Accurately grasping the patterns of population dynamics within cities can help promote coordinated regional development and optimize the spatial structure of society. Most of the existing studies focus on the total population and distribution changes at the macro scale, but lack of attention to the process of population dynamics caused by intracity relocation, and its measurement methods and characteristics are yet to be explored. Based on cell phone signaling big data and taking Wuhan City as an example, this study carried out an empirical analysis by constructing a three-dimensional indicator system of scale-direction-movement for population dynamics, applying cluster analysis to analyze the characteristics of population dynamics at the neighborhood scale caused by intracity relocation, and exploring the comprehensive characteristics of population dynamics changes and differentiation patterns. The results show that: 1) Population dynamics from the central city to the suburban areas have the scale characteristics of highly active→moderately active→inactive, directional characteristics of roughly balanced in and out→seriously imbalanced, and dynamic/static characteristics of static-oriented→dynamic-oriented. 2) There are five comprehensive types of population dynamics in the Wuhan metropolitan area, of which the highly active-growth-dynamic type and the highly active-loss-weak dynamic type are mainly interspersed in the core areas of the central urban area and the suburban area clusters; the moderately active-slight loss-weak dynamic type is mainly distributed in the periphery of the above two types; and the inactive-slight growth-strong dynamic type and the inactive-balance-dynamic type are distributed at the edge of the central urban area and the suburban area clusters. 3) The comprehensive types of population dynamics within the Wuhan metropolitan area have a core-periphery nested structure: The spatial differentiation of population dynamics between the central urban area and the peri-urban areas is mainly related to location and the quality of the living environment; within the central urban area, the spatial differentiation of population dynamics between the central city and peri-urban areas is mainly related to location and the quality of the living environment; the spatial differentiation within the central city and peri-urban areas is mainly related to the development and type of industries. This study expanded the theory and methods of the study of population migration and population change, and provides a reference basis for optimizing the social and spatial structure of urban society, and for fine-tuning the policy of residential space supply.

Residential segregation is the market-oriented manifestation of unbalanced urban resources allocation. Existing literature has not paid enough attention to the residential space differentiation of tenant groups. Renting as the main residential form of migrant population and young people in large cities, its spatial differentiation reflects problems such as spatial deprivation, spatial exclusion, and the disconnect between different socioeconomic classes, which may impede equal access to public services in large cities. Taking the 10 core administrative districts of Beijing as an empirical case, this study divided public service facilities into local level and district level according to the potential service catchment area, applying the spatial lag model to analyze the impact of public service provision at each level on the residential segregation of tenant groups. The findings are: 1) A significant portion of the subdistricts within the study area show significant residential segregation. 2) The spatial distribution of rent price levels and the residential segregation of rental groups are significantly different. The rent price levels are distributed in a stratified circle from the center outwards, while the residential dissimilarity index for tenants (RDIT) is distributed in a sandwich-like pattern of high in the inner city-low in the middle-high in the outer parts. 3) There are large differences in the impact of different levels of public service facilities on the residential segregation of renters. At the local level, negative correlations are observed between kindergarten density, accessibility to urban rail transit station and residential segregation among tenant groups. High school density exhibits a positive correlation with the residential segregation of tenant groups. In contrast, the relationship between the density of four public services (sports facility, park/urban square, medical facility, and top secondary school) at the district level and the residential segregation of the tenant groups is not significant. Drawing from the research results, this article proposed policy implications aimed at optimizing housing choices and addressing the supply and demand dynamics of public services for tenant groups, which provides a scientific basis for the rational distribution and spatial planning of urban public service facilities and rental housing.

