In the era of the knowledge economy, talent is important for the development of any country, region, or city, and attracting foreign talent to stay and settle down has gradually become an important issue. In this study, we analyzed the spatial distribution of highly educated migrants, their willingness to settle in the place they migrated to, and the social influencing factors from the perspective of migration networks using the 2017 China Migrants Dynamic Survey. We explored the differences in the influence of inter-provincial and intra-provincial migration patterns on the willingness of migrants to settle. The main conclusions are as follows: First, the willingness of the highly educated migrants to settle down shows a distribution pattern of "high in the north and low in the south." Migrants, especially highly educated people who are willing to migrate across provinces, showed highest preference for settling down in Beijing, Shanghai, and Tianjin, whereas those willing to migrate within provinces showed preference for settling down in Tibet, Shandong, and Hubei.. Second, the friendship and kinship networks of highly educated migrants show a clear pattern of "high in the north and low in the south," and the business network shows a clear pattern of "high in the west and low in the east," and the network of township ties has a clear pattern of "high in the east and low in the west." Third, migrant networks provide material and emotional social support for the migration of highly educated individuals and significantly influence their willingness to settle. Among these networks, kinship and friendship offer the greatest support and exert the strongest pull on their migration decisions. In contrast, the influence of township ties on the willingness of highly educated migrants to settle is smaller, highlighting a clear difference from the stronger reliance of migrant workers on township ties. Fourth, highly educated intraprovincial migrants, owing to their shorter migration distances and lower migration costs, are more influenced by kinship in their willingness to settle. By contrast, highly educated inter-provincial migrants who lack kinship ties in their destination areas showed a lower willingness to settle and are more influenced by friendships and hometown connections. Future research on talent migration and policies should place greater emphasis on social factors, thereby enriching the study of talent mobility from a societal perspective. This strategy is also beneficial in practice for attracting and retaining talent, not only through economic incentives but also by leveraging social policies. This fosters the integration of talent into destination cities and contributes to the socioeconomic development of these areas, thereby propelling the implementation of a talent-driven national strategy.

As China enters a critical transition period towards a knowledge-based economy, the optimization of the educational attainment structure and spatial distribution of the civil service, a crucial component of modernizing the national governance system and capacity, exerts a profound influence on enhancing government efficiency and fostering social progress. Based on recruitment data from the 2023 Guangdong Provincial Civil Service Examination, this study employs spatial statistical methods and Multivariate Logistic Regression analysis to examine the urban hierarchy migration model of newly graduated students admitted to civil service positions and its influencing factors. The research findings indicate: (1)The migration model of admitted newly graduated students are predominantly migrate down the urban hierarchy. For non-equivalent-level migrations, destinations are mainly fourth-, third-, and first-tier cities, whereas for equivalent-level migrations, destinations are primarily fourth-, third-, and second-tier cities. (2)Among personal attributes (including gender, university ranking, and the tier of the city where the graduation school is located), except for graduates from universities in the fourth- and fifth-tier cities, all other groups predominantly migrated down the urban hierarchy. (3)In terms of work-unit level and job requirements (including educational qualifications and work experience), the admitted candidates across all groups predominantly migrated down the urban hierarchy. (4) The results of the multiple logistic regression showed that personal attributes, work-unit level, and job requirements jointly affected the choice of migration mode for admitted candidates. Personal attributes and job requirements have a relatively significant impact; the better the personal attributes and the higher the job requirements, the more likely they are to migrate up the urban hierarchy. The effect of job conditions was not significant. (5)The results of the mechanism analysis revealed that the choice of migration model among newly graduated students is a complex and dynamic decision-making process underpinned by the interplay of multiple factors, such as government policy guidance, job characteristics, personal factors, and urban conditions. The decision-making and selection process in the selection mechanism for the migration mode of newly recruited graduates in the civil service examination is complex and dynamic, involving the interaction of multiple factors, such as government policy guidance, job characteristics, personal factors, and urban conditions, with objective limitations, personal abilities and resources, and subjective willingness. Compared to other non-establishment employment models, this employment model has a stronger possibility of migrating down the urban hierarchy, which may be caused by significant differences in the sources of job settings, competition intensity, and subjective willingness. To achieve the strategic goal of building a high-quality young civil service, the government should consider the multifaceted and complex interactions within the recruitment process, leverage its administrative functions, flexibly adjust job settings, and attract and retain outstanding newly graduated students through measures such as optimizing the urban environment and enhancing public service levels. This study has significant implications for local governments in formulating scientific and reasonable civil service recruitment policies tailored to local conditions, and guiding newly graduated university students to make informed and rational decisions when applying for civil service positions.

To enhance the scientific rigor and practical relevance of disaster resilience evaluation in mountainous rural communities, this study developed a multilevel assessment framework based on the Pressure-State-Response (PSR) model by integrating the entropy method and Analytic Hierarchy Process (AHP). The framework comprised three dimensions (pressure, state, and response), nine elements, and 32 indicators tailored to the unique environmental and socioeconomic contexts of mountainous regions. Focusing on four representative communities (Taoyuan, Caogu, Niulang, and Qunying) in the Anning River Basin of Liangshan Prefecture, Sichuan Province, China, a combination of field surveys, GIS spatial analysis, and multi-source datasets were used to empirically evaluate community resilience. The key findings revealed the following: (1) The comprehensive resilience scores ranked Taoyuan > Niulang > Qunying > Caogu. Taoyuan's top performance stemmed from its designation as a national disaster prevention demonstration community featuring robust infrastructure and frequent emergency drills, whereas Caogu's lowest resilience resulted from its high-altitude topography, aging population, and inadequate infrastructure. (2) State resilience contributed most significantly to overall resilience (51.43%), with the building quality (C9) being the pivotal driver. Pressure resilience was predominantly influenced by the proximity to active faults (C2) and population exposure to geological hazards (C6), whereas response resilience relied on disaster-monitoring equipment (C26) and early warning efficiency (C27). (3) A synergistic optimization strategy was proposed, emphasizing risk zoning and engineering controls (pressure layer), housing retrofitting and social capital cultivation (state layer), and intelligent early warning systems integrated with indigenous knowledge (response layer). The study validates the applicability of the PSR model in mountainous rural contexts, highlighting a "state resilience dominance with response capacity gaps" pattern. Notably, communities with higher state resilience demonstrate stronger recovery capabilities despite elevated hazard pressures, underscoring the importance of robust infrastructure and social cohesion. Conversely, insufficient investment in monitoring technologies and external rescue coordination hinders response effectiveness in remote villages such as Caogu. The framework provides methodological support for tailored disaster-prevention planning, particularly in ethnic regions where traditional ecological knowledge complements modern governance. However, limitations include a focus on earthquakes and geological hazards, excluding concurrent multi-hazard scenarios (e.g., wildfires and pandemics), and a static assessment that overlooks temporal resilience dynamics. Future research should incorporate longitudinal monitoring and cross-scale interactions to refine the generalizability of the model. This study advances the theoretical integration of socioecological systems into resilience assessments and offers actionable insights for sustainable rural development in hazard-prone mountainous areas.

Skilled migration is a pivotal phenomenon underpinning globalization that has attracted widespread scholarly interest; a nuanced understanding of the patterns and mechanisms of skilled migration is considered essential for fostering coordinated regional development and enhancing labor market allocation. To compare the domestic and international talent mobility research in the 21^st century and advance China's talent mobility theory, In this paper, we reviewed Chinese and English literature from fields such as geography, urban planning, demography, economics, and management since 2000 via quantitative and qualitative analysis. Initially, we conducted bibliometric and keyword co-occurrence analyses using CiteSpace to identify research hotspots and trends; subsequently, we performed Qualitative Data Analysis Miner qualitative analysis as a supplementary approach to derive in-depth insights and determine connections between literature sources. Herein, we summarize the research hotspots regarding skilled migration, domestically and internationally. We found that concerning research hotpots, domestic research emphasizes the spatial distribution of different types of talent, the impact of urban factors on skilled migration, and the interplay between talent and urban innovation. In contrast, international research emphasizes more on the mobility decisions of highly skilled migrants within a globalization context, focusing on the impact of international high-skilled migration on the destination and origin countries, the micro-level mechanisms of migration decision-making (such as family dynamics, gender roles, and early career stages), and social adaptation in destination countries (including identity, sense of belonging, and related factors). Theoretically, both domestic and international studies are based on labor migration theory, examining skilled migration mechanisms from macro-regional and micro-individual perspectives, and expanding theoretical frameworks to include amenities and the creative class. However, owing to differences in social, economic, institutional, and developmental contexts among countries, these theories are not entirely applicable in practice, particularly regarding their explanatory power in the Chinese context, which requires further examination. Furthermore, in terms of research progress, we found that international studies are increasingly highlighting the life course of migrants and the socio-cultural micro-mechanisms influencing skilled migration, emphasizing the adoption of a combination of quantitative and qualitative analytical methods. Conversely, domestic research predominantly focuses on the spatial patterns of skilled migration and the effects of macro-urban factors, relying on quantitative analyses. Future research in China should aim to examine micro-mechanisms, develop indigenous theoretical frameworks to foster theoretical innovation, and enhance the integration of qualitative and quantitative methods. Moreover, exploiting the potential of big data and emerging technologies could contribute towards overcoming limitations associated with data acquisition. On the basis of our survey of current theories and methods, we propose the following four directions for future research: (1) strengthening investigations into the micro-mechanisms of skilled migration; (2) developing indigenous theoretical frameworks to support theoretical innovation in China; (3) promoting the integration of qualitative and quantitative research methods; and (4) enhancing data acquisition and exploiting big data and advanced technologies to overcome the current limitations associated with acquiring data.

In the digital economy, developing skills among women with disabilities is crucial for improving their employment opportunities and income. This study examines the Aide Training School in Yixing City, Jiangsu Province as a case study to explore skill development pathways for women with disabilities based on the empowerment theory. The integration of government, market, and social resources, enhances their expertise in traditional crafts, strengthens market competitiveness, promotes economic independence, and supports social integration. Research Methods This study employed qualitative research methods, including participatory observation and in-depth interviews. Targeted interviews were conducted with 25 participants, including women with disabilities, institution heads, and disabled artisans at the Aide Training School in Yixing City. Data related to the Training School was also collected. Using an intersectional perspective, this study draws on Sirivaddhana's (1998) three empowerment methods for women and Qian Ning's (2020 internal and external framework to analyze skill development and reemployment processes, leading to self-empowerment and identity transformation. Results and Conclusions: 1)The Aide Training School integrates government, market, and social resources, to provide comprehensive skill training and employment support for women with disabilities. This has significantly improved their proficiency in traditional crafts, such as Yixing purple sand pottery. The local cultural significance of Yixing purple sand pottery serves as "local identity capital" for women with disabilities, enhancing their market competitiveness and economic independence. 2) Skill development and re-employment transform the social identity and roles of women with disabilities. They transition from marginalized, unemployed, or low-income groups to skilled professionals with stable incomes, improving their social standing and self-perception. Additionally, they gain social recognition through the identity of "purple sand pottery culture communicators." 3) Skill development expand social participation opportunities. Through market sales, cultural exhibitions, and social services, these women build social networks, increase their influence, gain greater decision-making power, reinforcing empowerment outcomes. This study provides novel perspectives and methodologies for research on the skill development and reemployment among women with disabilities in China. Theoretically, it applies empirical case analysis to substantiate the explanatory utility of empowerment theory in elucidating the pathways and mechanisms of skill development for women with disabilities, thereby enriching the application of empowerment theory within this demographic and compensating for the previous neglect of this group within the empowerment theory. The proposed "human-land interaction empowerment" mechanism adds localized, intersectional insights to feminist geography. Practically, this research deepens the understanding of the empowerment process for women with disabilities, particularly in enhancing self-awareness, strengthening capabilities, and achieving skill development, thus providing a practical foundation for the evolution of subsequent related theories and, to some extent, advancing the career development of individuals with disabilities and providing innovative employment strategies.

