With the regional integration, the population of cross-city commuting residents is gradually increasing. This growth has led to a rise in mental health issues stemming from behavioral patterns and environmental pollution that impact these cross-city residents. This study focuses on the cross-city commuting residents between Zhongshan and Zhuhai in the Guangdong-Hong Kong-Macao Greater Bay Area. Using dynamic monitoring and tracking methods, including spatiotemporal activity diaries, portable real-time sound sensors, and GPS tracking devices, this study employs a mixed approach that combines quantitative and qualitative methods. Given that psychological stress plays a significant role in individuals' mental health, this research examines the relationship among leisure behaviors, noise environments, and psychological stress by analyzing activity units. The results indicate that the relationship between objective noise exposure and psychological stress levels at the activity level is not significant for cross-city residents. Instead, subjective noise perception acts as a mediator between objective noise exposure and psychological stress. Different leisure locations and types have varying effects on alleviating psychological stress. In Zhongshan, cross-city residents experience higher stress levels outside their community due to noisy environments despite better housing conditions, while in Zhuhai, lower noise levels during leisure activities provide a less stressful environment. The work, residence, commuting, and leisure activities of cross-city residents are interrelated. Long work hours and commuting on weekdays impose high spatiotemporal restrictions on leisure and contribute to increased psychological stress, underscoring the importance of weekend leisure activities for stress relief. However, the weekend leisure activities of cross-city residents are influenced by both spatiotemporal constraints and active adjustments. On one hand, they often face high spatiotemporal constraints and are forced into noisy leisure environments; on the other hand, they can actively adjust their weekend leisure activities, thereby achieving better leisure-related acoustic environments and effectively relieving psychological stress through cross-city leisure activities. By integrating multi-source data and mixed methods, this study provides new theoretical and methodological perspectives for understanding the relationship among noise environmental exposure, subjective perception, and psychological stress in diverse leisure contexts for cross-city populations. Additionally, it provides policy implications for relieving psychological stress and enhancing mental health for cross-city populations through offering more leisure opportunities, improving leisure environments, and minimizing travel constraints. These strategies will improve cross-city residents′ leisure environments and mental health.

As a supportive environment closely related to the daily life of residents, geographical environment exposure derived from the activity space and its influences on mood has attracted considerable attention. Some studies to date have mainly examined the direct effects of environmental exposure on mood state based on macro and static geographic contexts (e.g., residential neighborhoods, cities). However, few studies have estimated the level of environmental exposure derived from individual activity space and its direct impacts on momentary mood from a micro and dynamic perspective. They also tend to ignore the moderating effects of activity attributes on the associations between geographical environment exposure and momentary mood. To this end, this study collects measured data (real-time environments, Ecological Momentary Assessment (EMA) records, GPS trajectories, and activity logs) in various activity spaces from 131 participants in Guangzhou, China, and then employs the hierarchical linear modeling to analyze the direct effects and moderating mechanisms of "internal inherent attributes (demographic and socioeconomic characteristics)" and "external contextual factors (micro-scale dynamic environmental exposures and activity attributes)" on participants' momentary mood. The findings indicate that: (1) There are significant differences in the momentary mood of residents with different genders and education levels. (2) Compared with demographic and socioeconomic characteristics, environmental exposure (i.e., temperature, relative humidity, PM_2.5 concentrations, noise, surrounding population size, environmental safety) derived from people's activity space has a stronger explanatory power on the variations in momentary mood. Optimizing the environmental exposure in people's daily activity space can directly improve their mood state, such as appropriately raising the temperature (in winter), decreasing noise level, and enhancing environmental safety. (3) Individual activity attributes (i.e., adjustable activity, activity companion) exert significant moderating effects between some environmental factors (i.e., temperature, noise, environmental safety) and momentary mood. Thus, the positive effects of environmental exposure on people's momentary mood can be enhanced and the mood risks caused by environmental pollution can be reduced through adjusting activity attributes. This paper has significant implications for enriching the knowledge of environmental mood effects and providing more refined and humanistic strategies for activity space planning and environmental optimization.

