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.

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.

The world is undergoing unprecedented changes that have not been seen in a century, with an era of uncertainty and precarity beginning to emerge. Over the past 20 years, the concept of precarity has rapidly become a topic of great interest in Western human geography. This article first explained the basic connotations of precarity in terms of labor conditions, ontological experience, and class categories based on the classic literature of Western social science. It then reviewed the research trajectory of precarity in Western human geography and found that the geographical research on precarity exhibits a significant critical thinking approach. It focuses on the impact of structured environments of precarity on individuals and their responses within such environments, forming two main research threads: one is the study of precarity in labor conditions under specific historical circumstances, focusing on the structural mechanisms of precarious employment and the agency of the precariat; the other is the study of precarity as an ontological experience of human life, focusing on the impact of precarity caused by geopolitics and the politics of everyday urban life on residents and the political consequences that arise. Finally, the article suggests that research on precarity in the Chinese context can be carried out by integrating the economic situations of emerging economies, the new normal of the economy, flexible capital accumulation, and international politics. This article aimed to promote the field of human geography in China to extend into the realm of precarity, preparing for research in understanding social risks brought about by precarity and achieving long-term stable development of the social economic system.

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.

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.

The world is currently experiencing unprecedented changes, with frequent geopolitical conflicts, major public health incidents, extreme natural hazards and disasters, and other emergencies. The risks of the global grain supply chain are becoming increasingly prominent, and enhancing the resilience of the global grain supply chain has become a fundamental way to ensure the security and stability of the global grain supply chain. This study measured the resilience of international grain supply chains by identifying multidimensional supply chain network resilience measurement indicators based on the perspective of complex network. The characteristics of change of resilience and node anti-interference ability were analyzed. The results show that: 1) The global supply chains of rice and corn have a higher level of resilience, followed by the global supply chain of wheat, and the global supply chain of soybean has the lowest level of resilience. 2) The global supply chain networks of the four types of grain products are all resilient networks with fast recovery capacity and adaptability and their resilience levels have all improved. However, there are differences in their improvement levels, with soybeans, rice, wheat, and corn in descending order. 3) In the global supply chain network of the four types of grain products, China's anti-interference level is higher than the world average, but lower than the United States, and the anti-interference level of wheat and corn needs to be improved. The results of this study have important practical and theoretical significance for clarifying the resilience level and characteristics of change of the global grain supply chain, which may help enhance China's position and anti-interference ability in the global grain supply chain network.

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.

In the context of global warming, there is a higher probability of occurrence of the summertime compound hot extremes when daytime and nighttime heat sustains, which lead to the reduction of continuous precipitation and increase of precipitation with short duration and high intensity, resulting in changes of diurnal precipitation pattern at summertime in the Northern Hemisphere land area. Compared with the well-understood summer precipitation on the annual scale, current knowledge about combined daytime and nighttime precipitation remains too scarce for the Loess Plateau of China. Based on the daily precipitation and maximum temperature dataset from 1970 to 2020 released by the National Meteorological Information Center and using the empirical orthogonal function (EOF) and Mann-Kendall trend analysis method, we investigated the spatiotemporal variations of rainfall amount, days, and intensity for four types of diurnal precipitation process on the Loess Plateau in summertime (from June to August), including sunny days and rainy nighttime, hot daytime and rainy nighttime, rainfall days for diurnal composite precipitation, as well as rainy daytime and rainless nighttime. The results are as follows: 1) From 2000 to 2020, the Loess Plateau witnessed a significant increase of precipitation amount in summertime and nighttime, which had not changed the spatial pattern characterized by a decreasing gradient of precipitation from southeast to northwest. 2) Consistent with the fluctuating precipitation amount and decreased precipitation days, there was a significant increasing trend for the precipitation intensity in sunny days and rainy nighttime, rainfall days for diurnal composite precipitation, rainy daytime and rainless nighttime from 2000 to 2020, while for hot daytime and rainy nighttime the precipitation intensity maintained stable fluctuations after the 1990s. 3) Areas in the central arid zone of Ningxia, eastern part of the Hetao Plain, northern Shanxi Province, and from the Fen-Wei Plain to the Yiluo River Plain were sensitive to the variations of sunny days and rainy nighttime. However, the Earth-Rock Mountain and high-altitude regions of the southwestern Loess Plateau are sensitive to hot daytime and rainy nighttime changes. Meanwhile, we observed a high sensitivity for the variations of rainfall days for diurnal composite precipitation, as well as rainy daytime and rainless nighttime in the valley and plain areas of the southeastern part of the Loess Plateau. The findings highlight that the increased intensity of daytime precipitation and diurnal composite precipitation is changing the patterns of diurnal extreme precipitation on the Loess Plateau, inspiring to enhance the research regarding the variations and mechanism of diurnal extreme precipitation in summertime.

