Green finance is also called environmental finance or sustainability finance. As an important kind of financial development, green finance focuses on the win-win situation between the environment and economic growth by supporting the environmental protection industry. On the other hand, the green low-carbon transformation development can form diversified green capital needs, which will induce financial institutions to adjust products and services structure, innovate green finance service models and application scenarios with ecological concepts, and this will promote the development of green finance. Therefore, the concept and practice of green financial development and green low-carbon transformation are highly consistent, and there is an inherent logic of coordination and mutual promotion. However, there is limited literature on the coupling and coordination relationship between green financial development and green low-carbon transformation, and the research on influencing factors needs more in-depth discussions. To reveal the status of coupling and coordination between green financial development and green low-carbon transformation, this study used the entropy method to measure the level of green financial development and green low-carbon transformation, and introduced the coupling and coordination degree model, geodetector, and ArcGIS technology to explore the spatial and temporal variation characteristics and influencing factors of coupling and coordination between green financial development and green low-carbon transformation based on the data of Hunan Province from 2013 to 2021. The results show that the coupling and coordination degree between green financial development and green low-carbon transformation in Hunan Province was on the rise year by year, and continued to improve over time. The status was transiting to a coordinated stage step by step. The coupling and coordination degree in various regions showed a relatively consistent trend with the entire province. The coupling and coordination degree exhibited spatial agglomeration characteristics and presented a green development pattern radiating from Changsha City to the surrounding areas. The spatial differentiation of the coupling and coordination degree was obvious, greater in the eastern region than the western region, and in the northern region than the southern region. However, the growth speed in the western and southern regions was higher than that in the eastern and northern regions. The geodetector test results show that the coupling and coordination degree was influenced by factors of economic development, financial development scale, green R&D investment, digital infrastructure, and regional openness. Among them, the explanatory power of green R&D investment and financial development scale was greater than other factors, and both of them were the driving factors for the coupling and coordination between green financial development and green low-carbon transformation. The research may enable governments to clearly understand the integrated pattern of green financial development and green low-carbon transformation, so as to provide a decision-making reference for the integrated development of green financial development and green low-carbon transformation, and a reliable theoretical basis for cultivating new quality productivity according to local conditions to promote high-quality development.

Digital empowerment for the deep integration of rural culture and tourism is an important initiative for the upgrading of rural industries and the comprehensive revitalization of the rural areas in the context of the digital economy. Taking Wusi Village in Zhejiang Province as an example, this study applied the actor network theory to explore the process and mechanism of the deep integration of rural culture and tourism based on digital empowerment. The results show that: 1) The deep integration of rural culture and tourism based on digital empowerment in Wusi Village is a dynamic process in which multiple subjects participate and play with each other in three stages: initial exploration, rapid development, and deep integration. In the process of the deep integration of rural culture and tourism based on digital empowerment in Wusi Village, the village committee continues to play a key role, the role of market players such as cultural and tourism enterprise is gradually increasing, and the degree of association of rural residents with the network of actors is gradually deepening. 2) The deep integration of rural culture and tourism based on digital empowerment in Wusi Village is driven by a dynamic circular mechanism consisting of the rural core system and the peripheral system as the integration basis, digital technology and digital platform as the integration support, governmental, societal, and local forces formed by the interaction of multiple actors as the integration actor, and the deep integration of the rural cultural and tourism resources, products, industries, factors, markets, and values as the integration content. 3) The high-level cyclic development of the deep integration of rural culture and tourism based on digital empowerment is the result of the release of strong effects of both the mechanisms of action and reaction of the integration support and integration actor, and that of the integration actor and integration content. This study provides a theoretical basis and empirical experience for the high-quality development of rural digital cultural tourism, the upgrading of rural industries, and comprehensive rural revitalization.