Under the background of the new type urbanization, accurately grasping the changes in family migration patterns is of great significance for understanding the pattern of change of migration in China and promoting high-quality development of urbanization. Based on the data from the 2012 and 2018 China Migrant Dynamic Survey and related statistics of cities, this study analyzed the characteristics of family migration and influencing factors by using descriptive analysis and multi-level regression models. The results show that: 1) The average size of migrant population households is increasing, and family migration has been and will continue to be the dominant form of migration for a significant period of time. 2) Changes in the patterns of family migration have mainly manifested in the decline in semi-family migration and the emergence of complete family migration, demonstrating a trend of continuity. 3) Over time, the process of family migration has become more complex, and the reunion of the migrant population's family members requires more batches of migration; the larger the family size and the more complete the family migration is, the more batches of migration are required to achieve family reunion. The modeling results show that the characteristics of both the destination areas and the migrant population at the individual level affect family migration patterns. Individual and family characteristics of the migrant population and their mobility characteristics have always been important factors that influence family migration; at the city level, the influence of the level of urban socioeconomic development has undergone an important shift from insignificant to positively significant over time. In addition, complete family migration has always been affected by the conditions of the urban housing market and the level of public services, while semi-family migration has been mainly influenced by the rank of the city in the urban hierarchy.

Rural industrial heritage, which integrates rural historical value, technological value, social value, and artistic value, serves as an important carrier of rural industrial culture, and has witnessed the significant development journey of rural industries. In recent years, various regions have actively promoted the integrated development of cultural and tourism industries, and the creative connection between cultural tourism and rural industrial heritage has provided new ideas for rural revitalization. Studies have found that the development model of "tourism+" centered on rural industrial heritage is the contemporary representation of spatial practice under the interaction of multiple subjects. This study proposed a "subject-space" approach to analyze the specific connotation of the new endogenous development model through exploratory case studies. The results indicate that: 1) The interaction of multiple subjects has broken through the stable structure of traditional acquaintance society and reconstructed the unique subject-space interaction relationship in rural industrial heritage sites through multi-dimensional practices of production-living-ecological spaces. 2) The spatial production of rural industrial heritage sites is a process of the joint efforts of external forces such as government power and cultural capital and the cultural subject value of local communities, which transform rural industrial heritage sites into cultural tourism consumption spaces and promote the overall renewal of rural industrial society. 3) The new endogenous development path endows rural society with a new connotation. The interactive connection between subjects and spaces transcends the dilemma of cycled interpretation of traditional local value, incorporating more peripheral elements, and realizing the renewal and reconstruction of rural society in new dimensions. The evolution of rural industrial heritage sites supported by tourism is not only a new paradigm for rural revitalization but also a scientific demonstration of the reactivation of industrial heritage in rural areas.

Strengthening the research on the change in resilience and adaptation strategies of oasis rural regional system in arid areas under the impact of various factors is beneficial for the sustainable development of agriculture and rural areas. In response to the shortcomings of existing research on rural resilience, which cannot fully reflect the dynamic change characteristics of rural regional systems, and pays little attention to the scale effects and spatial type differences, this study took Ganzhou District, Zhangye City, Gansu Province, an oasis area in the middle reaches of the Heihe River as an example to construct the county adaptative resilience and township coping resilience measurement systems, analyze the resilience evolution characteristics and types differences, and propose adaptation countermeasures for improving resilience at different scales. The results show that: 1) Since 1990, the cumulative effects of county-level factors of rural areas showed a "S"-shaped process of change and an olive-shaped interannual change amplitude. The stability of social and economic systems is stronger than that of ecosystems. Rural development has gone through the stages of reorganization-early development (1990-2008), rapid development-protection (2009-2016), and protection-release (2017-2020 ). The adaptive resilience showed a change of slow rise-rapid growth-stagnant growth, and ecology is the main constraint dimension for resilience improvement. 2) Since 2011, the coping resilience of townships has fluctuated greatly and has shown a downward trend. Townships that mainly focused on large-scale grain production and animal husbandry have a higher ability to resist risks, while townships with a combination of richer water and soil resources have stronger adaptability and innovation and transformation capacity. Developing modern large-scale agriculture and multi-functional characteristic agriculture is conducive to the construction of resilient rural areas, and innovation and transformation ability is the main constraint dimension for resilience improvement. 3) Increasing ecological protection and restoration efforts in counties, strengthening ecological conservation functions, optimizing and adjusting the industrial structure of townships, exploring the diverse values of factors, innovating water rights allocation and management systems at multiple scales, and improving rural water use efficiency are the key adaptations for enhancing rural resilience at the current stage.