Coastal cities are highly vulnerable to compound flooding in which multiple flood drivers interact via complex nonlinear mechanisms under climate change. Although numerous studies have focused on individual flood drivers, integrated analyses of the spatiotemporal variations and compound effects remain limited. This study applied a high-resolution MRI-AGCM3-2-S climate model and the TempestExtremes tracking algorithm to construct a 6-hourly Tropical Cyclone (TC) track dataset affecting Haikou from 1960 to 2099. Storm tides during the TCs were simulated using the D-Flow FM model, whereas upstream river discharges were modeled with CaMa-Flood, incorporating climate-model-derived runoff data. Using rainfall data from the climate model, we applied the peak-over-threshold method and extreme value analysis to systematically assess changes in storm tides, rainfall, and upstream discharge under climate change. These analyses guided the construction of compound flood scenarios for simulating extreme events. Using a compound flood simulation model, we assessed the hazards under 10-year and 50-year Return Periods (RPs) for historical (1960–2014) and future (2015–2099) periods. Results indicate that significant differences exist in the compound flood characteristics between historical and future periods. In the 90^th percentile scenario, all three flood drivers exhibited higher future thresholds, suggesting an increased risk of compound extreme flood events. The probability of concurrent heavy rainfall and high discharge events increased by 40.9%, whereas the probability of simultaneous high storm surge and high discharge events increased by 58.3%. Despite the potential reduction in extreme event intensity, the frequency of compounding events has increased significantly. Extreme value analysis revealed that extreme storm surges and upstream discharge events became more severe and extreme rainfall events showed a decreasing trend. For high RPs (e.g., 50-year events), the projected storm tides and upstream discharges significantly exceeded historical levels. Specifically, projected increases in storm surge levels (+0.24 m under 50-year RP) and upstream discharge (+1,271.13 m³/s) are offset by a 16.5% decline in 100-year accumulated rainfall for Haikou when compared to historical period. Third, compound flood simulations showed that under the 10-year RP scenario, the total inundation area slightly increased, but the flood volume and maximum depth decreased, indicating the stabilization of the flood hazard. However, under the 50-year RP scenario, both the inundation area and flood volume increased substantially, with the area experiencing flood depths greater than 3 m expanding by 56.5%. The most severe flooding occurred along the northern coastal areas and banks of the Nandu River, where the inundation extent and flood severity increased markedly. These findings provide valuable insights for flood risk assessments and adaptive planning in coastal cities facing intensifying climate-induced hazards.

Industry and occupation are closely interwoven. Focusing solely on industrial structure cannot adequately address regional development challenges. Multifactor cross-relatedness provides a theoretical foundation for understanding the interplay between regional industrial and occupational relatedness. This study introduces the concept of industry-occupation cross-relatedness to investigate how urban labor skills influence industrial evolution in China, while also analyzing regional and industrial heterogeneity. Specifically, we construct a city-industry panel dataset using Chinese customs import-export data (2000-2015), census data (2000 and 2010), and population sampling survey data (2005 and 2015). This dataset enables us to analyze the structural evolution of the spatial network of industry-occupation interactions. Employing a linear probability model, we examine the impact of industrial relatedness and industry–occupation cross-relatedness on industrial evolution, with a focus on regional and industrial heterogeneity. The main findings are as follows: (1) The cross-relatedness between industries and occupations in Chinese cities has increased over time. Average industrial relatedness density exhibits a significant increase, particularly in eastern regions. Cross-relatedness density shows an increase in regions with moderate cross-relatedness values but a noticeable decline in the northeastern regions. The spatial distribution of the average industrial relatedness density and industry-occupation cross-relatedness density exhibits high consistency. (2) Industry-occupation interaction drives industrial evolution in Chinese cities. A path-dependence effect is evident in industrial evolution. The synergy between industries and occupations enhances regional industrial comparative advantages. The spillover effect of locally related industries strongly supports industrial comparative advantages, second only to the influence of pre-existing industrial foundations. (3) Regional and industrial heterogeneity is notable. Regionally, the probability of previous-stage dominant industries remaining dominant decreases from east to west. Industrial path dependence also declines from east to west, while cross-relatedness has a more significant impact on forming comparative advantages in eastern regions, followed by central regions. Larger cities exhibit a higher probability of path breakthroughs through skill-relatedness. Industrial heterogeneity shows that skill structures contribute the most to the diversification of technology-intensive industries, followed by capital- and labor-intensive industries. This study also provides several policy implications. First, regions should adhere to the principles of economic and social development to formulate reasonable talent demand. Second, vocational education should undergo deeper supply-side structural reforms to better meet industry needs. Finally, cities in different regions should adopt differentiated industrial and labor policies to align with their unique contexts and development stages. Compared with previous research, the marginal contributions of this study are threefold. First, it emphasizes the critical role of human capital as a foundation for high-quality regional industrial development, offering theoretical and methodological insights for promoting employment and addressing structural employment challenges. Second, it explores the bidirectional influence of labor and industry from a multi-factor interaction perspective, advancing research integration in evolutionary economic, industrial, and labor geography. Third, by focusing on coordinated development between industries and occupations, this study provides practical insights for aligning industrial and labor policies, facilitating the deep integration of industrial and talent chains to achieve high-quality development.

The current risk assessment of single landslides and debris flow disasters ignores the increasing supply, accumulation, and superposition amplification effects of disasters from top to bottom, resulting in a serious underestimation of the risk of landslide-debris flow disaster chains. This study takes the "2010.9.21" mega-landslide debris flow disaster in the Magui River Basin in Gaozhou, western Guangdong as a case study. A landslide-debris flow disaster chain risk assessment index system, guided by the cumulative amplification effect, was established from the perspective of disaster chain initiation, transmission, and cumulative amplification. A comprehensive index model was used to scientifically evaluate the risk of the disaster chain, and actual investigation results were used for verification. The results are as follows: 1) The landslide-debris flow disaster chain in the Magui River Basin is characterized by multi-ditch collection, high impact force, and major terrain fluctuation. The landslide in the starting area is directly transformed into a debris flow during the instability process and flows into the debris flow branch ditch over a short distance. Several debris-flow branches received landslides along the path, converging into the main ditch. After potential energy accelerates through the circulation area, the flow rushes out of the ditch, leading to a large area of fan-shaped accumulations in the low- and slow-terrain areas, causing serious damage to residential houses and farmland. 2) A total of one small watershed unit carries an extremely high risk, accounting for 2.04% of the total number of small watersheds. The extremely high-risk area covers 3.64 km², accounting for 2.24% of the total area. It is mainly distributed in a small watershed east of Liutang Village. There were eight small watersheds in high-risk areas, accounting for 16.33% of the total small watershed number. The dangerous area covers an area of 20.50 km², accounting for 12.62% of the total area. Most watersheds are concentrated in Langlian Village, Shenshui Village, Makeng Village, and northern Longkeng Village in the Middle East region of Liutang Village. The number of small watersheds in the medium-risk area was 18, accounting for 36.73% of all the small watersheds, and the total area covered by dangerous area was 81.22 km², accounting for approximately 44.90% of the total study area. The medium-risk areas were widely distributed within the scope of the study, especially in the southern part of Longkeng Village, most of the small watersheds of Liutang Village, the southern part of Langlian Village, Magui Village, Chengdong Village, Gancheng Village, the central area of Daxi Village, Houyuan Village, and Shanxin Village. There were 22 small watersheds in the low-risk area, accounting for 48.98% of the total number of small watersheds. The low-risk area covers 57.07 km², accounting for 35.13% of the total study area. It is mainly distributed in the small watersheds of Shanxin Village, Houyuan Village South, Yadong Village South, and Zhoukeng Village in the northeast; Daxi Village in the west; Hemudong Village in the central region; and Longkeng Village in the south. 3) The evaluation results of this study were verified using actual investigation data, which showed high consistency with field survey results, thereby confirming the credibility of the method employed in this study. The index system and evaluation approach for the risk assessment of mass landslide-debris flow disaster chains proposed in this paper can serve as a reference for risk studies of landslide-debris flow disaster chains in South China and other similar areas.

In the context of global climate change and accelerated urbanization, coastal cities in China are facing increasing risks from compound disasters caused by the co-occurrence of extreme rainfall and high tide levels. These risks pose substantial threats to urban development and the safety of residents' lives and property. Therefore, it is essential to reasonably calculate the designed co-occurrence probability of rainfall and tide levels under different standards for the planning and design of flood control and drainage systems in coastal cities. In this study, we selected 105 drainage zones in Guangzhou, China with the aim of analyzing the spatial distribution characteristics and co-occurrence risk of extreme rainfall and high tide levels. Based on tide level and elevation data from Guangzhou, the 105 flood-prone zones were divided into 37 areas unaffected by high tide levels and 68 areas affected by high tide levels. Rainfall sequences and corresponding tide-level sequences for each zone were selected using the peak-over-threshold sampling method. On this basis, the designed combinations of rainfall and tide levels under different joint return periods were calculated using Copula functions and the co-frequency method, and their spatial distribution characteristics were analyzed. Our results show that, influenced by factors such as rainfall volume and elevation, the joint return periods of extreme rainfall and high tide levels for 50-year, 100-year, and 200-year events were approximately 30~35 years, 50~58 years, and 74~94 years, respectively. This indicates that the designed return periods for extreme rainfall and high tide levels individually were lower than their corresponding joint return periods, highlighting the obvious amplification effect of the co-occurrence of rainfall and tide levels. The designed storm intensity generally decreased from north to south, reflecting the spatial variability of rainfall patterns across the city. The probability of a 100-year daily rainfall event coinciding with a 100-year high tide level in Guangzhou showed an increasing trend from north to south, underscoring the heightened vulnerability of the southern regions to compound flooding. Additionally, areas in Guangzhou farther from the estuary were less affected by high tide levels than the central and southern regions, resulting in relatively lower risks of rainfall–tide level co-occurrence. This spatial heterogeneity emphasizes the need for region-specific flood control strategies. Our findings provide valuable insight into the spatial distribution and risk of compound flooding in Guangzhou, China. By quantifying the joint probabilities of extreme rainfall and tidal events, we offered a scientific basis for optimizing flood control and drainage infrastructure. The results of this study can guide policymakers and urban planners in developing targeted measures to mitigate the impacts of compound disasters, thereby enhancing the resilience of coastal cities to climate change and urbanization. This study not only contributes to the understanding of flood risks in Guangzhou but also provides a methodological framework that can be applied to other coastal cities facing similar challenges. The research outcomes serve as a critical reference for the planning and design of flood control and drainage systems in Guangzhou, offering practical solutions to reduce the risks posed by compound disasters and to safeguard urban development and public safety.