With the in-depth development of a new round of scientific and technological revolution and industrial transformation, intelligent manufacturing equipment has become an important force to promote the high-quality development of industry, and the study of its production and supply relationship is of great significance to optimize the distribution of new quality productivity.Based on the data of core enterprises and suppliers in China's intelligent manufacturing equipment industry from 2010 to 2023, this study explored the spatial change characteristics of production-supply relationships of China's intelligent manufacturing equipment industry from three dimensions: production and supply linkage, production and supply network, and production and supply cluster by Pareto analysis and k-kernel analysis. The results are as follows: 1) The number and intensity of enterprise connections were increasing, and 700-1800 km was the general distance of production and supply connection of intelligent manufacturing equipment enterprises. The pattern of intercity production and supply links evolved from the shape of dual core radiation, triangle, to bow and arrow in China, and there were similarities and differences in the dominant flow of intercity production and supply links. The strong production and supply links between enterprises gradually shifted from intracity to intercity, and the number of export-oriented cities increased rapidly. 2) For more than a decade, the structure of the intercity production and supply network of China's intelligent manufacturing equipment industry has become increasingly compact and complex. After 2015, the city hierarchy of the intercity production and supply network has moved from a "pyramid" to a flat structure. 3) The number of production and supply clusters of China's intelligent manufacturing equipment industry has increased from 21 to 29. The production and supply cluster of the Yangtze River Delta has always maintained a leading position, the production and supply clusters of the Pearl River Delta, the Beijing-Tianjin-Hebei region, and Shandong Peninsula have developed steadily, and the status of the production and supply clusters in the middle reaches of the Yangtze River and the Chengdu-Chongqing region have significantly improved. The pattern of association of node cities within the clusters can be divided into five types: Single center, one core and multiple subordinates, two cores and multiple subordinates, multi-center, and low-level equilibrium, and the node association patterns within the clusters have showed spatiotemporal heterogeneity from 2010 to 2023.

Urban affordable housing communities are often located in suburbs, and these large communities have increasingly become focal points in urban social geography research due to the unique social, economic, and cultural attributes of their residents, the impact of affordable housing communities on residents' employment, lifestyle, and behavioral patterns, as well as the urban social-spatial issues such as residential spatial differentiation and resource distribution disparities induced by the construction of affordable housing. To address the deficiencies in relevant existing studies, including the lack of big data, comprehensive samples, and multi-dimensional, small-scale analyses, this study selected Daishan, the largest affordable housing area in Nanjing City, as the research object. Using 21 residential communities (groups) within the area as spatial units, and utilizing mobile user profiles and questionnaire survey data, combined with social, spatial, behavioral, and perceptual factors, this study investigated the social-spatial characteristics and issues of large affordable housing districts on urban outskirts. The findings reveal that the Daishan area exhibits characteristics such as aggregation of vulnerable groups, insufficient service facilities, heavy commuting burdens, and weak community belonging. While the social space across the area is relatively homogeneous, residents of communities with high concentration of public rental housing have the poorest economic conditions. Conversely, areas with better environmental and residential quality tend to house high-income young professionals. Future development in the area must pay attention to potential risks such as the perpetuation of poverty, community decline, and social discrimination. By integrating big data and conventional data sources to explore social spaces on a fine-grained spatial scale, this approach effectively compensates for the deficiencies of traditional data sources, such as socioeconomic statistics and sample questionnaire survey. This enables a nuanced exploration of urban social-spatial phenomena, providing detailed and authentic insights into the complexities and issues within social spaces.

Against the backdrop of globalization and informatization, digital transformation is not only crucial for cultural and tourism enterprises to enhance service quality and competitiveness but also an inevitable path to achieving high-quality development. Leveraging the theory of complex network evolutionary games, this study constructed a diffusion model for the digital transformation strategies of cultural and tourism enterprises. It delved into the impact of government subsidies on the digital transformation behavior of these enterprises across different regional economic development levels. The findings underscore the significant role of government subsidies in fostering digital transformation among cultural and tourism enterprises. These subsidies expedited decision-making processes and widened the economic disparity between transformed and non-transformed enterprises. Furthermore, the study revealed that the prosperity of the regional economy shaped the decision-making landscape for cultural and tourism enterprises, with those situated in economically developed regions exhibiting a greater propensity to embrace digital transformation. However, as the regional economy attains a certain threshold, the stimulatory effect of government subsidies may diminish, potentially slowing down the pace of digital transformation. This research offers insights for governments to formulate targeted subsidy policies, while also providing theoretical underpinnings and practical guidance for cultural and tourism enterprises to capitalize on the opportunities presented by digital transformation and attain high-quality development. By bridging the gap between policy formulation and corporate strategy, this study contributes to the advancement of the cultural and tourism industry in the digital age.