The improvement of well-being stands as one of the ultimate goals of transport policy. In recent years, exploration of the relationship between travel behavior and well-being has gained increasing attention in geography and transportation research. Numerous studies have demonstrated that travel has significant impact on well-being. However, the mediation effects of social networks in the relationship between travel and well-being remain unclear. To bridge this gap, this study focused on the mediating role of social networks in the relationship between travel and well-being. Using data from a household survey conducted in the urban area of Nanjing City in 2019, this study employed regression analysis and mediation effect analysis to comprehensively unravel the mechanism of impact between travel, social networks, and well-being. The findings show that the frequencies of both traveling by car and by public transport have significant positive influence on hedonic and eudaimonic well-being, with the frequency of traveling by car exhibiting a more pronounced effect. The results of mediation effect analysis reveal that social networks play an important mediation role in the relationship between travel and well-being, and the effects vary between different travel modes. Notably, the mediation effect of social networks is significant in the impact of the frequency of traveling by car and travel distance on well-being, yet appears inconsequential in the relationship between frequency of traveling by public transport and well-being. This study investigated different impact paths of three dimensions of travel characteristics on well-being. By examining the impact mechanisms of travel behavior on well-being through the lens of social networks, this study sought to comprehend how the societal value of travel influences residents' well-being. Travel not only enhances individual hedonic experiences and holistic development through the augmentation of social networks but also contributes to the long-term accumulation of social well-being, thereby fostering an overall improvement in the social environment. Consequently, this research offers valuable insights for urban transportation policies to enhance social inclusion and well-being. Given the distinctive characteristics of the relationship between residents' travel and well-being in the current urban development context and the sociocultural landscape of China, it becomes imperative to account for the social effects of travel behavior and residents' well-being in transportation policies. Hence, there is a pressing need for research on the nexus between travel, social network and well-being among urban residents in Chinese cities.

Under the background of increasing population mobility, the environmental health problem has become an important issue, which is closely related to people's well-being, social justice, and sustainable development. Combining the environmental health disparity concept and the research paradigm of spatiotemporal behavior, this study empirically explored environmental exposure of daily activities and disparities in mental health effects between floating and registered populations in Guangzhou City, China. A linear regression model was employed to analyze and compare the impacts of multidimensional environmental exposures (natural, built, and social environments) derived from the daily activity context on the mental health of floating and registered populations, after controlling for individual characteristics. The research findings show that: 1) The mental health of the floating population is worse than that of the registered population. Compared with the registered population, the floating population spends more time on family and personal affairs and work, whereas takes less time on leisure and physical activities. For the floating population, "going out early and coming back at dusk" and "having activities close to the residential neighborhood" are common. Also, the spatiotemporal characteristics of the daily activities of the floating population (i.e., frequency, distance to home) are strongly correlated with their mental health. 2) The floating and registered populations have different levels of multidimensional environmental exposures. The influence of multidimensional environmental exposures on the mental health of the floating population is greater than that of the registered population. Specifically, some environmental variables (i.e., green space coverage, fitness facility density, and recreational facility density) are positively correlated with the mental health of floating population, but other environmental variables (i.e., noise, public transit station density) are negatively correlated with their mental health. Social interaction only plays a significant role in promoting the mental health of the floating population. To improve the mental health of floating and registered populations, this article provided population-specific and differentiated strategies and suggestions on urban planning, environmental optimization, and allocation of public service resources.