Based on the scholarly background of promoting the concept of people-centered urban development, it is of great academic significance and application value to reconcile the logic tension between people's spatial behavior and subjective well-being in different geographical contexts. Specifically, depicting the interactive mechanism between their environmental perception and subjective well-being is utilized as the basis for urban development towards diversification and personalization, where the employed population can be regarded as the largest stable group of active residents living in the city. This paper initials the research target through the large-scale urban physical examination survey data conducted by the Ministry of Housing and Urban-Rural Development in Jinan city since July 2023 and makes steps further via structural equation modeling to examine the impact of human settlement quality perception on the cognition, behavior, and subjective well-being of the employed population. Our experimental results demonstrate the following four findings. (1) The perception of urban human settlement quality can affect subjective well-being through the mediating role of the cognition and behavior of the employed population. (2) The main factors that positively affect the subjective well-being of the employed population are the perception of the living system and the support system, and the perception of job-housing balance has a negative impact on subjective well-being. (3) The perception of urban safety accident response and emergency infrastructure setting, commuting, and road perception determine the level of perception of the employed population towards urban human settlement quality. (4) The perception of living system dominates the cognition of physical health of the employed population, and the balance between job and housing space helps to increase the frequency of fitness exercise for the employed population. The perception of the support system also increases the confidence of the employed population in commuting. This study expands the theoretical analysis and derivative mechanism of the impact of urban human settlement quality perception on the subjective well-being of the employed population, and provides decision-making basis and scientific support for people-oriented urban management.

Ensuring the equity and inclusiveness of transport systems, thereby enabling individuals to equally access convenient and reliable transport services, is the key to the construction of inclusive cities. From the perspective of transport and behavioral geography, the travel behavior characteristics of disadvantaged groups and the influencing factors have become a research hotspot. However, the internal causal relationship and complex interaction mechanism between transport disadvantage caused by geospatial imbalance, temporal constraints, and socio-economic characteristics and residents' travel behavior have not been fully explained. Based on the survey data of urban residents' built environment perception and travel behavior in Xi'an in 2022, this study analyzes the characteristics of transport disadvantage under the space-time constraints, and constructs a structural equation model to explore the mechanism and spatial heterogenicity of the impact on urban residents' travel behavior. The result reveals that: (1) The perceived transport disadvantage under the space-time constraints exhibits obvious socio-economic and spatial heterogenicity. Perceived spatial disadvantage is higher for elderly, less educated, non-car owners, and lower annual household incomes. Females and young middle-aged groups are more vulnerable to temporal constraints. Higher perceived transport disadvantage groups cluster in the suburbs. (2) Perceived spatial disadvantage caused by geospatial obstacles and uneven distribution of facilities is a key factor that affects the travel decision-making of transport disadvantaged groups. Bus accessibility, distance to metro stations, and amenity accessibility affect travel frequency by influencing perceived spatial disadvantage. (3) There is spatial heterogenicity in the impact of perceived transport disadvantage on travel frequency, with more significant direct and mediating effects in the suburbs. Perceived spatial disadvantage mediates the relationship between the built environment and individual socio-economic attributes on the travel frequency of transport-disadvantaged groups in suburban areas, while perceived temporal disadvantage significantly mediates the impact of income on resilient travel frequency. This study deepens the understanding of the influencing factors and mechanisms affecting the travel behavior of transport-disadvantaged groups. It provides valuable support and recommendations for optimizing and regulating the spatial environment and social governance strategies from the perspectives of inclusiveness and equity.