As China's economic and trade cooperation with Southeast Asia and other regions becomes increasingly close, accelerating the construction of the new western land-sea corridor and enhancing the quality and efficiency of logistics development is of great significance for promoting economic development and high-level opening-up in the inland areas of western China. This study focused on 30 urban units within the core coverage area of the new western land-sea corridor. Based on long-term statistical data, it employed the back propagation (BP) neural network model to predict the railway and highway freight volumes of each city after the completion of the main corridor. An improved gravity model was used to simulate the freight connections between cities under future corridor capacity conditions. Additionally, social network analysis was applied to compare the railway and highway logistics network structures before and after the completion of the corridor. The results indicate that: 1) The construction of the new western land-sea corridor helps reduce the railway and highway distances between cities in the core coverage area, increasing the total freight volume of each city. 2) Upon completion of the corridor, logistics connections between seaports and landports, such as Fangchenggang and Kunming facing Southeast Asia, and cities such as Chongqing and various provincial capitals, will be significantly strengthened. This will also promote the flow of goods to prefecture-level cities, leading to a hierarchical and integrated development pattern in the logistics network. 3) In terms of the distance reduction effect, changes in freight volume, and shifts in logistics network structure, the construction of the corridor has a stronger impact on the railway logistics network compared to the highway network. By comparing the changes in land logistics network patterns before and after the construction of the corridor, this study provides scientific insights for optimizing corridor layout, upgrading logistics networks, and promoting high-quality regional economic development.

Functional polycentricity is a reflection of the essential attributes of urban agglomerations, and an important way to build a new urbanization pattern of division of labor and cooperation with improved functions.Based on Tencent's population movement data from 19 urban agglomerations of China, this study analyzed the spatiotemporal change characteristics of population flow networks at the national and regional scales and functional polycentricity in urban agglomerations, and further explored the influencing factors of functional polycentricity. The results show that: 1) The regional functional polycentricity index of urban agglomerations of China as a whole is larger than the national functional polycentricity index and evolves toward stronger polycentricity, and there is a large gap between the national and regional functional polycentricity indices of the three types of urban agglomerations. 2) The regional functional polycentricity index of most urban agglomerations is larger than the national functional polycentricity index, which is in line with the general pattern that the larger the scale, the smaller the polycentricity index. The functional polycentricity type of each urban agglomeration is stable, but the direction of change differs. There is no obvious relationship between the functional polycentricity type of urban agglomerations and the type of urban agglomerations' development, and the type of urban agglomerations' functional polycentricity shows complexity. 3) The increase in GDP per capita reduces the national functional polycentricity index and shows a "U"-shaped correlation with the regional functional polycentricity index. The increase in the ratio of the total value of the secondary and tertiary industries promotes the increase of the national functional polycentricity index, and the increase in the size of the resident population and the decrease in the proportion of Internet users promotes the increase of the regional functional polycentricity index. The results of this study can provide relevant references for the development strategy of the spatial structure of urban agglomerations.

Rhythmmanalysis, as an important theory in geographic research, has received extensive attention in the international academic community, but has not yet been fully emphasized in the Chinese academic community. This article first defined the connotation of Henri Lefebvre's concept of rhythm, and explained the theoretical connotation and inner connection of polyrhytmia, arrhythmia, eurhythmia, dressage, and isorhythmia in the theory of rhythm analysis; second, it systematically reviewed the rhythm research of the international geography community in the dimensions of the subject, the place, and the mobility. The article further discussed the deep insight of rhythm analysis in understanding the interactions between human activities and geographical space. Third, the article explored two theoretical perspectives of rhythm analysis—a localized time and a temporalized place—and explained the differences and connections between them in terms of research focus. Ultimately, rhythmanalysis, as a humanistic research method, pays attention to the comprehensive development of individuals, offering new theoretical perspectives and research methodologies for issues such as life rhythm, cultural rhythm, and ecological rhythm within the context of contemporary China. The article posits that the localization and modernization of the theory of rhythm analysis will provide a scientific guidance for the theoretical innovation of human geography practice in China, and is of great significance for promoting the sustainable development of society and the comprehensive development of human beings.

The flow of cultural ecosystem services, as a bridge between the supply of ecological resources and the needs of human society, represents the nonmaterial benefits that people actually receive from ecosystems and is closely related to human well-being. National parks are spatial carriers to realize the value of natural resources and benefit the general public in typical ecosystems. They take ecological protection, scientific research and education, and recreational use as management objectives to satisfy people's needs for beautiful ecological environments, excellent ecological products, and high-quality ecological services. Taking the Liaohekou National Park as a case area, this study constructed a spatial multiscale integration framework for cultural ecosystem service flow based on the research paradigms for different spatial scales, used multiple source data such as remote sensing and social media data, and applied spatial analysis tools such as the MaxEnt model and ArcGIS platform to evaluate the spatial patterns of recreational, biodiversity, historical, scientific, and educational services provision and flow of the ecosystem and their influencing factors in the study area. The results show that: 1) In general, at the intraregional scale, the total supply of various cultural ecosystem services is greater than the intraregional service flows, and the four types of cultural ecosystem service flows are mainly concentrated in estuaries and eastern coastal areas; at the interregional scale, the distribution of various types of cultural ecosystem service flows is mainly related to the level of economic development, especially in coastal provinces and municipalities. 2) At different spatial scales, the factors that influence the spatial distribution of cultural ecosystem service flows have different strengths, among which the distance from national parks and economic factors show significant differences at different scales, with the former showing strong-weak-strong changes within the region, province, and the whole country, and the latter showing weak-strong-strong changes. The spatial multiscale integration framework of cultural ecosystem service flow constructed in this study is not only an exploratory study on the distribution pattern and mechanism of cultural ecosystem service flow, but also provides a reference for improving the management efficiency and ecological product supply capacity of national parks, and promotes the construction of national park protected area system.

