Typhoons are among the most significant natural disasters affecting the eastern and southern coastal regions of China, inflicting substantial annual damage on both coastal and inland areas. Since the initiation of the reform and opening-up policy, the socioeconomic development of the coastal regions of China has been swift, leading to increased exposure to typhoons. In the context of global climate change, typhoons are expected to increase in frequency and intensity in China. Therefore, researching on the spatiotemporal pattern characteristics of typhoons impacting China is of critical importance for understanding the impact patterns and risk changes of typhoon disasters, as well as for formulating policies on disaster response, prevention, and mitigation. This study aims to provide valuable insights into the formulation of such policies. Based on these objectives, this study utilized a comprehensive dataset, including county-level socioeconomic and disaster statistics, historical typhoon wind and rainfall data, and high-precision topographic data. Using county-level administrative regions as spatial units, this study employed various methods, such as time-series statistical analysis, gravity model, geographical detector, spatial correlation analysis, and geographically weighted regression, to analyze the spatiotemporal distribution patterns and influencing factors of typhoon disaster conditions in China from 1978 to 2020. The findings of this study are as follows: (1) The number of deaths and missing persons, quantity of damaged housing, death, and missing rate per million people, and proportion of direct economic loss to GDP caused by typhoon disasters have all shown a declining trend, indicating significant achievements in disaster prevention and mitigation efforts. (2) The center of gravity of typhoon disaster-related losses has shifted southward, corresponding with the economic development of coastal regions, demonstrating a reduced disaster impact in coastal areas and an increased impact in inland areas. (3) Wind and rain induced by typhoons are the primary driving factors of disaster conditions, and topographical factors are also drivers of casualties and crop loss. (4) The two major regions, Zhejiang-Northern Fujian and Western Guangdong-Eastern Guangxi, exhibit significant characteristics of disaster condition agglomeration, closely related to typhoon activity patterns and levels of economic development. (5) There is a negative correlation between the gross local product and disaster conditions in some areas, reflecting the role of socioeconomic development in enhancing the capacity for disaster prevention and mitigation.

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

Against the backdrop of rapid global climate change, the frequency and severity of storm surges in coastal areas are increasing, particularly in tidal river segments that are affected by storm surges and upstream river flooding. Although existing storm surge models have introduced a variety of different boundary settings, the boundary conditions provided are limited and cannot meet the current generalization needs of complex hydraulic engineering projects in China. This study considered the Feiyun River Basin as the research subject and coupled the upstream hydrodynamic model IFMS with the oceanic storm surge model ADCIRC. By utilizing the strengths of both models, a flood evolution model for the estuarine tidal river segment was established, enabling the spatiotemporal simulation of tidal levels in the Feiyun River tidal segment. The model not only effectively considers the impact of storm surge propagation at the estuary on flood evolution in the tidal river segment, but also the effect of upstream river flooding on the area. The study first validated the model with Typhoon Meranti in 2016, where the simulation results showed a high degree of agreement with the observed data series and errors were within acceptable limits. Flood processes at the Ruian, Mayu, Bishan Liqiao, and Dongtou tidal stations during Typhoons Doksuri and Khanun were simulated. The results show that the peak flood errors at all four stations were below 0.30 m, with Nash coefficients >0.80, indicating the model's capability to accurately reflect tidal level fluctuations and effectively contribute to disaster prevention and mitigation efforts in estuarine tidal segments. Finally, the study analyzed the impact of the driving forces of the upstream and downstream boundaries on tidal level predictions at three stations (Ruian, Mayu, and Bishan Liqiao). It was concluded that, compared to Mayu and Bishan Liqiao stations, the influence of the upstream boundary on Ruian can essentially be ignored, suggesting that the error from the upstream boundary under the influence of Typhoon Khanun is negligible for predicting errors at Ruian. The degree of the impact of the downstream boundary fluctuations on the three stations, from largest to smallest, was Ruian, Bishan Liqiao, and Mayu. Compared to the changes in the upstream boundary, the downstream boundary had a greater overall impact on all three stations. Additionally, when the downstream boundary changed by the same magnitude, the variation in low tide levels showed a decreasing trend from downstream to upstream, whereas the variation in high tide levels, although following the same trend, did not show a significant difference between the three. In summary, compared to the upstream boundary, the downstream boundary had a greater impact on tidal-level predictions at the three stations. The result shows that the lower boundary has a greater impact on the tidal level forecasts at three stations compared to the upper boundary. The study not only provides a new method for tidal river flood simulation in coastal urbanized areas but also offers directions for improving model simulation accuracy through analysis.