Urban rhythm theory emphasizes the intertwined relationship between time and space in cities, as well as the resultant repetitiveness and differentiation. This theoretical framework provides a new perspective for observing and understanding cities, which is an innovative research angle for addressing contemporary urban challenges. The spatiotemporal travel behavior of urban residents exhibits distinct rhythmic characteristics, which not only reflect individual lifestyle patterns but also, to a certain extent, and mirror the complexity of urban operations. It has long been one of the critical issues in urban geography and behavioral geography research. This study introduces the concept of urban rhythm and focuses on the spatiotemporal behavior of residents' non-commuting travel. Utilizing traffic analysis zones as spatial units, and mobile phone signaling data and POI (Point of interest) data, the study explores the rhythmic patterns of residents' non-commuting travel activities by integrating time series soft clustering methods based onFuzzy C-Means Clustering (FCM) with spatial analysis. Simultaneously, it employs a spatial lag model to reveal the influencing factors of the degree of membership in travel rhythm patterns. The results demonstrate that there are seven patterns of non-commuting travel rhythms for Beijing residents. Based on the differences in the frequency density and enrichment index of POIs across regions of various patterns, these seven patterns can be described as "residential-oriented", "commercial activity-oriented", "business-oriented", "mixed residential-biased", "mixed business-biased", "science, education, and culture" and "leisure and entertainment". The study finds significant differences in the average degree of membership and influencing factors among different patterns. Within the 6th Ring Road of Beijing, the non-commuting travel rhythm patterns exhibit a high degree of mixing, with significant differences in the travel rhythm period, functional features, and spatial distribution across different patterns. Moreover, these travel rhythms exhibit significant spatial dependence and are strongly correlated with the urban functional structures of commerce, employment, and residential areas. This study conducts an in-depth exploration of Beijing residents' non-commuting travel rhythm patterns from a spatiotemporal perspective, advancing urban research towards a more dynamic, refined, and human-centered direction. The research results will help to further improve the scientific understanding of the relationship between population travel rhythms and urban functional structures, thereby providing essential decision support for urban planning and construction.

Commuting is a significant representation of the geographical characteristics of residents' spatiotemporal behavior, and analyzing excess commuting is key to assessing urban commuting efficiency and jobs-housing relations. Over the past 40 years, China has undergone rapid urbanization, where urban development often alters jobs-housing relations, leading to prolonged commuting times that impact residents' well-being. To further explore the relationship between commuting time and commuting satisfaction, this paper introduces reference point theory and constructs an analytical framework for excess commuting perception based on three dimensions: "time-space-society-individual expectations". Utilizing 2013 survey data from Beijing, this study integrates excess commuting perception into the analysis of commuting time and satisfaction, and examines their interrelationships. The research focuses on family and individual constraints, and analyzes spatiotemporal differentiation characteristics of excess commuting perception through empirical research based on gender, age, and household monthly income. The findings are as follows: First, There is a difference between the individual excess commuting perception and the overall excess commuting perception, highlighting spatial heterogeneity in excess commuting perception across different dimensions. Second, changes in commuting satisfaction depend on changes in excess commuting perception. Residents assess their commuting time satisfaction based on the reference point, meaning that the level of commuting satisfaction is determined by the relative difference between their own commuting time and the reference point. Third, excess commuting perception significantly negatively impacts commuting satisfaction. Residents mainly use theoretical standard time, similar group commuting time, and tolerable time as reference points. The effect of "45 minutes" and "tolerable time" on commuting satisfaction is more pronounced than that of the "space-society" dimension. Fourth, the influence of excess commuting perception differs among various groups. The combination of family, gender, and income constraints amplifies excess commuting perception and decreases commuting satisfaction. For example, married women perceive greater excess commuting compared to single women. These insights contribute to a deeper understanding of how subjective commuting experiences vary and how they affect overall commuting satisfaction. This study provides a theoretical framework for understanding the complexities of commuting behavior and its implications on urban planning and policy-making. It highlights the importance of considering both individual expectations and broader social and spatial factors in addressing urban commuting challenges.