Under the influence of climate change, drought poses a novel and urgent challenge to sustainable development in the humid regions of southern China. Therefore, it is essential to estimate future drought changes and population exposure comprehensively. Using CMIP6 climate models and population forecast data, we estimated drought variations and population exposure in the Xijiang River Basin of Guangxi from 2021 to 2100 under three scenarios of Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The findings are as follows: (1) By employing Taylor diagrams to evaluate the multi-model ensemble mean method (MME) of 18 CMIP6 climate models, we found that the method effectively simulated temperature and precipitation in the Xijiang River Basin, reducing the uncertainty associated with single-model simulations. Under all future scenarios, temperature and precipitation in the Xijiang River Basin are projected to increase, with effects of climate change becoming more pronounced in this region. (2) Using the Standardized Precipitation Evapotranspiration Index (SPEI), we observed a significant increasing trend in aridification in both historical and future periods. Significant differences and complex changes in the rate, occurrence time, frequency, intensity, and other drought characteristics were observed under various scenarios. Droughts are expected to be alleviated under low-emission scenarios but intensify comprehensively under high-emission scenarios. (3) The spatial variability of drought in the Xijiang River Basin will differ significantly under different scenarios. In low-emission scenarios, the intensity and extent of droughts nearly disappear in the long-term. Under medium-emission scenarios, the intensity and extent of droughts may increase. Drought events in this region are severe and worsen comprehensively, under high-emission scenarios, and the long-term impact will be extensive and serious. Drought events in this region are influenced by global climate change and are closely linked to the specific socioeconomic development path of the area. (4) Future, population exposure to drought will be highly correlated with different emission scenarios in the Xijiang River Basin. Under low-emission scenarios, the total population affected by droughts decreased. However, under medium-emission scenarios, the population exposed to each drought level will substantially increase in the medium- to long-term, and the spatial distribution will be more complex. In high-emission scenarios, although the exposure of populations may decrease in the short-term owing to extreme weather events, it will sharply increase in the medium- to long-term, especially with a sharp rise in exposure to severe droughts in the long-term. Climate change is the main factor affecting population exposure to drought; however, emission strategies are fundamental drivers, and population growth and structural changes cannot be ignored. Therefore, emission reduction measures play a key role in mitigating the risk of drought under the impact of global climate change. It is urgent to promote the transformation of low-carbon development models, strengthen regional coordination, and formulate adaptive strategies. This study provides scientific evidence for water resource management and drought response strategies in the Xijiang River Basin, and is of great significance for regional sustainable development.

With the acceleration of climate change and urbanization in recent years, extreme rainstorms and urban flooding have increasingly threatened urban safety. Their impact on cultural, commercial, and tourism industries is widespread and significant, often leading to traffic paralysis, closure of tourist attractions, business shutdowns, and passenger stranding. In severe cases, this can endanger personal safety and result in significant economic losses. Shanghai, a representative coastal tourist city in China, is highly prone to rainstorm-induced flooding events from June to October each year due to the Meiyu front, extreme rainstorms, and typhoons. Conducting flood inundation simulations in Shanghai during the flood season is essential to identify high-impact urban flood areas and evaluate flood effects on densely populated cultural, commercial, and tourism hubs. This study used daily rainfall data from Shanghai between 1990 and 2020 to construct nine rainstorm scenarios based on three flood season periods (Meiyu, midsummer, and autumn) and three rainfall thresholds (maximum, 99th, and 95th percentiles). Using the SCS-CN and Mike21 hydrodynamic models for urban rainstorm flood simulations, a fuzzy comprehensive evaluation index system was developed based on a combination of Analytic Hierarchy Process(AHP) and Entropy Weighting Method (EWM) to assess the impact of flooding on Shanghai's cultural and tourism cluster areas. Results indicate the following: (1) Shanghai experiences the highest impact from rainstorm-induced flooding in the midsummer period. In the 95th percentile scenario, suburban areas experience minor flooding, whereas in the maximum value scenario, central urban areas experience a significant increase in flooding impact. (2) Control rules effectively improved the rationality and adaptability of the flood impact evaluation system. Resident and transient populations are key factors in evaluating flood impact. The flood impacts in Shanghai's cultural and tourism clusters showed significant spatial and temporal gradient characteristics, with medium-to-high- and high-impact areas primarily concentrated in the central urban cultural and tourism clusters. (3) Midsummer had the largest medium-to-high and high-impact zones, reaching 3.1 km² (8.79% of the total area), followed by the Meiyu period, whereas the autumn period has the smallest impact. (4) During midsummer, the largest proportion of high-impact areas was found in street- and road-type clusters, followed by waterfront leisure and comprehensive cultural tourism clusters, with areas accounting for 27.52%, 8.30%, and 6.44%, respectively. Cultural and tourism clusters should strengthen early warning, regulation, and preventive measures based on seasonal variations, especially during midsummer, when effective countermeasures must be implemented to reduce flooding impacts on visitor experience and regional safety. This study provides valuable insights for urban flood forecasting, early warning, and emergency response, as well as recommendations for sustainable development of the urban cultural, commercial, and tourism industries.

In recent years, the number of Chinese university graduates has been progressively increasing, and their employment situation has become increasingly poor under the influences of the COVID-19 epidemic and downward economic pressure. The employment issue of university graduates has attracted considerable attention. The migration of university graduates is synthetically affected by multiple factors including individual-, family-, and city-level factors. A systematic theoretical framework of the influencing mechanism of the migration of university graduates, which combines these factors, is lacking. Moreover, extant studies have scarcely investigated the migration of university graduates from the overall perspective of family capital, let alone different factors considered by graduates with different family capital levels in the migration decision-making process. The role of human capital in the relationship between the family capital and migration of graduates still remains unknown. To address this gap, based on first-hand survey data on the migration of new graduates from 78 universities in eight cities in 2022, this study employs a nested logit model to examine the influencing factors on the intercity migration of university graduates from both the individual and city levels, and reveals the dual influencing mechanism of family capital (economic, cultural, and social capital) and human capital (education qualification, university type, student cadre status, academic records, certificates, and internship experience). The results demonstrate that: 1) Family capital exerts a significantly positive impact on the intercity migration of university graduates. Graduates with higher levels of family capital are more inclined to move to higher-level cities. Compared with graduates whose parents have an annual income level below 90 thousand RMB and highest education qualification below a college degree, graduates whose parents have an annual income level above 90 thousand RMB and highest education qualification above a college degree are more likely to flow to first-tier and second-tier cities. 2) The influence of family capital on the migration of graduates presents significant heterogeneity. When choosing employment cities, graduates with a higher level of family capital pay more attention to urban economic and amenity factors. Compared with graduates with lower levels of family capital (represented by lower parental income levels, lower educational qualification levels, and parents' non-managerial or professional occupations), graduates with higher levels of family capital (opposite to their counterparts) are more affected by income levels, living costs, environmental quality, medical resources, and cultural resources, in selecting employment cities. 3) The human capital of graduates plays both a positive mediating role and a certain degree of a negative moderating role in the impact of family capital on the migration of graduates. All the variables of human capital play a positive mediating role, that is, family capital positively influences the migration of graduates by affecting their human capital; however, some variables of human capital (student cadre status, academic records, certificates, and internship experience) play a negative moderating role, that is, the human capital accumulated in the university can weaken the impacts of family capital on the migration of graduates. By introducing a spatial perspective, this study provides not only empirical evidence for the response to the social concern about whether getting good jobs depends on family background or personal efforts, but also scientific references for promoting the full employment of graduates and guiding the rational talent flows.

Typhoons are among the most destructive natural disasters affecting China's coastal regions, often resulting in substantial economic loss and casualties. The annual average Direct Economic Loss (DEL) caused by typhoon disasters in China exceeds 60 billion yuan, accounting for 10%-30% of the DEL caused by all disasters each year. Consequently, the accurate assessment and prediction of typhoon-induced DEL are essential for improving disaster mitigation strategies and optimizing resource allocation. Rapid development of artificial intelligence and the growth of multi-source spatiotemporal big data have introduced data-driven methods for assessing disaster losses. These methods have the advantage of using large samples to improve adaptability and consider more risk factors. In this study, DELs of 30 typhoon events in Fujian Province at the county level and a total of 911 samples were collected from 2009 to 2021 to establish an assessment model. Owing to the large range of the DEL in different districts and counties during the same typhoon, the logarithm of the DEL was used as the model output. This study included three steps for constructing the model. First, 24 influencing factors of typhoons, including disaster-inducing factors, disaster-forming environmental factors, and disaster-bearing body exposure factors, were calculated using the Pearson correlation coefficient and variance inflation coefficient to analyze the multicollinearity effect, and 20 key factors were selected to assess the DEL. Second, a LightGBM-based model is developed using the selected indicator factors as model inputs. Of the 911 samples, 734 were used to train the model, and 177 were used for validation. Finally, Super Typhoon Meranti was used as a case study to evaluate the applicability of the model in the dynamic DEL assessment of a typhoon. This study evaluated predictive performance of the model using five indicators: the Pearson correlation coefficient (R), coefficient of determination (R ²), mean squared error, mean absolute error, and median absolute error. The importance of LightGBM factors shows that the maximum daily wind speed, river network density, maximum daily precipitation, cumulative precipitation, and GDP per unit area are the primary determinants of typhoon-induced economic losses in Fujian Province. In the training set, R between the predicted results of the model and the actual loss was 0.836, and R ² was 0.66, indicating good fitting ability. In real-world applications, the proposed model effectively captured the spatial distribution of losses from Typhoon Meranti, demonstrating its potential for disaster loss prediction. This study provides valuable insights into typhoon risk assessment and emergency management in Fujian Province and other coastal areas. We sorted the relevant research literature and found that economic loss assessment is more difficult than population, housing, and other loss assessments because economic loss is a comprehensive statistical indicator in China. Therefore, we drew on the method of processing DEL as logarithms from the literature. By comparing with other studies, the results of this study can improve model performance in terms of data quality inspection and sample size.

As China transitions to high-quality economic development, the innovation-driven growth model places increasing demand on the high-tech industry, highlighting the critical role of high-tech talent in enhancing regional competitiveness. Existing studies have primarily focused on talent distribution patterns at national or provincial levels, with limited exploration at the city level. Furthermore, most studies concentrate on the distribution patterns and influencing factors at a single stage, treating talented individuals as a homogeneous group without a comparative analysis of the differences in talent distribution across employment stages, educational qualifications, or school levels. To address these gaps, in this study, we employed big data on high-tech talent resumes spanning 2003 to 2021 using spatial analysis techniques and spatial econometric models to examine the spatial distribution patterns and influencing factors of high-tech talent across different employment stages at the urban scale. Additionally, we explored the heterogeneity of the influencing factors at various educational qualifications and institutional levels. The results reveal the following. First, high-tech talents in China are predominantly clustered in economically developed eastern coastal regions, provincial capitals, municipalities, and urban agglomerations. Compared with the initial employment stage, the spatial concentration of high-tech individuals intensified during the current employment stage. The number of dense clusters in the eastern coastal regions decreased, whereas the number of non-dense clusters in the western and northeastern regions increased. A strengthened "high-high" clustering pattern around central cities in urban agglomerations reflects the increasing preference for high-tech talents in such areas. Second, the factors influencing the distribution of talented individuals differ significantly across employment stages, and are shaped by economic conditions, amenities, talent policies, and administrative hierarchies. Economic factors, particularly income levels, play a dominant role during the initial employment stage, whereas amenities become more influential in the current stage, reflecting a growing focus on quality of life as material needs are met. Talent policies significantly affected talent distribution at both stages. Third, the distribution of high-tech individuals exhibits heterogeneity across educational qualifications and university tiers. High human capital groups, such as postgraduate degree holders and graduates from "double first-class" universities, demonstrate a stronger preference for amenity factors, particularly during the current employment stage. These findings have important implications for understanding talent distribution dynamics, optimizing talent allocation, and fostering supportive environments for talent development. This underscores the urgent need for effective management of high-tech talent mobility, formulation of targeted and actionable talent policies, and enhancement of talent governance modernization.