Based on the measured precipitation stable isotope data and related meteorological data in Lanzhou City from April 2019 to October 2022, this study used the HYSPLIT backward trajectory model to systematically examine the characteristics of variation of hydrogen and oxygen stable isotopes of precipitation and the difference of isotopes between day and night under different types of precipitation events (convective precipitation, stratiform precipitation), and trace the water vapor sources. The results show that: 1) Both δ²H and δ¹⁸O in precipitation presented a trend of enrichment and then depletion, while d-excess in convective precipitation showed a trend of depletion and then enrichment during the daytime and continuous depletion at night, and d-excess in stratiform precipitation all showed a trend of depletion and then enrichment. 2) The local atmospheric water line slope (8.01) and intercept (15.55) of convective precipitation at night were the largest and closer to the global atmospheric water line, while the local atmospheric water line slope (6.81) and intercept (4.08) of stratiform precipitation during the day were the smallest, indicating that stratiform precipitation was more susceptible to evaporative fractionation. 3) There was a positive correlation between air temperature and δ¹⁸O values, and the influence on the daytime stratiform precipitation isotope was most significant (r=0.59, P<0.01). There was a significant negative correlation between relative humidity and δ¹⁸O values, and the most significant effect was on the isotopic values of convective precipitation at night (r=-0.52, P<0.01). There was no significant correlation between precipitation and precipitation isotope during the day, but a negative correlation at night (r=-0.26, P<0.05). 4) In the summer half year (April to October) in Lanzhou, the precipitation-producing water vapor mainly comes from Central Asia, Mongolia, and other northern regions and is transported to Lanzhou through the control of the westerlies and continental air masses, and only a small part of it is affected by the southwest monsoon. The results of this study can provide a new perspective for exploring the key drivers of precipitation isotope change in arid areas, and have important significance for modern climate research and water resources management.

Urban ventilation corridors play a critical role in mitigating the heat island effect and air pollution and the construction of low-carbon cities. This research utilized a variety of data, including meteorological data, basic geographic information data, and satellite remote sensing data, to calculate urban ventilation indicators in the main urban area of Hefei City. Four scenario evaluation systems were established based on different combinations of indicators, including ventilation potential coefficient (VPC), VPC + high temperature (LST), VPC + haze (PM_2.5), and VPC + high temperature (LST) + haze (PM_2.5). Subsequently, we employed the least-cost path model to construct ventilation corridors and used Pearson correlation models to assess ventilation efficiency under various scenarios. The findings revealed that: 1) We proposed and validated a new paradigm for constructing ventilation corridors—constructing ventilation corridors based on a composite index evaluation system consisting of the VPC and climatic indicators (LST/PM_2.5/LST+PM_2.5). The VPC was determined by sky view factor and roughness length indicators, while the selection of climate environmental indicators was based on specific climate environmental issues faced by the city. 2) The main urban area of Hefei City experiences dominant southeast winds in the summer and northeast winds in the winter. Areas with high values of sky view factor and roughness length indicators are concentrated outside and inside the second ring road, respectively. High LST values are observed in Jingkai District and Baohe District, while high PM_2.5 concentration values are found in the old urban area, Baohe District, Xinzhai District, and Yaohai District. 3) The paradigm proposed in this study for constructing the ventilation corridor demonstrated high efficiency. Specifically, under the VPC+LST+PM_2.5 paradigm, the coefficients of correlation between wind speed level in the ventilation corridor and LST, as well as PM_2.5 concentration, were -0.75 and -0.85, respectively. These absolute values were higher than the correlation coefficients of -0.68 and -0.82 obtained from the traditional paradigm based on building form indicators for the ventilation corridor. 4) The main urban area of Hefei City featured a two-tiered ventilation corridor management system, designated as "1+7". This structure permitted the implementation of tailored control strategies within the primary and secondary regulatory zones. This study aimed to provide strategic guidelines for improving urban climate resilience at the built environment level.