The concept of "people-oriented" planning emphasizes the need to understand the interaction between behavior and space and accurately portray urban spatial and structural characteristics from the perspective of micro-residents' behavior, and the commuting-based life circle is one of the most important objects to identify and analyze. Previous studies have identified and portrayed the circles from two approaches: place-based and flow-based. The morphological perspective makes it more difficult to consider the mobility brought by commuting behaviors, while the functional perspective makes it difficult to portray the internal structure of the life circles. Therefore, this paper proposes an artificial intelligence method that integrates the place-based and flow-based methods, which takes into account the characteristics of the built environment on the supply side and the commuting behaviors on the demand side.The method constructs an unsupervised model of "encoder-decoder" (GCN-FCM: Graph Convolution Network-Fuzzy Cluster Model) to delineate the scope and analyze the internal structure of the commuting-based life circles of Shenzhen, and the study finds that: (1) The model divides Shenzhen into 10 major commuting-based life circles, which on the whole shows the structural characteristics of "large scale in the central and western life circles and small scale in the eastern life circles, and dense spatial connection in the western life circles and relatively weak in the eastern life circles"; (2) The commuting-based life circles can be classified into two categories according to the differences in their internal structure. One is the southern and central life circles with a "significant and concentrated core and the emergence of the peripheral sub-centers", and the other is the northern and eastern suburban life circles with a "weak and dispersed core and a relatively fragmented overall situation"; (3) The results can well respond to the ideal model of life circles as well as corroborate the development goal of urban spatial structure in real planning, and deepen the knowledge of life circles for megacities; (4) Compared with the place-based approach, the new model can more accurately and rationally classify the commuting-based life circles; and compared with the flow-based approach, the new model can portray the internal structural differences of different life circles. Overall, the GCN-FCM model embodies the integration of spatial and behavioral interactions by the space-time behavioral methodology under the support of artificial intelligence methods, and shows a better application prospect in commuting-based life circles and other spatio-temporal planning.

Time use is a crucial dimension for studying residents' lifestyles, daily activity patterns, and travel behavior. In China, time use surveys and research are still in their early stages of development, with limited systematic studies on the time use behavior of the employed population. This study utilizes data from the 2018 Shanghai Time Use Survey to examine the characteristics and influencing factors of time use behavior among the employed population. The results show that: (1) Employed residents in Shanghai currently spend more time on maintenance and survival activities but less time on leisure activities. Their daily activity patterns demonstrate strong regularity, with work activities generally following an 8 am to 6 pm schedule. (2) The relationship between socioeconomic attributes and time allocation for work, household care, and leisure activities among Shanghai's employed residents is consistent with previous findings. Women, individuals raising children, and those in certain manual occupations have less leisure time due to work or household care pressures, and their rest and work schedules are earlier or later than the regular schedule. However, gender and child-rearing do not significantly affect commuting time, challenging the household responsibility hypothesis that women have shorter commuting times than men. (3) There are significant differences in the time use behavior of employed residents in suburban and central city areas, due to both demographic differences and the residential spatial environment. Employed residents in the outskirts of the central city experience longer commuting times due to job-housing imbalance. Suburban workers have a higher proportion of manual occupations and longer working hours. Employed residents in Chongming exhibit characteristics of an aging population engaged in agricultural production, with the shortest work and commuting times, and their rest and work schedules are significantly earlier than those in the central city. By comprehensively analyzing the time use behavior of employed residents with different demographic attributes and geographic locations, this study sheds light on the influence of micro-level socioeconomic and geographical factors on time use patterns. It deepens the understanding of time use patterns among the employed population in Chinese metropolises and provides a foundation and empirical evidence for further time use research in China.