In the context of intersecting knowledge economies and globalization, attracting international academic migrants has become a crucial external driver for fostering innovation and sustainable development at national and regional levels. The knowledge production activities of international academic migrants in their host countries are embedded within local institutional and cultural environments, and involve multidimensional interactions that engage in economic and sociocultural geographies. However, limited research has examined how different types of collaborative network embeddedness affect the knowledge production of these migrants and the intricate sociocultural mechanisms underlying these dynamics. This study examined network embeddedness in knowledge production by combining the "buzz-pipeline" framework with strong- and weak-tie models, focusing on the structure and characteristics of three types of collaborative networks: local buzz collaborations, domestic pipeline collaborations, and international pipeline collaborations. In-depth interviews with international academics provided qualitative insights into the sociocultural dynamics that drive network embeddedness. Key findings include: (1) Spatial characteristics: Local buzz collaborations among international academics in China are largely concentrated in cities, such as Suzhou, Ningbo, Shantou, and Shenzhen, underscoring the importance of localized networks. Regional hubs, such as Guangzhou and Shanghai play a pivotal role in facilitating cross-city exchanges within urban clusters. Domestic pipeline collaborations are predominantly found in provincial capitals, with Beijing leading the most. International pipeline collaborations are mainly oriented toward developed countries, particularly in Europe and the United States. (2) Network relationships: Domestic pipeline collaborations positively influence both local buzz and international pipeline collaborations. However, a negative correlation exists between local buzz and international pipeline collaboration, suggesting that scholars engaged in strong local networks may be less likely to establish extensive international ties. (3) Impact of network embeddedness: Both "buzz" (regional cooperation) and "pipeline" (cross-regional and cross-national cooperation) have a significant positive impact on the knowledge production of international scholars. However, in terms of knowledge spillover, domestic pipeline collaborations yielded better results in terms of paper output and quality than that by local buzz and international pipeline networks. Strong-tie local buzz networks are the most effective models for maintaining the research productivity. (4) Social and cultural mechanisms: Sino-foreign cooperative universities play an important role in fostering strong institutional ties, resulting in a "broad weak-tie domestic pipeline and a stable strong-tie local buzz" model that maximizes knowledge production. On one hand, Local weak-tie collaborations serve as bridges between international scholars and key research resources. On the other hand, international collaboration networks favor strong-tie international pipelines because of the difficulties international scholars face in completely embedding them into local cultural and institutional contexts. Simultaneously, a stable international collaboration network, particularly one established prior to their arrival in China, can enhance the competitiveness of academic community in China. Concludingly, this study contributes to the literature by offering a nuanced understanding of the multi-scalar and sociocultural dimensions of collaborative networks that shape the knowledge production of international academic migrants. This study provides valuable policy insights for enhancing the ability of China to attract, integrate, and retain global talent. Strengthening institutional support, fostering deeper local embeddedness, and facilitating cross-regional and international collaborations are essential for consolidating the position of China in the global knowledge economy.

Social changes have triggered a drive for change among young people, leading to a spatial reverse mobility trend among university graduates in China, amid shifts in both domestic and international contexts. Using university graduates in Guangzhou as a case study, this study employed a mixed-methods approach, integrating questionnaire surveys, cyber-ethnography, and in-depth interviews. Grounded in spatial and social mobility theories, this study explores the motivations, processes, and outcomes of reverse mobility from the perspectives of structural factors and individual agencies. The findings reveal that: (1) the unequal distribution of spatial resources, shifts in mobility within modern society, and the unique socio-historical environment of Generation Z graduates jointly shape their reverse mobility preferences, with the unequal distribution of spatial resources driving university graduates to consider their location choices from both urban and individual perspectives. Resources available in cities are uneven, and individuals have varying access to these resources. They need to uncover comparative advantages in order to "overtake on a curve." The transformation of societal mobility further facilitates the diversification of movement. Spatially, rapid intercity movement enabled by technology allows some local resources, previously exclusive to first-tier cities, to be more easily accessed across regions. The rapid flow of information further amplifies regional disparities and provides a multifaceted understanding of different cities. Graduates from Generation Z, who are in a unique historical era and social structure, increasingly focus on noneconomic factors such as class mobility, quality of life, and cultural consumption when making employment decisions, no longer simply considering economic opportunities. (2) The factors influencing the reverse migration of university graduates mainly include the realization of their economic, social, and educational cultural capital, as well as considerations of the cost of urban living and the overall environment. According to survey results, university graduates had a clear understanding of the differences between cities. They recognized that first-tier cities offer better matching job opportunities for their fields and higher social status in the future, along with superior cultural resources and public services. However, they are also aware that competition in first-tier cities is intense, the possibility of upward social mobility is relatively low, housing costs are high, and quality of life is lower compared to that in non-first-tier cities. (3) The interviews further confirmed that reverse spatial mobility to lower-tier cities does not necessarily signify a decline in the social status of graduates. Many adapt well to new locales, embedding themselves both spatially and culturally and constructing new social networks that afford a quality of life that is not easily attainable in larger cities. This study developed a new framework for understanding the mechanisms underlying university graduates' reverse mobility by systematically examining pre-migration motivations and post-migration local negotiations and adaptation. By taking a more comprehensive view encompassing economic, non-economic, structural, and agentic factors, this research deepens our understanding of man-milieu interactions during the social transition period. It offers insights into local development and talent attraction strategies and provides policy recommendations to promote balanced urban development in a highly mobile society.

Understanding the factors influencing the return of high-level scientific and technological talent from outside China's customs borders is important for optimizing the policy practice of introducing high-level talent from abroad. Based on the biographical information of 1,248 high-level scientific and technological talents who had studied or worked outside China's customs borders and then returned to China to obtain the National Outstanding Young Scientist Fund from 2009 to 2020, this study analyzes the characteristics of the spatial pattern of the return of high-level scientific and technological talents from outside China's customs borders and their influencing factors using social network analysis and a nested logit model, respectively. The results reveal the following: The outflow city network for talents from outside China's customs borders centers around Hong Kong (China) and Cambridge (USA), while the inflow city network is centered on Beijing and Shanghai. There are notable regional differences in the distribution of cities where these talents return.Cambridge (USA) is the primary source of returning talents to Beijing and Shanghai, while Singapore is the main source of returning talents to Nanjing. For Guangzhou and Wuhan, Hong Kong (China) serves as the main source of returning talents.At the individual level, academic ties and the level of talent introduction programs significantly influence the choice of cities for returning talents. At the macro level, high salaries, significant investment in science and technology, and a high concentration of top-tier scientific research platforms in Chinese cities are the primary factors attracting high-level talents from outside China's customs borders. Additionally, the quality of educational service facilities and favorable climate conditions also play a significant role in influencing city choices.Individual heterogeneity exists in the influence of urban macro-factors on location choices for talent return. Male talents, those with mobility experience, or those who have resided outside China's customs borders for an extended period tend to place greater emphasis on academic and social ties as well as support from high-level talent introduction programs. Conversely, talents returning later are more influenced by higher salary levels and the availability of top-tier scientific research platforms in the city.Compared with existing studies that primarily focus on analyzing the influence mechanisms of talent return driven mainly by policy factors, this study contributes to revealing the joint impact of government policy factors and market-oriented factors on the return of high-level scientific and technological talents.

Southeastern coastal China is sensitive to climate change and is characterized by an advanced economy and aging population. The region faces substantial exposure and vulnerability under climate change, making it a potential hotspot for Compound Heat-Drought Events (CHDEs). Therefore, in this study, we used multi-model integrated prediction data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate different climate change scenarios, along with the standardized precipitation evapotranspiration index (SPEI), sliding threshold method, and Copula joint probability distribution to define drought, heat, and compound events, respectively. Additionally, we aimed to analyze the temporal and spatial patterns of future CHDE hazards in southeastern coastal China under various climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and during different periods (2021-2040, 2041-2060, and 2081-2100). To further understand the lag effect of heat events on drought, we applied a lagged logistic regression model to quantify the attributable fraction (AF) for delays ranging from 1 to 7 days. In particular, we used the CN05.1 high-resolution gridded daily observation dataset to compare and analyze CMIP6 model prediction data, verifying their applicability to the study area and the accuracy of the prediction results. Our results indicate that CHDE hazards (number of occurrence days, intensity, and duration) in southeastern coastal China are expected to increase in the future, with a faster increase under the SSP5-8.5 scenario than under the SSP1-2.6, SSP2-4.5, and SSP3-7.0 scenarios. The intensity is projected to increase faster than the number of occurrence days and duration. Under the SSP5-8.5 scenario, the CHDE intensity at the end of the 21st century is projected to reach 3.41 times that during the baseline period (1995-2014), while the corresponding occurrence days and duration are projected to be 1.74 and 1.61 times those of the baseline period, respectively. This indicates that the probability of high-intensity CHDEs is expected to increase significantly considerably in the future. As for the spatial pattern, the spatial heterogeneity of the hazards (occurrence day, intensity, and duration) was more pronounced under the SSP5-8.5 scenario than under the other scenarios, especially during 2081-2100. Under the SSP5-8.5 scenario, the combined hazard indexes exceed 0.6 in southeastern Fujian, eastern Zhejiang, Jiangsu, and Shanghai, with some areas having indexes as high as 0.9. Spatial variability was shaped by factors such as distance from the coastline, availability of water resources, land use patterns, and human activities. Notably, the spatial heterogeneity in the CHDE duration was significantly greater than that in the occurrence days and intensity. Under the SSP5-8.5 scenario, the CHDE duration was approximately 2.23 times higher in the high-value areas than in the low-value regions, whereas the differences in occurrence days and intensity were smaller, at 1.13 and 1.11 times, respectively. This highlights the urgent need for regional adaptation strategies that focus on the persistence of CHDEs. The lagged effect of heat on drought events in southeastern coastal China exhibits an east-west sea-land gradient, with differences between the northern and southern areas. Specifically, the lag effect gradually intensifies from the inland to coastal regions. This may be attributed to the fact that coastal regions are influenced by the combined impact of heat on both the land and ocean and are more likely to experience delayed droughts. In the north-south divergence, northern Jiangsu experienced a stronger influence of heat on subsequent droughts than the other areas. This is primarily because of its predominantly dryland environment, which is highly vulnerable and in which heat events are more likely to trigger drought events. Under the SSP5-8.5 scenario, the AF value exceeded 5% in the northeastern Jiangsu coastline, eastern Zhejiang coastline, and Shanghai, with lag times of up to 7 days in some areas. This indicates that heat events will have a prolonged effect on subsequent droughts. These results provide a scientific foundation for policymakers to formulate effective disaster prevention and mitigation strategies tailored to their regional needs. Furthermore, they support decision making to promote a climate-adapted society and contribute to sustainable development.