Social and economic losses from typhoons are increasing owing to climate change. It is of practical significance to correctly understand new characteristics and trends in typhoon activity. Based on the best track dataset of tropical cyclones from the China Meteorological Administration, the temporal and spatial variation characteristics and evolution law of northward-moving typhoons from 1949 to 2022 were analyzed using the linear trend, Mann-Kendall test, and wavelet analysis method, and the impacts of the El Niño-Southern Oscillation (ENSO) on typhoon activities were also discussed. The results showed that: (1) 275 northward-moving typhoons occurred during the past 74 years, with an average of 3.7 per year. The interannual fluctuation in typhoon frequency was large, and the upward trend was not significant. The proportion of northward-moving typhoons to the total number of generated typhoons in the Northwest Pacific was between 2% and 30%, showing a significant upward trend. (2) Northward-moving typhoons were mainly generated from July to September, accounting for approximately 88.4% of the total typhoons. The highest number of typhoons entering the defined area was 114 in August. The life-cycle intensity of northward-moving typhoons is dominated by high-intensity grades, such as super typhoons and typhoons. Among them, super-typhoons accounted for 30.5% of the total number of northward-moving typhoons, and the intensity of typhoons and above grades exceeded 70% of the total amount. In recent years, the probability of high-intensity northward-moving typhoons has increased. (3) A total of 159 northward-moving typhoons landed in China over 74 years. Most of the turning-track typhoons made landfall in Taiwan, Fujian, and Zhejiang, whereas the landing locations of landed disappearing-track typhoons made landfall more northerly. Most unlanded turning-track typhoons turned eastward near 30°N and 125–130°E, showing a significant upward trend. The generating positions of the northward-moving typhoons were mainly concentrated in the ranges of 10—20°N and 130—150°E, with a density of 4.65/10,000 km². The central generation position of the landed northward-moving typhoons was 4.2° more westward than that of the unlanded typhoons. The latitude of the central generating position of the disappearing typhoons was 2.1° northward compared to that of the turning typhoons. (4) The Niño3.4 index had significant negative and positive correlations with the frequency and life-cycle intensity of northward-moving typhoons, respectively, and it also had an obvious effect on their generating positions. There were 4.5 northward-moving typhoons in the La Niña year, which was 1.67 times the El Niño year. However, the intensity of northward-moving typhoons generated during El Niño years was significantly higher than that generated during La Niña years, and the intensity of northward-moving typhoons increased with the Niño3.4 index. The central generating position of northward-moving typhoons during La Niña years was 5.8° northward and 12.4° westward compared to that during El Niño years, which was closer to China. This study provides a basis and reference for strengthening the risk management of typhoons and improving the efficiency of disaster prevention and reduction.

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

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

Typhoon gales can lead to accidents such as the breakage and collapse of transmission line towers, affecting the operational safety of power systems. Therefore, the risk assessment of transmission line towers during typhoon disasters is important. Taking all transmission towers in Zhejiang Province as an example, a typhoon disaster vulnerability assessment model for transmission line towers based on "excess loss" for both continuous and discrete variables was proposed based on tower attributes, geographical information, and typhoon disaster data. Utilizing the reanalysis data of typhoon parameters and wind fields from the past 68 years, a typhoon gale hazard assessment model was established based on the extreme value theory, and the statistical parameters of wind speed intensity under typical scenarios were analyzed. Furthermore, based on the regional disaster system theory and through a coupling analysis between typhoon gales and tower vulnerability, a risk assessment model for typhoon transmission line towers was developed. The results indicate the following: (1) the hazard of typhoon gales decreases from southeast to northwest, with differentiated distributions due to the local terrain and other factors. As the return period increased, a nonlinear increasing trend was observed. Taking the maximum wind speeds with a return period of 20 years and 100 years as examples, the wind speed intensities across Zhejiang Province range from 23.5-50.9 m/s and 32.6-68.9 m/s, respectively. Therefore, different wind resistance strategies should be adopted based on specific prevention requirements. Notably, the typhoon parameter wind field model used in this study had certain errors compared to the actual measured wind speeds. Therefore, in practical applications, particularly in complex terrain areas, it is necessary to combine local observational data for model calibration and application. (2) The comprehensive vulnerability of towers under the influence of typhoons generally exhibits a distribution pattern that is high in the south and low in the north, which is closely related to the terrain. Regions with high vulnerability (>1) were mainly located in central and southern Zhejiang and the coastal areas. Moderate vulnerability (0.5-1) is distributed in the Jinqu Basin and the offshore areas from Taizhou to Ningbo. The northeastern plain of Zhejiang had a relatively low tower vulnerability (<0.5). (3) The risk of transmission line towers generally exhibits a pattern of being high in the south and low in the north, with higher risks along the coast and lower risks in inland areas. There are significant local differences. In southeastern Wenzhou, Taizhou, and southern Lishui, the risk level of the towers was the highest. The southern part of Ningbo, Zhoushan, western Quzhou, and eastern Jinhua had the second highest risk. Additionally, some areas in Shaoxing, Huzhou, and Hangzhou have towers with higher risks that need to be addressed, which is consistent with the actual investigation findings. These results provide the necessary technical support for disaster risk assessments. Risk management plans should be adopted based on regional differences.