Against the policy backdrop of the Guangdong-Hong Kong-Macao Greater Bay Area, the social integration of Hong Kong and Macao migrants in cities of Chinese mainland has been placed at the policy forefront. As an important aspect of social integration, the urban experience of Hong Kong and Macao migrants, particularly in terms of daily activity patterns in space and time, has received insufficient scholarly attention so far. Also, the exiting studies usually relied on sampled survey data collected from typical neighborhoods that were not representative of the whole migrant population. Addressing this gap, the present study sheds light to the spatial and temporal differentiation of daily activities of Hong Kong and Macao migrants through the perspective of space-time behavior, based on an empirical study of Guangzhou. Cellphone data are utilized to quantify the spatial and temporal patterns of daily activities of Hong Kong and Macao migrants in Guangzhou, as well as the latter's co-presence with the local residents. The study also zooms into several selected neighborhoods to investigate the daily activity patterns in a more detailed manner. The empirical study finds that the Hong Kong and Macao migrants are concentrated in the central-city areas as well as in several suburban neighborhoods. Not surprisingly, while eminent residential segregation is observed, the workplace segregation is found much lower than the former, which is consistent with most previous findings regarding activity-space segregation. The analyses on the selected neighborhoods further highlight the peculiarity of daily activity patterns of Hong Kong and Macao migrants, in the way that those migrants tend to have short travelling distances. It is also noteworthy that these selected neighborhoods are associated with different daily activity patterns, suggesting the diversity and heterogeneity of Hong Kong and Macao migrants as a social group in Guangzhou. Overall, the empirical findings are conducive to understanding the opportunities and constraints for social integration of Hong Kong and Macao migrants into the mainland cities. Furthermore, through this empirical case, the study validates the effectiveness of big data in deciphering the daily life patterns of special groups in contemporary large cities. Last but not the least, the study provides policy implications for planning and development of the Greater Bay Area as well as for promoting socioeconomic integration of Hong Kong and Macao migrants into the Chinese mainland.

Under the background of social transition and mobility society, how individuals interact with their neighborhood environment is constantly reconstructed. This makes it more complicated to form an emotional attachment to a community. The shared activity space at the neighborhood level refers to the spatial connection formed by neighbors through the use of the neighborhood space and its surrounding environment to carry out daily activities. It represents the intersection of different residents' activity spaces at a micro-scale. The shared activity space has complex extensity, intensity, and structural characteristics. However, the impact of these complex characteristics on residents' neighborhood attachment belonging remains understudied. This study utilizes data obtained from the Shanghai residents' activity and travel survey and employs ordered logit models to investigate the influence of neighborhood environment and shared activity space on residents' sense of attachment to their neighborhood. Shared activity space is measured based on the extensity and intensity of the public contact potential index, as well as the cross-group public contact potential index. The extensity index quantifies weak spatial relationships, while the intensity index measures strong spatial relationships. Additionally, the intergroup index portrays the social composition characteristics in daily interactions. The study findings indicate that the extensiveness of public contact potential index and cross-income group public contact potential index have a negative impact on neighborhood attachment, while cross-hukou public contact potential index exhibited a positive effect. Moreover, a higher proportion of migrant residents within a neighborhood contributes to stronger neighborhood attachment, suggesting that diversity in the demographic composition positively influences emotional ties to the neighborhood. Additionally, subjective evaluations of the neighborhood environment are linked to enhanced neighborhood attachment. Residents of commercial housing are more likely to have high neighborhood attachment compared to other types of neighborhoods. Furthermore, local residents, middle-income residents, married residents, and homeowners demonstrate higher likelihoods of developing strong emotional attachments to their neighborhoods. Individuals whose daily activities are distanced from the neighborhood may struggle to form a robust emotional bond with their neighborhoods. This study proposes to construct a mechanism to promote social integration in the neighborhood in the context of mobility through shared activity space. This enriches the theory of social integration and provides a reference for building an inclusive city and promoting quality development.