Amidst the intensifying global climate change, coastal cities face multiple marine disaster threats due to sea level rise and frequent extreme weather events. Storm surge-induced flood disasters and their secondary effects (e.g., urban waterlogging) pose systemic risks to the lives of the residents, properties, and coastal system infrastructure. Compared with traditional disaster prevention models, the synergistic mechanism between resilience theory and community risk management not only provides a theoretical framework for urban complex risk prevention, but also demonstrates dynamic adaptive advantages in pre-disaster prevention, disaster response, and post-disaster recovery. Accordingly, this study integrated the resilience community theory with the sponge city concept, selecting 25 storm surge-prone bay communities in the Xiamen Wuyuan Bay Area as samples to establish a community resilience evaluation framework encompassing exposure, vulnerability, adaptability, and spatial connectivity. By integrating 16 subjective and objective indicators, including the rescue facility coverage rate and residents' disaster preparedness literacy, we employed the AHP-CRITIC combined weighting method to determine indicator weights and quantify community resilience levels using TOPSIS analysis. The key findings are categorized as follows: (1) an overview of the marine disaster context, the theoretical evolution of resilient communities, and existing research gaps. The literature review indicated that marine disaster threats to coastal urban safety showed significant upward trends, where communities, as direct disaster-bearing entities, needed urgent refined resilience assessments considering their spatial heterogeneity and component vulnerability. International practice comparisons revealed three critical deficiencies in China's resilient community development: overreliance on infrastructure hardware while neglecting the landscape spatial resilience layout, insufficient innovation in social organizational resilience and collaborative mechanisms, and superficial resident participation lacking substantive interactive mechanisms. (2) Development of multidimensional resilience evaluation system Through meta-analysis and expert consultation, we established a dual-dimensional ("vulnerability-adaptability") evaluation system comprising 7 primary and 16 secondary indicators. The AHP-CRITIC combined weighting results indicated that hazard level (0.221), disaster prevention capacity (0.169), and emergency response capacity (0.168) constituted the highest-weighted primary indicators. Secondary indicators, including coastal length, shoreline protection intensity, and volunteer rescue station accessibility, demonstrated significant spatial exposure and emergency response weights, suggesting for their prioritization in coastal community retrofitting. (3) Implementation of a resilience assessment system for coastal community in Wuyuan Bay Field surveys and questionnaire data enabled quantitative resilience analysis of 25 communities. TOPSIS results revealed geographical location and residents' disaster preparedness as core drivers of resilience differentiation. Inner bay communities (e.g., D25) achieved maximum resilience (0.872) through wetland regulation, natural terrain barriers, and emergency facility clusters, whereas outer bay communities (e.g., D1) showed minimal resilience (0.312), owing to high-risk exposure and medical resource scarcity. Wetland ecosystems notably reduced drainage system loads through hydrological regulation and flood detention mechanisms. (4) Optimization strategies for coastal community resilience. This study systematically identified the core elements for developing community resilience during flood-related disasters through the establishment of a coastal community resilience assessment system and empirical research. Through a comparative analysis of typical domestic and international scenarios, we proposed an actionable resilience enhancement strategy system. For public space optimization, dual-purpose strategies for both normal and emergency conditions were emphasized for road networks and green systems, integrating traffic management with ecological protection. For ecological water system development, the water conservation mechanisms of coastal wetland ecological barriers were systematically elucidated, and a synergistic optimization pathway for wetland protection and community water systems based on nature-based solutions was proposed. Regarding emergency shelter spatial planning, an innovative comprehensive evaluation framework was established, incorporating location accessibility, per capita shelter area thresholds, disaster prevention facility standards, and emergency transportation systems. For social governance, resident participation mechanisms and smart management platforms were suggested to amplify community resilience through flexible interaction and resource integration.

Historical precipitation data are crucial for assessing the risks associated with natural disasters such as droughts and floods. However, some extreme precipitation scenarios may not have been included in historical records, particularly in China where the observed precipitation time series is relatively short compared to the return periods of rare extremes. This limitation poses a considerable challenge in disaster risk assessment, because the absence of data on certain extreme events can lead to risk underestimation. Therefore, the generation of spatially correlated stochastic precipitation events based on historical data is a key issue in disaster risk assessment. Current methodologies tend to focus on generating stochastic precipitation events for either a single site or a small number of sites. However, methods designed to generate stochastic precipitation events on large-scale grids have not yet been fully developed. To address this gap, we aimed to explore a method for generating daily stochastic precipitation events set at a 0.1° grid scale nationwide based on empirical orthogonal function (EOF) analysis and probabilistic fitting of principal component coefficients. We applied the EOF analysis method to decompose daily precipitation data for China from 1961 to 2022 (62 years). For each day of the year, 62 spatial modes and their corresponding mode coefficients were generated. Multiple probability distribution functions were used to fit the probability distributions of the mode coefficients for each day, with the optimal fitting function selected for each day. Based on these probability distributions, thresholds were set using twice the maximum and minimum values of the historical mode coefficients as the upper and lower boundaries, respectively. Monte Carlo sampling of daily precipitation scenarios was conducted using the 62-year historical data (1961-2022). Finally, using 62-year historical data (1961-2022), we performed Monte Carlo sampling to generate daily precipitation scenarios. To compare the consistency and differences between historical and stochastic precipitation characteristics, 5000 years of simulated daily precipitation events were generated. A comparative analysis was conducted using five statistical metrics: maximum value, mean, standard deviation, typical return period precipitation, and spatial correlation. The analysis results show that: (1) The stochastic precipitation adequately preserved the intensity-probability characteristics of historical precipitation, with the average difference between the two at the grid scale being less than 0.9 mm, which is considered negligible. The differences in the precipitation intensities for return periods of 10, 20, and 50 years were all less than 15%, and the differences in their standard deviations were all less than 8%. (2) The stochastic precipitation effectively extended the upper bound of the annual maximum values, with the maximum value in the grid with the greatest difference being 36% higher than the historical precipitation. (3) The stochastic precipitation maintained a good spatial correlation, with the daily Moran's index and Pearson correlation coefficient for all grids across the country having minimum values greater than 0.96 and 0.95, respectively. The national daily precipitation stochastic event set, based on empirical orthogonal decomposition, provides a robust data foundation for subsequent quantitative disaster risk assessments.

This research delved into the complex dynamics of heritage communities during urban renewal, navigating the tension between preserving local heritage and embracing modernization. This study centered on Hangzhou's Mantoushan community and utilized a combination of fieldwork, participatory observation, semi-structured interviews, and online text analysis to investigate the interplay between spatial transformation and the construction of local identity in the context of urban development. This study aimed to dissect the multifaceted effects of urban renewal on the physical and emotional fabric of heritage spaces, with a particular focus on the microhistorical perspective. The methodology involved a comprehensive approach, capturing the voices of residents, tracking changes in spatial usage, and analyzing digital narratives to provide a nuanced understanding of the community's evolution. The results of this study underscore the dual impact of urban renewal. On one hand, it has led to improvements in the built environment and public amenities, fostering a renewed sense of community pride and attachment among residents. On the other hand, the process has been instrumental in the creation of a second space, as envisioned by authoritative bodies, which in turn, has given rise to a third space characterized by commercial, productive, and recreational functions. This transformation has been marked by diverse actors' reconstruction of the third space influenced by their varied perceptions and aspirations, which has led to a sense of dislocation and internal community division. The conclusions drawn from this study highlight the importance of recognizing the uneven and unstable nature of the transition towards a third space. It advocates for a more inclusive approach to urban renewal that acknowledges and addresses the diverse needs and aspirations of community members. This study also emphasizes the critical role of emotional connections and empathy in the sustainable development of heritage communities, cautioning against the illusion of a second space that overlooks the complex realities of community life. This study provides a compelling argument for a more nuanced understanding of the impacts of urban renewal on heritage communities. It calls for a balanced approach that respects the historical significance of these spaces, while embracing the potential for modernization, ensuring that the process of renewal is one that enhances rather than erodes the communities' sense of identity and belonging. The insights gained from this study are not only relevant to the Mantoushan community, but also offer valuable lessons for urban planners and policymakers worldwide, as they grapple with the challenges of integrating heritage conservation with the demands of contemporary urban life.

In the knowledge economy era, technological innovation has become increasingly crucial in forming international competitive advantages and driving national economic development. However, the global distribution of technological innovation remains uneven, with a sustained "core-periphery" structure. From the perspective of evolutionary economic geography, technological development paths are closely linked to the local knowledge base, making it generally difficult to overcome spatial constraints. Consequently, the path-dependent nature of national technological development may reinforce the disadvantageous position of late-developed countries in global technological progress, further widening the technological development gap. In this context, exploring how latecomer countries can achieve innovation breakthroughs spatially becomes essential. From the viewpoint of talent mobility, we employ a global patent database and data on the stock of highly skilled mobile talent to construct a country-time-level econometric model to analyze the impact of birthplace diversity among highly skilled talent on the ability of destination countries to achieve place-breaking innovations. Additionally, we conduct group regression based on multidimensional proximity (geographic, cultural, and institutional) to analyze the varying roles of different talent groups. Our findings reveal that greater diversity in the birthplaces of mobile talent significantly increases the likelihood of destination countries accessing new technological fields unrelated to their existing knowledge base. This suggests that the diversity of talent's country of origin positively influences place-breaking innovations in the destination country. Moreover, we find that multidimensional proximity affects the mechanism by which talent diversity drives place-breaking innovations. Specifically, talent diversity has a stronger impact on breakthroughs between geographically and culturally distant countries, while institutional distance appears less significant. This is likely because mobile talent from geographically distant countries brings more differentiated knowledge and skills, helping destination countries overcome geographical constraints on technological development. In contrast, between culturally closer countries, mobile talent faces fewer communication and integration barriers, which enhances the positive effects of their birthplace diversity. The results suggest that, when introducing highly skilled migrants, countries should focus not only on the scale and quality of talent but also the diversity of talent origins. Actively recruiting highly skilled individuals with diverse skills and differentiated knowledge can foster technological development, help overcome geographical constraints, and achieve technological catch-up. Additionally, countries should cultivate supportive linguistic, cultural, and social environments to ease the cross-cultural adaptation challenges faced by highly skilled immigrants. Simultaneously, countries should promote interaction among diverse talent groups, facilitate communication with local talent, and build affiliation networks to better leverage the benefits of talent diversity. These insights provide important guidance for latecomer countries in designing immigration and innovation policies and offer a new direction for future research. Future studies should explore non-proprietary innovation behaviors, delve into the integration and exchange among different talent groups at the micro level, and examine the underlying mechanisms using both quantitative and qualitative methods.

Disaster prevention and mitigation policy texts serve as a guidance and basis for the government to respond to disasters. They contain rich information on disaster risk factors, records the degree of damage caused by disaster hazard factors to disaster-bearing bodies, and provide disaster prevention measures. Risk factors form the foundation of a disaster risk assessment index. This study considered storm surges as an example and deconstructs risk factors into three dimensions-hazard, vulnerability, and disaster resistance capacity–by integrating disaster prevention and mitigation policy texts. Text mining techniques were used to analyze the composition and evolution characteristics of risk factors in policy contexts, with a focus on emphasizing disaster prevention and reduction at different stages. This study constructed a policy text-driven theoretical framework for disaster risk assessment, overcoming the limitations of traditional indicator systems that rely on statistical data and expert experience, and revealed the key role of institutional factors in risk formation. The results are as follows: (1) Policy texts can be used to extract a large number of storm surge risk factors, with hazard factors linked to high-frequency terms such as "sea level rise" and "typhoons," vulnerability to "coastal areas", "coastal zones", "land use", etc., and disaster resilience to "engineering defense," "financial support," etc. (2) There are significant differences in the focus on risk factors in policy texts at different stages. Before 2010, the focus was on identifying and monitoring disaster risks. From 2010-2015, the focus was on further refining the vulnerabilities of disaster-bearing bodies. After 2015, there was greater emphasis on the role of technological development in disaster resistance. These changes reflect the gradual deepening of policymakers' understanding of storm surge disaster risks. (3) The elements extracted from the policy text, such as "astronomical tide," "land reclamation," and "disaster insurance," have compensated for the neglect of human intervention and institutional factors in traditional indicator systems. This study pioneered a new paradigm of policy text analysis in disaster risk assessment at the methodological level, breaking through the traditional reliance on structured data in storm surge disaster risk assessments. Policy evolution analysis revealed changes in risk concerns.