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

Rainfall and sea surface temperature grid data, as well as rainfall data from coastal stations in China, were used to obtain the spatiotemporal response characteristics of summer rainfall along the Chinese coast to ENSO and analyzed interdecadal changes in summer rainfall. The results show that: (1) Summer rainfall along the coast of China was significantly affected by ENSO and can be divided into three regions, with Lianyungang and Yunao as the boundaries. The Niño3.4 index was negatively correlated with summer rainfall along the Bohai and Yellow Sea coasts, positively correlated with that of the East China Sea coast, and not significantly correlated with that of the South China Sea coast. (2) On an interdecadal timescale, the relationship between summer rainfall along the coast of China and the Niño3.4 index was unstable. The negative correlation between summer rainfall along the Bohai and Yellow Sea coasts and the Niño3.4 index was significant before and after 1980 and 2010, respectively. The positive correlation along the East China Sea coast became insignificant after the 1980s, whereas the correlation along the South China Sea coast remained insignificant. (3) On the interdecadal timescale, the summer Niño3.4 index, winter Arctic Oscillation (AO) index in the previous year, and spring Antarctic Oscillation (AAO) index in current year were significantly negatively correlated with summer interdecadal rainfall along the Bohai and Yellow Sea coasts and positively correlated with summer interdecadal rainfall along the East China Sea coast. Summer interdecadal rainfall along the coast of the South China Sea was significantly negatively correlated with the spring Arctic Sea ice index in the current year. Regarding the Niño3.4 index, the high sea surface temperature in the Central and Eastern Pacific triggered a negative Pacific-Japan-type interconnection wave train in the 500 hPa geopotential height field, resulting in a decrease in interdecadal rainfall along the Bohai and Yellow Sea coast and an increase in interdecadal rainfall along the East China Sea coast. When the winter AO in the last year and spring AAO in the current year were in a positive phase, the abnormal anticyclone in the southern part of Baikal Lake at 850 hPa wind field guided the airflow in the mid to high latitudes southward, causing a weakening of the East Asian summer monsoon and a decrease in interdecadal summer rainfall along the Bohai and Yellow Sea. In addition, the strong, westward position of the subtropical high pressure in the northwest Pacific increases the upward movement, increasing interdecadal summer rainfall along the East China Sea coast. The interdecadal variation of spring Arctic Sea ice stimulates the opposite atmospheric circulation pattern that induced interdecadal variation of summer rainfall along the South China Sea coast in the 850 hPa wind and 500 hPa geopotential height fields.