Ali Prefecture of Xizang, China is located in the middle and western sections of the China-India border, where the high altitude, continuous mountains, and crisscrossing valleys pose many restrictions on military activities. It was in this region that Chinese Xizang fought against Jammu's invasion from 1841 to 1842. The result of this war is closely related to the current border dispute between China and India. From the perspective of military geography, the military geographic pattern of Ali region underwent significant changes in the late Qing Dynasty. The three locations of Dongti, Chushule, and Shibuqi became the frontline of the military confrontation. At the beginning of the war, the Jammu army quickly passed through these three key locations and carried out a surprise attack. Xizang's army was forced to exchange space for time, and stroke a heavy blow to Jammu's army in Duoyu, recovering all lost territory. During the war, the main bases of operation of the Xizang army were located in the direction of Gorkha (Nepal). When they arrived in Leh, they were already over 2000 km away from their base. The Xizang army's attack was clearly unsustainable based on the analysis of time and distance factors. Thereby, the previous military structure of core-periphery was dramatically reversed, forming a new military geographic situation. When the Xizang army's attack exceeded its "peak", their situation shifted from advantaged to disadvantaged, forcing them to withdraw from Ladakh. This article aimed to reveal the relationships between wars and military geographic environments through military geographic analysis, and then identify key areas for war preparation and implementation, which is of great significance for the current national defense construction. Finally, the article put forward three recommendations for border security and national defense construction in the Ali region.

Knowledge-intensive business services (KIBS) is considered a key driver of innovation and economic development in the knowledge economy era as an industry that provides knowledge and technology services. With the rise of the knowledge economy and the advanced industrial structure in the 1990s, scholars in China and internationally began to focus on the spatial distribution of KIBS and the process of knowledge diffusion, as well as its significant role in promoting industrial integration, regional innovation, and economic transformation. Since the twenty-first century, rapid economic globalization has propelled the application research of KIBS in geographical fields such as national and regional innovation, industrial clusters, and innovation networks. Under the new situation of globalization and the new research paradigms of economic geography, research on the integration of KIBS and various research paradigms of economic geography, the mechanism of impact of KIBS on the new information technology revolution and new quality productivity, the mechanism of impact of KIBS on industrial upgrading and regional transformation from the perspective of global-local interaction, global-local production network, and multiscale innovation space reconstruction are relatively insufficient. Based on the current research progress, the authors reviewed the key publications on KIBS in the field of geography in China and internationally, summarized the spatial and temporal distribution characteristics of KIBS publications, and used the bibliometric analysis software CiteSpace 6.2.R6 to make a visual analysis of research hotspots in this field. We systematically summarized the research hotspot content and research trend of KIBS. Combined with the new situation of globalization and the major strategic issues of China's economic geography research, we put forward the prospect of KIBS geographical research focusing on KIBS and regional development transformation under the new trend of globalization, KIBS and new quality productivity, global-local innovation centers, KIBS and global-local innovation networks from the perspective of global-local interaction, and KIBS and multiscale innovation spatial coupling.

China's overseas industrial parks (COIP) are important means for implementing the Belt and Road initiative and vital strategic support for the new development pattern of "dual circulation", and have attracted increasingly more attention from the academic community. To explore the research progress of COIP, this study used the CNKI and Web of Science as data sources and the CiteSpace and VOSviewer visualization software to examine the number and distribution of publications, and identify the research teams and research hotspots of COIP research. It further elaborated on the research progress of COIP from the perspectives of economy and trade, institution and culture, geopolitics, layout and planning, and ecological environment, revealing the current problems of research in COIP and future research priorities. The main conclusions are: 1) The overall number of publications in COIP research shows a trend of first increasing and then declining, which can be divided into three stages: slow growth, rapid rise, and decline. 2) The overall research on COIP has undergone a transformation from a corporate perspective to an industrial park perspective, and then to a development perspective, mainly exploring the development models and characteristics, location choices, spatial planning, institutional culture, and ecological environment of COIP. 3) Research directions for further exploration of COIP may include promoting research on the resilience of COIP, expanding research on the relationship and scale of COIP, strengthening research on the relationship between geo-setting and high-quality development of COIP, and increasing research on the spatial layout of global COIP, as well as research on promoting green, low carbon, and sustainable development of COIP.