Global climate change has increased the frequency and severity of urban flooding, posing significant risks to critical infrastructure. The resulting disruption of essential services has profoundly impacted the daily lives of urban residents and, in extreme cases, endangered their safety. A systematic framework has been developed to address this, integrating flood process simulation, critical infrastructure modeling, and social vulnerability analysis. This framework elucidates the complex interdependencies among urban infrastructure systems, evaluates the impacts of flood-induced service disruptions on urban populations in the context of climate change, and assesses the resilience of various infrastructure services. The Shenzhen-Maozhou River Basin, prone to flooding, was selected as the study area. Based on the Delft3D model and using the "Mangkhut" typhoon event as a benchmark, rainfall and sea-level rise were selected as uncertainty factors to simulate and identify three future extreme flood scenarios. A network-based approach was employed to construct an infrastructure system network model that included seven types of infrastructure: substations, communication base stations, hospitals, fire stations, police stations, shelters, and water supply plants. The flood simulation results were used as inputs to the infrastructure system network model to obtain the simulation results, which were then analyzed. The results revealed the following. 1) Within the system's topological structure, the degree value of substation nodes is significantly higher than that of other facilities, making them a critical node for cascading failures triggered by floods. The power-outage areas simulated by the constructed model demonstrate a 62% concordance rate with the historical validation data, indicating a relatively high credibility level. However, due to the sensitivity and confidentiality of the data, the validation work is not yet sufficient. The types of infrastructure involved in the validation are limited, affecting the model's reliability and parameters. Therefore, in future research, it is necessary to collaborate with relevant stakeholders to obtain the relevant data, which will be used for model validation and parameter calibration, to enhance the model's reliability. 2) During the floods triggered by Typhoon Mangkhut, the cascading effect significantly increased the number of fire stations and police stations affected, which rose from 1 to 11 and from 1 to 7, respectively. Meanwhile, the disruption of communication and medical services had a more pronounced impact on the urban population, with the ratio of the population affected by service disruptions exceeding 5 (a ratio of "1" represents 140,672 people). 3) Under the backdrop of climate change, the disturbance of future extreme flood disasters on the infrastructure system network is significantly intensified. After taking into account the cascading effects, the overall number of affected infrastructure facilities is, on average, 38% higher than the baseline scenario of "Mangkhut" 4) Thanks to the relatively rational spatial layout and the flood resistance of the facilities, the power system, emergency response (covering police and fire services), and shelter services in the Maozhou River Basin have demonstrated a certain degree of stability. This study helps clarify the complex interdependencies among urban infrastructures, assess the impact of floods on the stability of service systems, and identify potential cascading effects on residents ' lives. It provides decision-making support for urban disaster prevention, mitigation planning, and emergency response strategies.

With the vigorous development of the global sports industry and the continuous improvement of competitive sports, the cultivation and development of sports talent has become an important component of sports strategies in various countries. An in-depth exploration of the spatiotemporal evolution laws and driving mechanisms of high-level tennis players in China is of great significance in sports talent research. It reveals the spatiotemporal distribution characteristics of sports talent, analyzes the internal logic of evolution, and lays a theoretical foundation for sports talent cultivation and resource allocation optimization. This study focuses on a group of high-level tennis players in China, taking a unique approach from the perspective of geography of talented individuals, and comprehensively using multiple quantitative analysis methods to explore their spatiotemporal distribution characteristics and influencing factors: 1) From 2013 to 2022, the annual distribution of high-level tennis players in China was uneven. The eastern region, leveraging its early advantages in terms of economy, facilities, and talent cultivation, has long accounted for the majority of players. However, in the past decade, there has been a slight decrease, partly because of the maturity of talent pipelines and the outflow of talent. The central and western regions, bolstered by policies, tournaments, and the return of talent, have experienced frequent fluctuations in player numbers. In contrast, owing to industrial adjustments and changes in sports investment strategies, the northeastern region has experienced significant fluctuations in the number of players and instability in tennis talent cultivation. 2) In terms of spatial distribution, tennis players are concentrated mainly on the southeast side of the Hu Line, where the economy and culture are advanced and sports resources are abundant and readily available, forming a stark contrast with the northwest region. Further exploration of the spatial evolution trajectory revealed that the major axis of the standard deviational ellipse aligns in a northeast-southwest direction. Over the past decade, the area encompassed by the ellipse has expanded considerably, directly reflecting the expanding distribution range of tennis players, which is no longer confined to traditionally advantageous regions. Meanwhile, the spatial center of gravity has shifted towards the southwest, indicating that the southwestern region is gradually emerging as a hub for attracting and cultivating tennis talent and is becoming an emerging force in tennis development. 3)According to the factor analysis, the urbanization rate (regression coefficient 0.608), per capita GDP (0.518), and the number of regional tennis courts (0.493) were the core factors. The correlation coefficient between the urbanization rate and the number of regional tennis courts was 0.793, the correlation coefficient between per capita GDP and the number of regional tennis courts was 0.783, and the interaction coefficient between per capita GDP and urbanization rate was 0.758. The synergistic effect far exceeded that of a single factor. This study theoretically fills a gap in tennis talent geography, constructs an innovative analytical framework, and assists sports departments in implementing precise policies to promote tennis development. The literature opens new paths for subsequent research, provides empirical references, and triggers in-depth discussions in academia.

Rapid urbanization and geological disasters pose significant challenges to regional ecological security. Although Ecological Security Pattern (ESP) construction is important for ecosystem stability and sustainable development, traditional approaches rarely incorporate vertical geological factors, such as land subsidence. This study proposes a framework that integrates land subsidence into ESP construction through machine learning and multi-source data fusion methods. Using Zhuhai City as a case study, we analyzed 30 environmental variables, including historical land subsidence data, topography, soil distribution, land use, climatic factors, and human activity indicators. The methodology consisted of four main steps: (1) correlation and principal component analyses to identify key factors and reduce dimensionality; (2) development of a multilayer perceptron (MLP) deep learning model with three fully connected hidden layers using ReLU activation functions and dropout regularization to predict ecological pattern types; (3) comparison of four fusion methods (weighted average, nonlinear sigmoid transformation, information entropy, and principal component analysis) to integrate prediction results; and (4) spatial analysis of the relationship between land subsidence and ecological security patterns using chi-square tests and spatial overlay analysis. Results showed that the MLP model achieved an average prediction accuracy of 84.5% with an F1-score of 0.844, demonstrating the feasibility of deep learning approaches in ESP construction. The principal component analysis showed that the first four principal components cumulatively explained 71.4% of the total variance, with the first two components explaining 27.1% and 19.8%. The first principal component was dominated by climatic factors, whereas the second primarily reflected the topographic and geological vulnerability characteristics. Spatial analysis revealed significant spatial heterogeneity in the impact of land subsidence on the ESP, with moderate historical subsidence (8-41 mm/year) showing more notable effects (x²= 57.008, P<0.001). Land subsidence in the 8-16.5 mm/year range showed particularly significant differences in the corridor areas compared to the non-subsidence zones (P = 5.7e-05). Source and construction areas exhibited higher proportions of mild subsidence (7.14% and 9.84%, respectively), which should be prioritized for monitoring and management. Different fusion methods showed varying effectiveness. Principal component analysis and information entropy performed better in identifying construction and corridor areas, whereas nonlinear fusion showed advantages in source area identification. This study makes three key contributions: (1) it establishes a novel methodological framework for incorporating vertical geological factors into ESP construction, addressing a significant gap in traditional approaches; (2) it quantitatively reveals the spatial heterogeneity of land subsidence impacts on different functional ecological zones, providing evidence-based guidance for targeted management; and (3) it demonstrates the effectiveness of deep learning and multisource data fusion techniques in complex ecological-geological system modeling. These findings provide methodological support for developing an ecological security pattern centered on coastal wetlands and estuarine systems in Zhuhai City and suggest potential approaches for coordinating ecological protection, disaster prevention, and urban development under land subsidence conditions. Future research should focus on utilizing high-resolution spatiotemporal data, refining algorithms, and developing mechanisms to translate research findings into practical urban planning and ecological management policies.

In recent years, the number of marathons in China has expanded rapidly, but the impact of high-temperature weather has become more apparent. Current high-temperature early warning systems lack tailored thresholds and unified standards for sports scenarios. This study aimed to develop an advanced early warning system for high-temperature exposure during marathons to enhance event safety and sustainability. The urgency of addressing high-temperature risks in sporting events is underscored by an increase in the frequency and severity of extreme heat events. These events not only threaten participants' health, but also challenge the organizational resilience of sporting events. Traditional early warning systems, designed primarily for general public health protection, fall short of providing the specificity required for sports settings. This study addresses this gap by proposing a refined early warning framework that is sensitive to the unique demands of marathons. Methodologically, this research moves beyond the limitations of a single air temperature index by employing the Wet-Bulb Globe Temperature (WBGT) as the primary indicator for thermal environment assessment. WBGT is recognized as a comprehensive metric that integrates temperature, humidity, and radiant heat, making it more suitable for evaluating heat stress during outdoor activities. By analyzing the relationship between human thermal comfort and meteorological factors, the study maps the Thermal Humidity Index (THI) sensory grading criteria to the WBGT system, creating a dynamic "red-orange-yellow" three-level early-warning system. The threshold setting considered the metabolic heat accumulation of marathoners during prolonged activity and was validated using six decades of national-scale meteorological data. Based on this, this study introduced the Marathon Exposure Index (MEI), which quantifies risks from three dimensions: exposure intensity (early warning level weight), exposure quantity (event frequency), and exposure value (event-grade coefficient). Results indicate a significant "long-south-short-north" pattern in China's marathon high-temperature exposure period. Southern regions, such as the Yunnan-Guizhou Plateau and the southeastern coast, have experienced extended high-temperature exposure periods compared with the historical baseline (1961-1990), with frequent red-alert zones coinciding with high-density Class A event areas (such as the Yangtze River Delta and Pearl River Delta). Further temporal analysis revealed that with accelerating global warming, extreme high-temperature red-alert events in China are becoming more frequent and prolonged. The innovative value of the study's findings is reflected in three key aspects. The early warning mechanism design established a graded-threshold dynamic-response-linked paradigm. By linking WBGT thresholds with event response measures, it enables a management paradigm shift from "passive response" to "proactive prevention and control," aligning general meteorological early-warnings with event safety management. In assessment technology, it breaks the traditional single-factor analysis framework, integrating an "intensity-quantity-value" three-dimensional model for comprehensive risk evaluation, integrating a refined early warning system with region-specific management measures, this approach ensures the safe operation and sustainable development of events. In practical applications, the proposed dynamic circuit-breaking response mechanism (e.g., event cancellation upon a red alert) was validated through situational simulations to significantly reduce heat-related injury rates and provide more forward-looking warning and response measures. Additionally, the research findings are broadly applicable to other outdoor sports and provide robust theoretical and practical tools for ensuring the safety of public sports activities amid climate change. The implications of this study extend beyond immediate applications to marathon event management. This study contributes to a broader discourse on climate change adaptation strategies in the sports and public health sectors. By offering a flexible and scalable framework, this study will enable stakeholders to tailor heat risk management strategies to diverse regional and event-specific contexts. Future research could explore the integration of real-time weather forecasting and participant physiological data to further enhance the precision and responsiveness of high-temperature early warning systems in sporting events.