As China has been deeply involved in the process of globalization, the social practices of foreign residents in Chinese cities are becoming a significant force in shaping urban social spaces. Their settlement intentions and immigration tendencies in China have drawn considerable attention from domestic scholars. Guangzhou, as an emerging center for diverse transnational migration, has consistently been an important destination for foreign migrants coming to China. Based on a 2019 survey of foreign residents in Guangzhou, this paper analyzes their settlement intentions from different dimensions. Using the WLSMV estimation method, it constructs a structural equation model to analyze the impact of socio-economic environment, resource accumulation in China, consumption service preferences, and social interaction willingness on the long-term settlement intention and immigration tendencies of foreign residents, from both personal intrinsic factors and external environmental factors. The results indicate that: (1) Foreign residents generally show a low tendency to immigrate to China, but a high proportion is willing to stay in a long-term, with differences among groups: younger or less-educated foreign residents show relatively low long-term settlement intentions, while older or highly-educated foreign residents exhibit stronger settlement intentions. Factors such as kinship, stable employment, and existing residency conditions enhance their long-term settlement intentions in China. (2) Regarding personal intrinsic factors, resources in the destination area are crucial for the survival of international migrants. The capital accumulation of foreign residents in China directly influences their settlement intentions, while consumption preferences do not show a significant impact. (3) In terms of external environmental factors, objective differences in the socio-economic environment affect migration choices, and further influence integration strategies and settlement intentions. Subjective social interaction willingness does not directly lead to social capital accumulation, thereby not directly affecting settlement intentions and decisions. This study reveals the settlement intentions and internal differences among foreign residents in Guangzhou, explores the influencing factors of their settlement intentions, and provides valuable insights for the social governance of foreign residents. Overall, this study constitutes a new attempt to examine the settlement intentions of foreign migrants in urban China, a topic that has been missing from the literature while being placed at the policy forefront with increasing importance.

In the context of increasing geographical mobility, there has been a significant shift in the perspectives and measurement methods employed in urban sociospatial segregation research. Additionally, the imperatives of contemporary social development, which emphasize promoting social equity and enhancing people's well-being, have put forward novel practical requirements for the research of urban sociospatial segregation, as well as its underlying influencing mechanism and social effects. This study adopted an approach integrating quantitative analysis based on CiteSpace and qualitative analysis, to provide a comprehensive review of the evolutionary trends and thematic shifts in urban sociospatial segregation research since 2000. Over the years, the research of urban sociospatial segregation has consistently embraced the perspective of space-time behaviors. The focus of research has broadened from the sole dimension of residential space to multidimensional analysis of space-time behaviors gradually. And it has shifted from a static examination of spatial features to a dynamic exploration of space-time characteristics. In terms of its measurement indices, the advent of multi-source data, such as space-time behavioral big data, has facilitated the diversification of indices and methods continuously. There is a growing trend to shift the focus from space-based to people-based measurements, which is evident in recent research endeavors. Furthermore, the scope and depth of the research content has expanded significantly. It has moved beyond the study of measurements and feature description, to exploring the intricate mechanism which shapes sociospatial segregation and probing into its multifaceted social effects. Starting from the dimensions of space, time, and activity, certain studies reveal the influencing mechanism of urban sociospatial segregation. And several studies explore its extensive social effects in combination with themes such as resources accessibility, environmental health, crime, social integration, and subjective well-being. However, it is worth acknowledging that, there remains considerable room for further refinement and improvement. Current studies necessitate a heightened emphasis on the perspective of space-time integration, as it is helpful to address the complexities of sociospatial segregation. Future research ought to delve deeper into the influencing mechanism and social effects grounded in the consideration of space-time behaviors. Moreover, it is imperative to foster interdisciplinary dialogue and integration across various disciplines and paradigms.

Human activity classification is a fundamental aspect of spatiotemporal behavior research. Traditionally, human activities are usually classified based on their constraint characteristics. However, the rapid evolution of society and technologies, such as information and communication technologies (ICTs), has introduced new complexities that challenge the adequacy of these classic classification methods.To address these limitations, the time-geographic concept of project offers a promising alternative. A project, in this context, is defined as a series of space/time-uses designated to achieve a specific goal. This concept allows for a more nuanced classification of activities based on the internal linkages between activities constructed by individual or organizational intentions. By framing activities within the context of projects, researchers can better understand the interconnectedness and goals-oriented nature of human behavior. Despite the potential of the project concept, existing research that integrates projects into activity classification still faces several challenges. These include the ambiguity of criteria used to define projects, a lack of consideration for the evolving ICTs, and a narrow focus on empirical studies mainly from Western developed countries. These limitations hinder the development of a more comprehensive and globally relevant framework for classifying human activities from the perspective of project. This study aims to advance the theory and methodology of human activity classification by introducing the concept of a "project-activity classification system" (PACS). The PACS incorporates five hierarchical levels: "demand-project-activity-behavior-episode," which not only clarifies the role of projects within the urban activity system but also links the entire process from the initial demand for an activity to its eventual outcome. In addition, it goes beyond merely simplifying activity categories; it also preserves the semantic richness and contextual depth of detailed activities. The paper furtherly presents an exploratory construction of the PACS based on 2021 Beijing residents' daily activity survey data. The PACS preliminarily constructed in this paper based on first-hand survey, on the one hand, reflects the influence of the recent development of information and communications technologies on daily activities, on the other hand, demonstrates the types of urban activities with Chinese characteristics and shows possibilities for innovation in theory, methodology and empirical application of human activity classification.