In recent years, machine learning models have been widely introduced into spatiotemporal travel behavior modeling and prediction research due to their superior predictive performance and flexibility, but their underlying research framework and technical routes are still unclear. This article reviewed the typical literature published in related fields from 2010 to 2022 to examine the impact of the application of machine learning algorithms on the spatiotemporal travel choice behavior research paradigm, summarize the key issues to be solved in the current application and the potential influencing factors and mechanisms that affect the effectiveness of spatiotemporal travel choice behavior modeling, and foresee the directions to be focused on in future research. The effective application of machine learning algorithms to the study of spatiotemporal travel choice behavior requires not only the support of model architectures and decision mechanisms that fit the decision scenarios, but also to overcome the inherent shortcomings of all learning processes and methods, and fully consider the impact of external research conditions on the simulation and prediction performance of spatiotemporal travel choice behavior. Existing machine learning models can already fit most spatiotemporal travel choice decision scenarios, and diversified and efficient machine learning algorithms will certainly give a strong impetus to the development of spatiotemporal travel choice behavior research. Limited model interpretability remains the fundamental reason why machine learning-based spatiotemporal travel behavior models are difficult to be widely trusted. Facing the opportunities and challenges of spatiotemporal travel choice behavior research in the era of big data, it will be an important development trend to fully integrate the respective advantages of machine learning algorithms and classical decision theories and models, while improving the simulation accuracy and model interpretability of spatiotemporal travel choice behavior.

The rate of climate change exhibits differences at daily and seasonal scales and is characterized by non-uniform warming. Particularly in the mid to high latitudes of the Northern Hemisphere, the rate of warming at night surpasses that during the day, and the rate of warming in winter exceeds that in summer. Accurately assessing the impact of non-uniform warming on the structure and function of terrestrial ecosystems represents a significant challenge in the field of global change research. This article, through a literature review, systematically analyzed the effects of non-uniform warming in winter, changes in snow metrics, and variations in photoperiod on the phenological characteristics of spring vegetation. It also discussed factors such as species specificity, geographic location heterogeneity, and seasonal compensation effects. The research indicated that seasonal changes in temperate regions have a significant impact on vegetation phenological cycle, but existing studies have shortcomings in observation experiments, mechanism understanding, and model simulation. Although controlled experiments are helpful for studying the effects of meteorological factors on vegetation, they may not fully reflect the natural conditions. Remote sensing monitoring provides a macroscopic perspective, but its data accuracy is limited by many factors, and it is difficult to capture subtle phenological changes. Ground observations provide valuable information for climate science, but the distribution of observation sites is sparse and the data uncertainty is large. In terms of the mechanism of impact, the interactions of light, temperature, and water and their effects on phenology are not fully understood, and the carry-over lag effect between seasons is not well understood either. In terms of model simulation, it is difficult to parameterize the plant phenology model, the study of parameter thresholds is insufficient, and the influence of other biotic and abiotic factors is not fully considered. These challenges limit the accuracy of predictions of plant phenological changes. Therefore, future research is needed to develop novel observational experimental methods to accurately distinguish plant responses under different environmental conditions and to validate model predictions under more natural conditions. This includes improving warming experiments, accounting for the effects of nighttime warming, and encouraging research based on global field observations. It is also necessary to strengthen the understanding of the mechanism of influence of non-uniform warming, especially the light, heat, and water requirements of spring phenology, and the complex effects of winter and spring warming on leaf phenology. In addition, research should focus on fall phenological processes and the risk of late spring frost. In terms of modeling, non-uniform warming and its associated impacts need to be incorporated into models to improve the ability to predict the response of temperate ecosystems to climate change. This includes precise measurements of the onset of ecological dormanism in trees, combined with physiological studies, and consideration of seasonal climate change effects on carbon sequestration and cycling in terrestrial ecosystem models. At the same time, the impact of seasonal snowfall should be considered and the understanding of photoperiodic effects should be deepened to assess the potential impacts of climate warming on terrestrial ecosystems, thereby enhancing our comprehension of the impacts of climate change on vegetation at the seasonal scale.