic of locality and cultural adaptation, and provides a scientific reference for community governance and conservation practices in traditional villages, supporting traditional village locality protection and urban-rural integration.

As an emerging form of accommodation in the leisure and vacation era, the relation marketing of homestays is an important factor in promoting a good relation between hosts and guests and stimulating the citizenship behavior of customers. Customer citizenship behavior is necessary to enhance the customer travel experience and promote the high-quality development of the homestay industry. Stimulating customer citizenship through relation marketing is an important scientific issue that needs to be addressed for the high-quality development of homestays. Based on social exchange theory and attribution theory, this study analyzes the relation between homestay staff and customers and refines the two-dimensional structure of homestay customer citizenship behavior, confirming the mediating effect of relation quality on the influence of relation marketing on helping behavior and deepening the understanding of the moderating effect of motivational attribution on the influence of relation marketing on customer citizenship behavior. The influence mechanism of customer citizenship behavior was clarified. The research results show that customer citizenship behavior in the homestay context consists of two dimensions: helping behavior and tolerant behavior, indicating that the structure of customer citizenship behavior in different contexts is still different. Second, the main effects of relation marketing on relation quality and customer citizenship behavior are significant. That is, a homestay can improve the quality of its relation with customers through instrumental behaviors, such as information communication, and emotional behaviors, such as human investment. Customer citizenship behavior is an important behavioral response to relation marketing. Third, relation quality mediates the relation between marketing and helping behavior, indicating that relation marketing promotes customer trust in homestays and understanding the reciprocity of behavior, which in turn promotes customer helping behavior. Fourth, motivational attribution has a moderating effect on the influence of relation marketing on tolerant behavior. This shows that in altruistic motive attribution, the more customers perceive relation marketing, the more they can feel the good experience brought about by homestay staff, so they voluntarily adopt tolerant behavior in the face of service failure, based on the principle of reciprocity in social exchange theory. This study combines the social exchange and attribution theories to explain the mechanism of customer citizenship behavior in the context of homestay services. While enriching the research content of high-quality development of homestay, it constructs a discourse system with more"relation" characteristics for tourism marketing, broadens the tourism application scenarios of relation marketing theory in practice, helps homestay maintain a good relation between host and client, stimulates customer citizenship behavior, and contributes to the development of homestay tourism services and products.

At the height of the national independence movements in Asia, Africa, and Latin America in the first half of the 20^th century, postcolonial thought began to emerge in Brazil, reconstructing the self-other relation between Brazil and the West. The imaginative geography of Brazil, one of the most important southern countries, is of great local and global geopolitical significance. In contrast to the general imagination centered on the West and other developed countries, Brazil has the particular imaginative geographies of another large southern country, China. One of the symbolic imaginaries of China in Brazilian scholarship is human geographer Gilberto Freyre's China Tropical, which he likens to China in Latin America. Freyre studied under American geographer and anthropologist Franz Boas, who was a vocal opponent of scientific racism. Therefore, in China Tropical, Freyre advocates for the equality of Brazilian civilization by imagining its structure, continuing Boas's thoughts, and developing a series of postcolonial critiques. This article uses Freyre and his book China Tropical and related thoughts as analysis objectives to explore Freyre's view of Brazil as a tropical China in the process of spatial othering. This study finds that Freyre constructed his postcolonial ideology of Brazil's nation-state development both geo-culturally and geopolitically by imagining Brazil's tropicality and Chineseness. Freyre's portrayal of Brazil as a third space belonging neither to the West nor the East disrupts the colonial hegemony of the discourse of a uniform and homogeneous culture between suzerain and colony and seeks the subversive power of postcolonialism through hybridity and in-betweenness. Second, Freyre conducted an analysis of the human-environment relation in cultural geography from the perspective of historical science, refuted the natural science perspective of environmental determinism, which was prevalent in Western academia at that time, and reshaped the visual balance within the framework of the human-environment relation. This is a side effect of the transformation and change in human geographical thinking. Third, Freyre's concept of tropical China is a prominent achievement in the embryonic period of postcolonial thought in Brazil as well as an important ideological foundation for contemporary Sino-Brazilian exchanges and cooperation. Freyre proposed commonalities and identities between China and Brazil in this field of thought, offering more possibilities for international cooperation beyond human- and poverty-based interactions. This article focuses on the imaginative geographies of former colonial countries, which are conducive to promoting China's understanding of Brazilian society. In addition, we believe that, in the future, Chinese scholarship should pay greater attention to small languages, such as French, Spanish, and Portuguese, which are widely spoken in the former colonial countries of Asia, Africa, and Latin America. With these small language texts at the core, we will continue to study imaginative geographies and country and area studies in Asia, Africa, and Latin America to improve the global understanding of Chinese scholarship.