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

In the context of global climate change, natural disasters pose increasingly serious threats to the Guangdong-Hong Kong-Macao Greater Bay Area. Therefore, in this study, we aimed to conduct integrated comprehensive zoning of natural disasters and to develop disaster prevention and mitigation countermeasures for the Greater Bay Area. To achieve this objective, we first carried out geomorphological division of the Greater Bay Area based on the land geomorphological classification system. Second, we performed comprehensive zoning of natural disasters according to the intensity of dominant natural disasters in various geomorphological units. Finally, we conducted risk zoning of natural disasters according to the main controlling factors of natural disasters in each zoning units. Based on the geomorphology of the Greater Bay Area and the risk of natural disasters, we proposed natural disaster prevention and mitigation countermeasures. The results show that: (1) The landform of the Greater Bay Area can be divided into four major first-class divisions: mountains, hills, platforms and plains. The landforms of the Greater Bay Area can be divided into 10 secondary subdivisions, including medium-altitude small undulating mountains, low-altitude small undulating mountains, low-altitude erosion and denudation hills, low-altitude erosion and denudation platforms, low-altitude alluvial platforms, low-altitude alluvial flood platforms, low-altitude alluvial plains, low-altitude marine plains, low-altitude marine alluvial plains, and low-altitude estuarine coasts. Among these subdivisions, low-altitude small undulating mountains represent the largest area (21,618.28 km²), while low-altitude erosion and denudation platforms represent the smallest area (849.77 km²). (2) The Greater Bay Area can be divided into three first-level major disaster subdivisions: mountain and hill disaster areas (52.77%), plain and platform disaster areas (40.43%), and estuary and coast disaster areas (6.80%). (3) The Greater Bay Area can be further divided into second-level disaster subdivisions, including the small undulating and low-altitude mountain disaster area, low-altitude alluvial plain land subsidence area, low-altitude plain and platform flood area, and 14 others. The largest second-level disaster subdivision area is the small undulating low-altitude mountain disaster area (20,892.18 km²), which is distributed in the east, north, and west of the Greater Bay Area, followed by the low-altitude plain and platform flood disaster area (13,320.98 km²), which is mainly distributed in Guangzhou, Jiangmen, Shenzhen, Huizhou, and Zhaoqing cities, among other areas. The karst collapse area of the low-altitude platform represents the smallest second-level disaster subdivision (163.62 km²) and is mainly distributed in some areas of Enping and Jiangmen cities. (4) The natural disaster risk in the Greater Bay Area can be divided into high-risk, medium-risk, and low-risk areas. The high-risk areas for mountain disasters are mainly in Deqing, Huaiji, and Guangning of Zhaoqing City; and Conghua District in the north of Guangzhou City, Longmen, Boluo, and other regions in Huizhou City. The high-risk areas for plain and platform disasters are mainly in Doumen District, Zhuhai City, Guanghua Basin, Huadu District, Nansha District, Guangzhou City, Foshan City, and other regions. The high-risk areas for estuary and coast disasters are mainly in Doumen District, Zhuhai City, and near the mouth of the Pearl River Delta. In this study, we proposed disaster prevention and mitigation countermeasures for natural disasters in the Greater Bay Area from four perspectives. Our results serve as a valuable reference for the Greater Bay Area urban agglomeration in regional development planning, comprehensive disaster reduction planning, and the improvement of disaster prevention and mitigation capabilities.

A comprehensive understanding of the distribution pattern and driving factors of population aging at the country level in China is fundamental for enhancing the governance capacity of the governing authorities and implementing a national strategy to actively cope with the aging society. On the basis of the 2000, 2010, and 2020 census data on the Chinese population, we determined the distribution pattern of population aging in China over the past 20 years at the county level and adopted a fractional response model to identify the main influencing factors of such spatial distribution from three perspectives: the natural environment, socioeconomic factors, and population migration. The following observations were made: 1) During the past 20 years, most counties in China have entered into an "aging society," some counties have entered into an "aged society," and counties in the Chengdu-Chongqing region, central Inner Mongolia, and peripheral Yangtze River Delta have entered into a "hyper-aged society." 2) The spatial structure of the distribution of population aging exhibited various patterns. Overall, the Hu Line is a clear demarcation for the distribution, with the degree of aging of the counties in the southeastern half of the line being generally higher than that of the counties in the northwestern half and maintaining a certain degree of stability. During the past 20 years, the aging population has shown a gradient diffusion of the characteristics of the Eastern monsoon region―Northwest arid region―Qinghai-Tibet Plateau region. From a local perspective, population aging presents various structural characteristics, such as "homogenization," "reverse core-edge," and "core-edge" spatial structures. 3) Significant regional differences exist in population aging. Vast differences in population aging between different ecological regions, between urban and rural areas, and between ethnic and non-ethnic autonomous regions are obvious, and these differences tend to expand further. 4) Natural factors have laid the macro pattern of the distribution of population aging. Socioeconomic factors are the main driving force of the aging process, and population migration has played an important role in restructuring the aging space pattern. This study provides a scientific basis for optimization of the spatial allocation of pension resources, and different regions can actively respond to the formulation and improvement of differentiated policies for population aging.

Place memory and emotions are popular topics in human geography. The rapid development of information technology has promoted new social media platforms, built virtual spaces that differ from physical spaces, and provided new carriers for place memory and emotional sustenance. In this study, subtitle, bullet-screen, and comment data were quantified on the basis of disembedding theory and media geography combined with the natural language processing method to explore the process of local memory awakening under the background of "digital-reality fusion," taking the documentary "A Bite of China" as the study case. The following results were obtained: 1) The theme words of the subtitles included hometown, food, taste, and life. In the bullet-screen and comment data, the words "food" and "hometown" were the core nodes that built the semantic network together with other theme words. Food has become a representative of local culture, not only as a focus of local economic development but also as a window to regional culture, and is capable of awakening people's deepest memories of their hometowns. Food reflects the good wishes and life expectations of people, with the memory of the taste of their hometown having become a symbol of this attachment and the nostalgia touching the hearts of travelers. 2) The documentary awakens social memories, shapes places in modern society, and constructs a sociocultural space that carries food culture and daily practices. From the data visualization results, it could be seen that the audience as a whole showed positive emotions, the immediacy of bullet-screen was more likely to stimulate positive emotions than comments, the semantic network of bullet-screen was denser, and the audience was more inclined to comprehensively evaluate the overall level of the video in comments. Modern media technology breaks through the limitations of physical space, bringing the experience of virtual space to the audience and allowing them to instantly express their emotions and feelings while watching the video, thereby realizing the generation of emotional ties and social relations across time and space. Mediated communication has become a habitual practice in modern society, providing channels through which audience members can exchange information and ideas and express their emotions daily, thereby shortening the mental cognitive distance of people and having the same authenticity as unmediated communication and interactions. 3) Digital media provides a new interactive platform for the audience, dissolves the geographical limitations of traditional communication, and realizes dialogue between virtual and physical spaces. It also reconstructs the relationship between people and places and shortens the emotional distance between people and hometowns while providing information for daily life practices. Digital media has reconfigured the relationship between people and places in society through new media technology, creating a new type of physical space connection; namely, virtual space. In addition to local activities, the virtual space provides a new place for people to communicate and interact with one another. Although it is also a place that carries people's emotions, it enriches the audience's experience, thus contributing to the construction of the media's sense of place. This study expands the content of dietary geography and provides theoretical and empirical references for the reconstruction of human-land relations in the digital information age.

In the digital economy era, take-out shops relying on the online-to-offline e-commerce platform have gathered in central cities on a large scale, forming large-scale food processing spaces—"Takeaway Factories"— to serve immediate local catering needs. In addition to the impact of the platform economy, consumer demand, and space costs, riders are an important and dynamic factor that promote the final formation of a "Takeaway Factory". Based on the analysis framework of virtual and real-space interactions using the participatory survey method, the specific roles of crowdsourcing and special delivery riders in the formation of "Takeaway Factory" was elucidated. Riders, as the core intermediaries of virtual agglomeration that leads to physical agglomeration, play a role at different stages and spatial scales. In the initial stage, because dedicated takeout shops tend to prefer low-cost, high-demand urban gap spaces, they face challenges in matching with special delivery riders until they are included in the special delivery distribution station. Thus, crowdsourcing riders with free-movement attributes are their first choice. Crowdsourcing riders have a strong preference for store clusters and select food through the two tools of the regional order heat map and grab order hall, bringing about differences in distribution efficiency and promoting the phenomenon of large regional differentiation of relatively concentrated and dispersed stores within the city scale. In the middle stage, in the face of the uneven distribution efficiency of different areas in the city, the platform divides the size of the stations according to the size of the shops in different areas, and matches the special delivery riders of the corresponding scale, which eliminates the uneven distribution efficiency of different areas to a certain extent, and promotes the distribution efficiency of different sections to reach a basic balance. With the emergence of special delivery systems, the special delivery riders are distributed in the station area through the delivery system, which effectively alleviates the distribution pressure of the relatively dispersed, inferior-location stores and promotes the balance of the distribution efficiency of different sections. In the final stage, the special delivery and crowdsourcing riders in the area jointly promote the agglomeration of shops in the area, and ultimately promote the formation of a more polarized takeaway factory. Crowdsourcing riders continue to promote agglomeration from the initial stage, whereas the emergence of special delivery riders promotes both equilibrium and agglomeration. With the increasing maturity of the special delivery and crowdsourcing system, the time-space behavior of different types of riders will eventually promote the completion of the high-density and large-scale agglomeration of takeaway shops in the area (distribution site) through virtual tools, such as site order thermal maps, order dispatching systems, resident points, and order-grabbing halls.

As a social, cultural, and spatial phenomenon, the spatial characteristics and dynamics of youth neo-tribes reflect the mode, process, and strategy of interaction with their social environment. However, existing studies mainly regard space as a formation condition and internal characteristic of neo-tribes, while failing to consider it as a key perspective for understanding the social and historical processes of neo-tribes. Therefore, this study constructs an analysis framework based on two spatial analysis paths proposed by Soja(2005)from his ontology of existence: "time-space" and "society-space." Furthermore, "706 Youth Space" is taken as a case study to analyze the spatial characteristics and dynamics of youth neo-tribes. Our results indicate the following: (1) The "706 Youth Space" embodies distinct neo-tribal attributes, including the mobility of its members, common feelings, rituals and symbols, and a shared space. As a neo-tribal space, the socialization of "706 Youth Space" includes emotional resonance and identification, memory generation, and imagination extension. This study supports the summary of the characteristics of neo-tribes in existing studies. Additionally, it reveals the temporal and spatial continuity, rhythm, and spatialization of the instantaneous outbreak of the neo-tribe and emphasizes the spatiality characteristics in the process of its socialization. (2) This study analyzes the relationship between the neo-tribe and its environment through the spatial strategy, and corrects the double illusion of the existing research on the spatial understanding of neo-tribes. The game strategy between the "706" youth neo-tribe and its environment is summarized as space contraction, stimulus diffusion, and space expansion strategy. The youth neo-tribe needs to be embedded in the real social space, and can be preserved and developed through strategic contraction and change. Through space extension strategies such as the opening of space and expansion of relationships, we can promote the connection with the place and make it a bridging space in terms of filling and extensibility of social relations. (3) This study analyzes the role of virtual and physical space in the formation of youth neo-tribes, the embodiment in their survival strategy, and the respective characteristics and relationships of virtual and physical space. Among them, in the formation, strengthening, and identification of neo-tribes, young people change from unfamiliar online members to offline physical space encounters through activities, and form temporary neo-tribes based on common feelings under the guidance of common interests and tastes. After the activity, young participants establish a sense of identity with the youth neo-tribe and apply to join the online community, thus continuing its existence through the virtual space. In terms of survival strategy, through the contraction of offline space, development of online space, and integration of online and offline, the youth neo-tribe realizes its adaptation to the external environment. The study overcomes the limitation of understanding the relationship between online and offline space from the functional viewpoint and reveals the synergy of such space in emotion, identity, and survival strategy of the neo-tribe.