The integration of subjective and objective perspectives is not only a hallmark of behavioral geography but also a challenging frontier that needs breakthroughs. This paper aims to provide an overview of the development and potential of mixed methods in behavioral geography research, particularly in terms of integrating subjective and objective elements. Mixed methods research has gained prominence in social science studies, offering a holistic approach that combines the strengths of both qualitative and quantitative methods. This paper briefly introduces the background and design typologies of mixed-methods research designs. Further, it summarizes current explorations in behavioral geography using mixed methods and their contributions to integrated research, encompassing the collection of subjective elements, the interpretation of behavioral decisions, and the understanding of subjective experiences as three primary themes. After addressing the challenges in existing research on the integration of subjective and objective factors, this paper proposes a path for applying mixed research methods in behavior geography studies, more specifically: (1) by using mixed-method research designs, such as the consistent designs, studies may enhance the depiction of dynamic, contextually detailed processes of subjective and objective factors' integration; (2) by using mixed-method research designs, such as the explanatory sequential designs, studies may identify diverse emerging new subjective and objective elements in complex contexts; and (3) by using mixed-method research designs, such as the explanatory sequential designs, studies can advance the construction and validation of theories in behavioral geography through widely applicable designs that emphasize consistency, interpretability, and exploratory analysis. While it is important to select research methods based on the research questions and the researcher's mastery of quantitative or qualitative methods, mixed methods have significant potential for the innovative integration of subjective and objective elements in behavioral geography. By incorporating mixed methods, researchers can contribute to theoretical innovation, methodological integration, and practical exploration within the discipline. Overall, mixed methods offer a valuable opportunity for researchers in behavioral geography to address the complexity of individuals' behavior in geographical contexts. As the field continues to evolve, the integration of mixed methods in behavioral geography research will play an increasingly important role in advancing the discipline and addressing key research questions.

The relationship between material space and human activities, shaped by their interactions, is a focus of attention in both human geography and urban planning. Research on spatiotemporal behaviors, grounded in the concept of space-time-human coupling, serves as a crucial foundation for revealing and explaining this intricate relationship. This paper systematically reviews the research progress from urban spatial structure to urban spatiotemporal structure, and ultimately to urban spatiotemporal behavior landscapes. It emphasizes the necessity of understanding cities through the lens of space-time-human coupling, advocating for the development of a theoretical and applied research framework for urban spatiotemporal behavior landscapes. Furthermore, the paper delves into the connotation, measurement, mechanisms, and effects of spatiotemporal behavior landscapes. Building on these insights, it also anticipates future research and significant application potentials. These include: firstly, further refine the theory of urban spatiotemporal behavior landscapes and, based on this foundation, develop related classical theories in human geography theoretically; secondly, deepen the methodologies for the collection, integration, and simulation of multi-source spatiotemporal data in the context of time-space-human coupling; thirdly, explore more potential applications, such as urban spatiotemporal behavior landscape planning aimed at creating livable cities, individual spatiotemporal behavior planning focused on promoting healthy lifestyles, and urban spatiotemporal collaborative governance geared towards fostering smart societies. This holistic approach underscores the importance of integrating spatial, temporal, and human factors in urban studies to address contemporary urban challenges effectively.