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.

The digital economy is an important driver of the development of the tourism industry. In order to analyze the multidimensional transmission mechanism and spatial spillover effect of the digital economy on the development of the tourism industry, this study used the panel data of 30 provinces (data of Xizang, Hong Kong, Macao and Taiwan are temporarily unavailable) in China's mainland from 2012 to 2019, and the panel benchmark regression model, the mediation effect model, and the spatial econometric model to conduct an empirical analysis. The results show that: 1) The digital economy played a significant role in promoting the development of the tourism industry. 2) Consumer demand, technological innovation, and institutional change were the important pathways of the digital economy affecting the development of the tourism industry. Among these three factors, consumer demand and technological innovation had a partial mediation effect, and institutional change had a masking effect. 3) Under the condition of a certain spatial weight, the digital economy had a spatial spillover effect on the development of the tourism industry, and the digital economy had a siphon effect on the development of the tourism industry in the adjacent areas of informatization, but had no obvious spatial spillover effect on the geographically adjacent areas. This paper can provide theoretical references and practical guidance for further deepening the integration of digital economy and tourism industry, and promoting high-quality development of the tourism industry.

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.

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.

The digital economy has become the first driving force for the innovation-driven development of the cultural and tourism industry. Based on data from 41 cities in the Yangtze River Delta from 2011 to 2021, this study found that the digital economy can promote high-quality synergistic development of the cultural and tourism industry, the conclusion that remains valid after robustness tests. The digital economy has been a more significant driving factor within Jiangsu and Zhejiang provinces, between large cities and between large and small and medium-sized cities, and between the core areas and between core and non-core areas. There is no significant correlation between the national smart tourism pilot cities and non-pilot cities in terms of high-quality synergistic development of the digital economy and the cultural and tourism industry. Mechanism tests showed that the digital economy can promote high-quality synergistic development of the cultural and tourism industry through channels such as promoting cultural and tourism product innovation and enhancing market potential. Further research found that the development of the digital economy in the Shanghai metropolitan area has narrowed the gap in the development of the cultural and tourism industry in various cities, while the existence of the "digital divide" in non-metropolitan areas has exacerbated the imbalance in the cultural and tourism industry. The conclusions have important implications for various types of subjects to cultivate the digital economy as a new force for the development of the cultural and tourism industry, and thus optimize the spatial pattern of high-quality synergistic development of the cultural and tourism industry enabled by the digital economy.