The primary objective of a regional integration strategy is to foster talent agglomeration and knowledge spillover, thereby enhancing the high-quality development of the regional economy. Extant literature predominantly concentrates on talent distribution and the pattern of knowledge spillover under integration policy. However, scant attention has been paid to the causal inference of regional integration policy on talent aggregation and knowledge spillover. Under the new economic structure of establishing a unified national market and high-quality development, a comprehensive understanding of the evolutionary mechanisms of integration policy in relation to talent aggregation and knowledge spillover is pivotal for shaping regional talent policies and refining theories of population mobility. To address this gap, this study employs time-varying Difference-In-Differences (DID) and spatial DID approaches to empirically assess the influence and underlying mechanisms of regional integration policy within the context of the Yangtze River Delta Urban Agglomeration. The analysis reveals three key findings. First, the integration policy demonstrates a substantial facilitative impact on talent aggregation and knowledge diffusion within the Yangtze River Delta Urban Agglomeration, bolstering these processes by 10.5% and 14.8%, respectively, and exhibiting significant spatial spillover effects. This indicates that the policy not only attracts talent to specific regions but also encourages the spread of knowledge beyond the immediate geographical boundaries of the targeted areas. Second, heterogeneity analysis shows that the policy effectively enhances talent aggregation and knowledge spillover in central cities, with no significant influence observed in peripheral cities. This disparity suggests that central cities, with their advanced infrastructure and economic opportunities, are better positioned to capitalize on the benefits of the integration policy. Furthermore, from a demographic perspective, the policy exhibits a more pronounced positive effect on talent aggregation and knowledge spillovers in medium- and large-scale cities. This trend underscores the importance of city size and demographic factors in the successful implementation of integration policies. Third, mechanistic analysis indicates that the beneficial impacts of the policy on talent concentration are more pronounced in cities characterized by higher levels of urbanization, investment, market integration, education, income level, public service provision, and transportation infrastructure. These factors collectively create an environment conducive to talent attraction and retention, amplifying the effects of the integration policy. Furthermore, the policy has significantly enhanced talent agglomeration by increasing the stock of human capital, highlighting the role of education and skill development in fostering regional economic growth. In conclusion, this study provides a theoretical basis and practical reference for urban agglomerations aiming to spearhead the high-quality advancement of regional economies. By revealing the intrinsic laws and influence mechanisms of regional integration policy, the findings offer valuable insights for policymakers seeking to optimize talent policies and promote sustainable economic development. The empirical evidence highlights the importance of targeted policy interventions that consider the unique characteristics of different urban areas, thereby ensuring a balanced and inclusive approach to regional development. Future research should continue to explore the long-term effects of integration policies and their potential to drive innovation and economic resilience in an increasingly interconnected world.

China has a long history and rich cultural heritage; however, the rampant criminal looting of ancient cultural sites and tombs (referred to as "cultural relics" in this study) poses a significant challenge to the construction of China's cultural confidence and security. Despite its importance, relatively little research has been conducted on this issue from the perspective of criminal geography. Therefore, this study focuses on China, utilizing such methods as text and spatial analyses and mathematical statistics based on relevant data from the "China Judgments Online" website to explore the spatial distribution and its evolution process, crime pattern characteristics, and the main influencing factors of the criminal looting of cultural relics. The research findings indicate that (1) the majority of looted cultural relics are ancient tombs from the Qin and Han dynasties or earlier periods. Crimes have been committed predominantly by middle-aged or older adult men with low levels of education who are typically engaged in farming or are unemployed. (2) Regarding spatial distribution, crime is mainly concentrated in the central and eastern regions, with three high-incidence provinces (Henan, Shanxi, and Shaanxi) and three sub-high-incidence provinces (Zhejiang, Shandong, and Anhui). The hotspots are mainly concentrated at the junction of Henan, Shanxi, and Shaanxi provinces, with seven hotspot cities, such as Luoyang and Yuncheng, and 16 sub-hotspot cities, such as Anyang, Hebi, and Xinxiang. Although slight changes and shifts have been observed over time in the high-incidence areas, their overall locations have remained relatively stable. At the micro level, these crimes frequently occur in farmlands, forests, and wastelands. Both criminal activities and protected heritage sites tend to cluster around the middle-lower reaches of the Yellow and Yangtze River regions; that is, regions with rich cultural relics are more susceptible to cultural relic theft. (3) The spatial mode of criminal travel is mainly "intra-city theft and excavation", and the destinations of "cross-city theft and excavation" are concentrated in the middle and lower reaches of the Yellow and the Yangtze Rivers, mainly in medium and short distances. Most crimes are committed by gangs of 4-9 people (accounting for 80.82% of cases). Crimes are divided into two categories: professional and occasional theft and excavation. The criminal process can be divided into four stages: teaming, planning, implementation, and escape. (4) The distribution of cultural relics and prevention policies are important factors that influence the criminal looting of cultural relics, and the interaction between them is obvious. This study explores the spatial distribution, crime patterns, and influencing factors of such crimes in China and expands the research field of criminal geography to a certain extent. It also provides a scientific reference for historic site protection policymakers.

"Shaping a healthy Greater Bay Area" has been positioned as a key policy agenda in the Outline Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area, issued by the central government in 2019. However, difficulties and uncertainties in accessing healthcare services have long been a major concern for Hong Kong (HK) residents wishing to work or live in mainland China. Information barriers to mainland China's healthcare services have become a primary obstacle for HK residents' cross-border healthcare utilization, while related studies remain scarce. This study aims to examine the extent of the information barrier, its variation among social groups, and its major causes, based on which we also seek potential policy responses. We conducted a large-scale survey of 3,500 HK residents in HK, Shenzhen, and Guangzhou in 2022, of which 2330 had never used mainland China's healthcare services before, and we asked them about their understanding of mainland China's healthcare quality, medical insurance schemes, and healthcare expenditures. Additionally, we conducted in-depth interviews with 129 HK residents, 42 medical professionals, and 14 officials in both HK and mainland China to gather their opinions on information barriers to cross-border healthcare utilization. Profound results were revealed through our mixed research approach: (1) HK residents generally lacked an understanding of mainland China's healthcare services. Only 4.98%, 2.26%, and 2.02% of respondents indicated that they were familiar with the hierarchy of healthcare quality, medical insurance schemes, and healthcare expenditures in mainland China, respectively, while 24.04%, 35.28%, and 37.68% stated they did not know these aspects. The understanding of medical insurance schemes and healthcare expenditures is even more limited compared to the hierarchy of healthcare quality. (2) Among others, middle-aged individuals (especially those aged 45-54 years), middle- and high-income families (with a monthly household income of more than 40,000 HK dollars), those who visit mainland China more frequently, and those with strong social networks in mainland China demonstrated a better understanding of mainland China's healthcare services. (3) These information barriers are the result of exacerbated healthcare information asymmetries amid the differences between HK and mainland healthcare systems and residents' healthcare utilization habits, which have long been unaddressed due to strict regulations on medical advertisements and social segregation between the two societies. Based on these findings, four potential policies are suggested to address these information barriers: (1) Establish a cross-sectional scheme to govern information on cross-border healthcare, with more proactive and integrated policy actions to promote various necessary healthcare information to HK residents; (2) Enrich the channels for promoting information on cross-border healthcare, such as providing an online platform compiling mainland China's healthcare information, promoting professional exchanges between HK and mainland China, and using virtual reality and other state-of-the-art technologies to enable HK residents to better understand the hospital environment and treatment procedures in mainland China; (3) Enhance policy attention to both healthcare quality and healthcare expenditures, with particular efforts to increase HK residents' healthcare affordability in mainland China; and (4) Employ different information dissemination strategies for different groups of HK residents and use those who already understand mainland China's healthcare services as proxies to accelerate information promotion.

Global precipitation observations have been realized through the development of satellite remote-sensing technology. However, there is a lack of evaluation of remote-sensing precipitation products in complex tropical island terrains. This study used hourly rain gauge data to conduct a multi-scale systematic evaluation of common precipitation products, such as CMORPH, CHIRPS, GsMAP, GPM, MSWEP, ERA5-Land, and PERSIANN, over Hainan Island, providing an in-depth analysis of the precipitation detection capabilities of various products in this region. The main conclusions are: (1) In a multi-temporal scale evaluation, GPM and GsMAP outperformed the other products across all time scales. On a 3-hour scale, GPM and GsMAP showed the highest correlation coefficients (0.53 and 0.52, respectively). On a daily scale, except for PERSIANN, all products showed correlation coefficients above 0.56, with GPM and GsMAP showing the best performance (R = 0.73 and 0.74, respectively). (2) In comparing annual precipitation, Hainan Island's average-annual precipitation over the past 20 years showed a fluctuating trend, with a mean of 1,776.4 mm/a. The CMORPH annual average of 1,765.1 mm/a was the closest to the CHM-PRE dataset, with minimal error. ERA5-Land and MSWEP significantly overestimated (2,504.3 mm/a) and underestimated (1,662.2 mm/a) the average-annual precipitation, respectively. (3) Spatial distribution pattern analysis revealed that the observed multi-year annual precipitation in Hainan Island ranges from 996.9 to 2,368.9 mm, exhibiting an annular-distribution pattern with higher precipitation in the east than in the west and the southwestern mountainous areas than in the northeastern plains. The precipitation range of 1,337.9‒2,287.0 mm observed in GsMAP was the closest to the rain gauge data and particularly matched that of the high-value center in the southeast of the island. (4) In a precipitation trend analysis, CMORPH, ERA5-Land, GPM, MSWEP, CHIRPS, and PERSIANN showed an increasing trend in local areas of Hainan Island, while GsMAP showed a stronger increasing trend. (5) In an analysis of extreme precipitation events, GsMAP, CMORPH, and GPM reproduced the spatiotemporal evolution of extreme precipitation events on a daily scale in Hainan relatively well. GPM better reproduced the spatial and temporal evolution characteristics of typhoon precipitation events in Hainan Island. However, the accuracy of the precipitation estimation still requires improvement. The results of this study not only contribute to our understanding of precipitation products applicable to Hainan but also provide insights for improving satellite-based precipitation products in tropical island environments. These findings underscore the importance of regional validation and the potential of multi-product fusion approaches for enhancing precipitation estimates in complex terrains.

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