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

China has numerous islands and reefs with complex terrain that are heavily impacted by tropical cyclone disasters. High-resolution tropical cyclone wind-field simulations are beneficial for representing the spatial variations in wind speeds. It is important to conduct high-resolution simulations on relatively small islands and reef areas. To explore the differences in tropical cyclone wind field simulations at various spatial resolutions in the island and reef areas of China, this study compared the modeled wind fields of historical tropical cyclones in China's island and reef areas, which have complex terrains, including plains, peaks, valleys, and cliffs, at three spatial resolutions of 1,000 m, 90 m, and 30 m. The wind fields were modeled using land cover and elevation data of the three spatial resolutions as inputs and validated against observed winds at eight stations. Comparisons were made regarding the differences in wind speeds of tropical cyclones with a 100-year return period at three spatial resolutions. The results showed that: (1) the 30 m resolution achieves the best accuracy, with a root mean square error of 4.28 m/s, lower than those of 90 m and 1 km by 0.08 m/s and 1.04 m/s, respectively. (2) Different spatial resolution simulations showed that wind speed errors were related to terrain types. For example, on Zhujiajian Island, located in Zhoushan City, the 30 m resolution captured the spatial heterogeneity of winds better than the other resolutions, especially for mountainous, valley, and cliff terrains. Comparisons between the simulated wind speeds at 90 m and 1,000 m resolutions versus those at 30 m resolution indicate that the differences in the simulation percentages are as follows: 6.57% and 7.61% for peak terrain, 21.28% and 17.35% for valley terrain, and 22.85% and 23.37% for cliff terrain, respectively. Additionally, the 30 m simulation was more sensitive to transitions between windward and leeward slope terrains. (3) For the 100-year return-period wind speeds, the 30 m resolution produced the highest values and largest spatial variations. On Zhujiajian Island, the maximum wind speeds at 1,000 m, 90 m, and 30 m resolutions were 71.13, 73.18, and 79.97 m/s, respectively, and standard deviations of 3.88, 3.72, and 7.18 m/s. This study demonstrates the importance of using high-resolution data to simulate tropical cyclone winds in complex terrain. However, this study had some limitations. First, the terrain correction factors need to be optimized further. The assessment method provided by the building codes tended to overestimate the impact of the terrain correction factors. In the future, more accurate terrain correction factors could be obtained using computational fluid dynamics and wind tunnel tests. Second, because of the limited types of land cover data used in the calculations, the subdivision of certain land types when calculating the surface roughness is not sufficiently detailed. Additionally, different years of land cover data were not incorporated, making it challenging to reflect the variations in surface roughness. Remote sensing can be used in the future to determine the high-resolution spatial distributions of surface roughness.

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

Typhoons and their associated disaster chains pose serious threats to the lives and property of coastal residents, and they remain a focal point for research and response. Previous studies on typhoon disaster chains often employed high-dimensional symmetric Copula models to establish the joint distribution of multiple hazard factors, however they failed to explore the complex nonlinear and asymmetric dependencies among them. This study aimed to depict these complex relationships more comprehensively and efficiently to provide a more accurate typhoon hazard assessment. Focusing on Zhoushan, a city comprising numerous islands in Zhejiang Province that faces multiple typhoon threats, this study employed the C-Vine Copula function to model the complex dependencies among "strong wind-rainstorm-storm surge" in the typhoon disaster chain. Utilizing observational data from 1979 to 2018, this study involves three main steps: first, fitting the marginal distribution of each hazard factor and identifying the best one from Lognormal, Gamma, GEV (Generalized Extreme Value), and Burr functions based on the K-S test; second, fitting the bivariate joint distributions of wind speed-rainfall and wind speed-storm surge using Gaussian, Clayton, Gumbel, Frank, and Joe Copula functions, and determining the best fit based on the AIC (Akaike Information Criterion); and finally, estimating the trivariate joint probability distribution and corresponding return periods for wind speed-rainfall-storm surge using the C-Vine Copula function. This revealed (1) a strong correlation between wind speed and rainfall observed within regular value ranges (non-extreme conditions), were best represented by the Frank Copula, In addition, wind speed and storm surge exhibit an upper-tail dependence, best captured by the Gumbel Copula. (2) The rainfall distribution under certain wind speed conditions revealed dual peaks, whereas the storm surge distribution maintained a uniform pattern, with the best joint distribution fitting the Gumbel Copula. (3) Considering a 100-year return period for individual variables, the bivariate return periods for wind speed-rainfall and wind speed-storm surge events were significantly reduced to 29 and 30 years, respectively, while the trivariate return period for the wind speed-rainfall-storm surge combination was further reduced to 17 years. Overall, the C-Vine Copula function effectively characterizes the complex nonlinear and asymmetric dependencies among the typhoon disaster chain "strong wind-rainstorm-storm surge", reducing high-dimensional parameter estimation complexity. This method provides new insights for constructing joint probability and return period models for multiple hazard factors and offers a scientific basis for disaster risk assessment and management strategies. Therefore, this enhances the accuracy of disaster prevention and mitigation efforts. Additionally, the application of the C-Vine Copula assists to deeply understand the mechanisms and development processes of natural disasters, providing new tools for on-site emergency response and decision-making.