The digital economy is an important engine that can guide the rapid optimal allocation and regeneration of resources and achieve high-quality development of the tourism economy. Studying the impact of the digital economy on tourism innovation efficiency from the perspective of "local-neighboring area" spatial effect has important theoretical and practical significance for the high-quality development of the tourism industry. Taking the Yangtze River Delta as the research object, this study constructed a theoretical framework for the impact of the digital economy on tourism innovation efficiency. Based on the measurement of the development level of the digital economy and tourism innovation efficiency, this study explored the dynamic response relationships between the two and the spatial effects of the impact of the digital economy on tourism innovation efficiency. The findings are as follows: 1) Temporally, the mean value of tourism innovation efficiency in the Yangtze River Delta region showed a U-shaped pattern of first decreasing and then increasing. The overall level of efficiency was relatively low, and the region with high values kept growing over time. The tourism innovation efficiency of Shanghai and Zhejiang Province was higher than the average value of the Yangtze River Delta region. The gap between the tourism innovation efficiency of Jiangsu Province and the average value of the Yangtze River Delta region was narrowing, and it exceeded the average value of the Yangtze River Delta region in 2018, while the tourism innovation efficiency of Anhui Province had always been lower than the average values of the Yangtze River Delta region. 2) Spatially, tourism innovation efficiency generally presented a trend of high in the east and low in the west, and high in the south and low in the north. The high-value areas were mainly distributed in the economically developed areas or the areas with high abundance of tourism resources, which had apparent characteristics of economic and resource orientation. The spatial agglomeration characteristics of tourism innovation efficiency were apparent, and the "high-high" and "low-low" types dominated the agglomeration modes. 3) The digital economy was the Granger cause of tourism innovation efficiency, and the response of tourism innovation efficiency to the impact of the digital economy presented the characteristics of cyclical fluctuations and time lag. The digital economy had a significant positive direct effect on local tourism innovation efficiency, but the influence on tourism innovation of neighboring cities is stage-specific. Currently, the trickle-down effect of digital factor resources has a positive effect on the tourism innovation of neighboring cities.

Scene theory provides a new theoretical perspective for deepening research of cultural and tourism integration. This study used the scene theory as a theoretical analysis tool, summarizing the research value of cultural and tourism scenes, proposing the theoretical connotation and logic of cultural and tourism scenes, and identifying the research direction of cultural and tourism scenes. The research findings are as follows: 1) The research value of cultural and tourism scenes is reflected in placing the cultural and tourism industries in the same dynamic and complete system, and the differentiated scenes formed are conducive to implementing heterogeneous cultural and tourism integrative development strategies. 2) The theoretical connotation of cultural and tourism scenes includes four parts: First, concrete substance is an important foundation for the existence of cultural and tourism scenes. Second, the unique cultural value is contained in cultural and tourism scenes. Third, cultural values are the core components of cultural and tourism scenes. Last, the construction of cultural and tourism scenes becomes the driving force for culture and tourism integration. 3) The theoretical logic of cultural and tourism scenes is formed by the interaction of three dimensions: local originality, symbolic perception, and value expression. 4) Future research on cultural and tourism scenes should focus on the theoretical connotation and contemporary value of cultural and tourism scenes, the expression of cultural value in cultural and tourism scenes, the pattern recognition and operation mechanism of cultural and tourism scenes, and the application of digital technology in cultural and tourism scenes. The research can provide a theoretical basis and scenario application reference for promoting the development of culture and tourism integration.

Nearby urbanization is a new urbanization development path relative to remote urbanization, which refers to the process in which the rural population migrates to small and medium-sized cities and towns near their home areas for employment and residence rather than to distant places. Under the background of new-type urbanization, the regional difference of nearby urbanization constitutes a significant part of China's overall regional urbanization disparities, and it will profoundly affect China's urbanization process and the coordinated development of the economy and society. In this study, we used Theil index nested decomposition and the spatial Markov chain model to analyze the overall difference and decomposition of China's nearby urbanization development, and describe the regional convergence pattern of China's nearby urbanization development in detail, focusing on the impact of spatial effects on the nearby urbanization. The results show that: 1) From 2000 to 2020, the overall difference of nearby urbanization level in China showed a trend of continuous narrowing, consistent with the gradual narrowing of the development direction of the country's regional nearby urbanization gap. The overall difference of the urbanization rate within provinces was the largest, followed by the urbanization rate within counties, and the urbanization rate within towns was the smallest. 2) From the perspective of scale decomposition, local urbanization and its three subtypes (provincial urbanization, county urbanization, and town urbanization) showed the largest differences within provinces. By comparing the inter-provincial differences in the four regions, the western region had the largest inter-provincial differences, while the other regions showed relatively small differences. Comparing the intra-provincial differences of the four regions, the differences in the western and central provinces were large, while the differences in the eastern and northeastern provinces were small. 3) With regard to convergence patterns, there were spatial convergence clubs for nearby urbanization and its decompostions in China. The development of nearby urbanization in China showed obvious spatial linkage effect with the surrounding environment, and there was a certain spatial spillover effect. The results imply that the regional inequality of nearby urbanization in China follows the neoclassical convergence hypothesis and will narrow in the long term. Overall, the regional inequality of nearby urbanization in China from 2000 to 2020 stemmed mainly from inter-provincial inequality, especially in the central and western regions. With the improvement of the development level and radiation capacity of central cities in central and western China, we should strengthen support for the economic development of secondary regional node cities and improvement of public service facilities in small towns. This study provides a scientific support for comprehensively grasping the regional differences of urbanization in China and scientifically formulating the strategic measures of differentiated urbanization.