The rise of a mobile society and the pursuit of high-quality development have created new demands for innovative theories in Chinese geography. In order to effectively address the societal progress towards Chinese-style modernization, Chinese geography needs to depict and explain the micro-level processes and behavioral mechanisms present in both urban and rural Chinese societies. It is important to establish a research paradigm with Chinese characteristics in behavioral geography in order to provide a scientific foundation for understanding the implications of China's societal transition. This paper argues for a behavioral revolution in Chinese geography and its theoretical framework. It discusses the contributions of the behavioral revolution to the needs of China's social development and the theoretical foundations of the discipline's development. The behavioral revolution aims to create a framework for understanding human behavior within the context of time and space. It introduces a new research paradigm that emphasizes the interaction and integration of space-time behaviors. The behavioral revolution also explores the mechanistic interpretation of behavioral processes at both individual and interactive levels and introduces new technologies and methods for a hybrid measurement and analysis approach.Ultimately, its goal is to create a decision support system that considers dynamic human-land interaction. During the 15th Five-Year Plan period (2026-2030), addressing the need for high-quality development, the behavioral revolution in geography can play a crucial role in practice. It can offer theoretical foundations for addressing various urban challenges through innovative approaches to individual space-time behavior studies. It can support decision-making for urban mobility governance by establishing a space-time behavioral paradigm. Furthermore, it can enhance the theoretical understanding of behavioral processes to provide improved solutions for urban public safety and emergency management. The behavioral revolution in geography also holds significant theoretical importance for the construction of the geography discipline. It can address the frontiers of social sciences by delving into the study of individual behavior and contribute to the advancement of geography spatial research by enhancing the analysis of space-time interactions and processes. It can broaden the new direction of geography spatio-temporal dynamics coupling by refining the theoretical study of space-time integration. By introducing innovative methods of space-time behavior, it aims to enhance geography's microscopic mechanistic explanations and support the innovation of geography application practice.

The "international wetland city" certification proposed by the Ramsar convention is a new measure to promote wetland conservation and restoration. Taking the international wetland city of Changde as an example, based on the 15-meter spatial resolution wetland classification data from 2000 to 2022, we monitored the dynamic changes of wetland protection and restoration in Changde city year by year, quantitatively analyzed the importance and contribution rate of wetland protection and restoration driving factors, and finally explored the spatial distribution pattern of dominant driving factors. The results show that: (1) During 2000-2022, the wetland protection and restoration in Changde city achieved significant results, increasing from 1298.53 km² to 1399.61 km². The establishment of wetland reserves has a positive impact on wetland protection and restoration. (2) The main types of wetland changes are wetland stability (61.86%), followed by wetland restoration (22.10%) and wetland loss (16.04%). (3) Attribution analysis reveals that wetland restoration is mainly attributed to returning farmland to wetlands, and wetland damage is mainly caused by climate drought; mud flats, grass flats, reed wetlands, ponds, and rivers are mainly affected by arable land; lakes are mainly affected by construction land; and reservoirs and canals/canals are mainly affected by rainfall. (4) In the attribution partition, agricultural activities contribute to 68.76% of wetland changes, while urbanization and climate change contribute to 22.03% and 9.21%, respectively.

Behavioral geography is a discipline that explores the interaction between human behavior and geographic space. In the context of digital transformation, it faces a series of new opportunities and challenges in theory and methods, resulting in many new phenomena, problems, technologies, methods, and application scenarios. On the basis of sorting out the international cutting-edge dynamics of behavioral geography and the cutting-edge progress of Chinese behavioral geography research, this article focuses on cutting-edge directions such as big data behavioral research paradigms, AI innovative virtual and real behavioral systems, planning activity systems and local order nesting, special behaviors of the elderly population, behavioral and emotional geography, and proposes new development directions and key scientific issues of Chinese behavioral geography, such as paradigm shift, digital shift, humanistic shift, and emotional shift. Chinese behavioral geography needs to actively promote the innovative development of theory and methods, continuously improve the Chinese behavioral geography school, and strengthen the teaching practice and application innovation of behavioral geography.