China is frequently affected by tropical cyclones, which can lead to severe economic losses. Rapid disaster loss assessment is crucial for effective emergency response. A variety of factors affect tropical cyclone disaster losses, which can be roughly categorized into hazard, exposure, and vulnerability. In the past, traditional statistical methods were used as the main tools for disaster loss assessment. To explore the potential of machine learning models, we explored five algorithms: the Light Gradient Boosting Machine (LightGBM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Back-Propagation Neural Network (BP). The maximum gust wind and rainfall of tropical cyclones were selected to represent hazards, fixed capital stock data were used for the valuation of exposure, and the GDP of each county was collected to reflect capacity or vulnerability. In addition, river network density data were used as a simple proxy to demonstrate the contribution of flood-induced tropical cyclone rainfall. The relationship between these input variables and disaster loss at the county level was developed based on the data of 81 tropical cyclone events from 2009 to 2020 in Fujian Province. The performance of these models was compared using accuracy, precision, recall, and F1 scores. The accuracies of the LightGBM, RF, XGBoost, SVM, and BP models were 0.794 6, 0.772 6, 0.762 8, 0.251 8, and 0.268 1, respectively. The main findings are as follows: (1) The performance of the ensemble learning algorithms (RF, XGBoost, and LightGBM) was higher than that of the individual classifiers (BP and SVM). The LightGBM model exhibited the best performance, with accuracy, precision, recall, and F1 scores >79%. (2) Maximum hourly rainfall and maximum wind gust are two of the most important loss-inducing factors, and fixed capital stock is a better proxy for disaster exposure than GDP. (3) The modeled losses are consistent with the actual losses under different but typical tropical cyclone events, indicating that the models can be applied to future tropical cyclone events impacting Fujian Province. However, this study had some limitations. First, some natural hazards, such as floods, storm surges, and waves, were not fully considered, which introduced uncertainty into the model results. Second, the emergency response capacity and actual actions taken among counties may have varied dramatically and were neglected due to data unavailability. In the future, hazard and vulnerability variables should be obtained to extend the model inputs. In addition, whether the model parameters trained with data from Fujian Province can be applied to other provinces remains unaddressed. In the future, to develop an operational model for the whole of coastal China, county-level data of all typhoon-prone areas in China with long-term time series are needed.

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.

Infrastructure and economic networks can be used to describe different dimensions of urban systems, and a close relationship exists between them. Therefore, it is important to study the dynamic coupling relationship between them to promote the formation and development of urban networks. Relevant studies have compared and analyzed the evolution characteristics of urban network structures from different dimensions; however, relatively few studies have focused on the dynamic coupling relationship between high-speed rail and remote investment networks. The formation and development of high-speed rail networks has become a key factor affecting remote investment networks, and the layout of a remote investment network also affects the development of a high-speed rail network. To this end, we used high-speed railway operation service data and related transaction data of listed companies from 2008 to 2023 to construct high-speed railway and remote investment networks reflecting intercity high-speed railway and enterprise remote investment connections, respectively. QAP correlation analysis was used to explore the overall correlation between the two networks. Using the quadrantal diagram method and the coupling coordination degree model, we discuss the spatiotemporal coupling coordination of the two networks, identify the types of cities and urban connections, and propose operational planning suggestions for cities and high-speed railways. The results indicate the following: 1) Both the scale and density of the high-speed rail network and the off-site investment network show a rapid growth trend, and the expansion of the high-speed rail network is significantly faster than that of the off-site investment network. There is a significant positive correlation between high-speed rail and the remote investment network as a whole, and the degree of correlation first increases and then decreases. 2) In terms of space, cities with the simultaneous development of high-speed rail and remote investment networks are primarily concentrated in the administrative and economic centers of the eastern region. However, cities with lagging high-speed rail networks are mainly located in non-transportation hub cities in the economically developed areas of the Pearl River Delta, Dalian, and Urumqi. Moreover, cities with advanced high-speed rail networks are mainly centered in the central and eastern regions around the main high-speed rail lines. 3) Cities with synchronous development of high-speed rail and remote investment networks are mainly located in developed cities within the five major urban agglomerations. The pairs of cities with lagging high-speed rail networks are mainly located between the core cities of different urban agglomerations. Pairs of cities with advanced high-speed rail networks are typically positioned between cities that are closer together and contain at least one city with a less developed economy. The relevant research results can provide policy support for China's high-speed rail operation planning and urban system construction.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.