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.

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.

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.

Exploring the impact of urban morphology on the thermal environment is crucial for implementing sustainable urban planning and improving thermal conditions of cities. However, current research on the multiscale analysis of the heterogeneity in urban morphology's thermal environmental effects at the community scale is still insufficient, and the process of effectively integrating research findings into urban planning and management practices also faces numerous challenges. This study focused on the Nankai District, a typical high-density urban area in Tianjin Municipality, and used the building vector data and Landsat 8 remote sensing imagery to quantify urban morphology and land surface temperatures during the summer at the community scale. It integrated the multiscale geographically weighted regression and K-means clustering methods to investigate the spatial heterogeneity of urban morphology's impact on land surface temperatures and to perform cluster zoning. The results revealed that: 1) The summer land surface temperatures in Nankai District exhibited a high in the north and low in the south distribution with significant spatial autocorrelation, forming high-high and low-low aggregation patterns. 2) The multiscale geographically weighted regression model significantly outperformed ordinary least squares and geographically weighted regression models in fitting and explaining the relationship between urban morphology and land surface temperatures. 3) The impact of urban morphology factors on summer land surface temperatures showed multiscale spatial heterogeneity, with influences ranking from highest to lowest as follows: building density > normalized difference vegetation index > floor area ratio > building volume density, where building density and building volume density contributed to higher temperatures, whereas the normalized difference vegetation index and floor area ratio had a notable cooling effect. 4) Clustering based on the spatial heterogeneity of urban morphology indicators affecting summer land surface temperatures allowed the study area to be divided into three distinct regions, which enabled the formulation of differentiated planning strategies. The findings of this study provide a basis for optimizing community thermal environments. Moreover, effectively integrating multiscale geographically weighted regression and K-means clustering methods offers new perspectives and methodological frameworks for urban thermal environment research and related fields.

Since 2000, great changes have taken place in the spatial pattern of the development in western China, and the internal differentiation has become increasingly prominent. Optimizing the spatial pattern of development is an important way to solve the problem of unbalanced and inadequate development in the western region. This study used the trajectory of gravity center of development and Theil index to examine the change of the spatial pattern of development and regional inequality at different spatial scales in western China from 2000 to 2019. The results show that: 1) The change of the spatial pattern of development of the western region showed obvious stages. From 2000 to 2010, the population gravity center and economic gravity center moved northward, and the development in the northwest was better than that in the southwest generally. The overall regional development inequality in the western region had been widening. After 2010, the population and economic gravity centers began to move southward, and the development in the southwest was obviously better than that in the northwest. The overall gap in regional development was also narrowing. 2) There was a significant spatial heterogeneity and diversity in the changes of regional development inequality in the western region. Although the economic gap between the far west and the near west was small, it continued to widen since 2005. The per capita GDP gap between the southwest and the northwest and the income gap between urban and rural residents in the west show an inverted U-shaped trend. Although the income gap of rural residents in northwestern China and southwestern China had been narrowing, the gap was still significant. The income gap of rural residents between northwestern and southwestern areas had shown a widening trend, but the gap was not significant. 3) The development trend of the provinces showed a clear differentiation, forming four different types of development. Finally, the article put forward the strategy of optimizing the development pattern of the western region in the future.

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.