Global warming has led to accelerated changes in the global hydrological cycle, resulting in an increasing number of extreme events and compound events in which multiple extreme events occur simultaneously or consecutively, and are more hazardous than a single extreme event. The Yangtze River Basin has always been one of the areas with the most frequent extreme weather and climate events and disasters in China and has also experienced more severe compound events in recent years due to global changes, which has seriously constrained ecological protection and high-quality development in the region. The Yangtze River Basin is one of the most populous and economically developed regions in China, and climate change and human activities have significantly affected the distribution of water and heat conditions in the region. Therefore, taking the Yangtze River Basin as an example and based on long-term historical observations and CMIP6 model prediction data, this study adopted the compound drought and heatwave magnitude index (CDHMI) to identify compound drought and heatwave events (CDHEs) in the Yangtze River Basin, used cumulative probability density curves to classify the intensity of CDHEs, and explored the spatial and temporal evolution patterns of the compound drought and heatwave events as well as the future trends. Meanwhile, to ensure the accuracy of the data, the applicability of the 23 CMIP6 models in the Yangtze River Basin was assessed using three evaluation metrics, which improved the credibility of future CDHEs predictions. Finally, the spatial changes of CDHEs in the Yangtze River Basin under different future scenarios were characterized based on a multi-model ensemble of 23 CMIP6 data. The results of the study show that: 1) During the historical period, the frequency and duration of CDHEs showed a non-significant increasing trend. The frequency and duration of CDHEs were the highest in July, at 0.511 times and 3.59 days, respectively. The frequency of mild CDHEs was the highest in the historical period, with an annual average frequency of 0.4 times, which mainly occurred in the middle and lower reaches of the Yangtze River Basin, the Hengduan Mountains, and the Yunnan-Guizhou Plateau. 2) Among the 23 CMIP6 models, INM-CM4-8, ACCESS-ESM1-5, NESM3, NorESM2-LM, and INM-CM5-0 are the five most suitable models for the Yangtze River Basin after bias correction. 3) In the future, the middle and lower reaches of the Yangtze River Basin will be the areas with high frequency and long duration of CDHEs, and the annual average frequency and duration of CDHEs by the NorESM2-LM model are the highest. The results of the five models and multi-modal ensemble also show small differences between scenarios in the short term and medium term and significant differences in the long term. In the long term of SSP5-8.5, the average annual frequency of CDHEs would increase by 2.3 times and 1.8 times, respectively, compared to the short term and medium term under the same scenario. The duration was 29.9 days and 21.3 days higher than that of SSP1-2.6 and SSP2-4.5 during the same period. The average annual frequency of mild CDHEs is the highest for all three scenarios, and all severity events should peak at SSP5-8.5. This findings can provide scientific and technical support to actively mitigate future climate change risks in the Yangtze River Basin.

Under the background of globalization, informatization, industrialization, and urbanization, the hierarchical structure of China's urban system and its flow networks are intertwined and interact with each other. Based on the improved gravitational field model and the spatial econometric model, this study analyzed the economic efficiency of the Wuhan metropolitan area under the interaction of urban hierarchy and population flow (hierarchy-flow). The study found that the economic performance of cities and towns in the Wuhan metropolitan area showed a significant center-periphery pattern, and the Wuhan-Ezhou-Huangshi-Huanggang axis of economic efficiency is initially formed. The total economic volume of cities and towns grew super-linearly with the increase of urban population scale, but the gap between them tended to narrow. Population flows across scales promoted the growth of urban economic efficiency, and there was heterogeneity in the effects of different dimensions of urban hierarchies on urban economic efficiency. The influence of scale hierarchy on urban economic efficiency was negative, while increased population flows to large cities reduced scale diseconomies. Functional hierarchies contributed to the economic efficiency of cities and towns, and they further promoted agglomeration economies through cross-scale population flow. The administrative hierarchy promoted efficient economic growth in cities and towns, and growth in the scale of urban mobility at high administrative tiers promoted hierarchical diffusion. The interaction of hierarchy-flow expands the research perspectives of urban economic growth, deepens the understanding of the mechanism of high-efficiency growth of cities with different hierarchies, and lays the foundation for the coordinated and high-efficiency development of urban economy in metropolitan areas.

Under the background of high-quality urban development in Chinese-style modernization, building open, diverse, and resilient livable community life circles has become an important aspect of the sustainable development of future cities and the improvement of residents' quality of life and sense of well-being. The spatial and temporal optimization of facilities in community life circles is an important direction for urban renewal and transformation. This study took the Dangdai-Yimei community life circle—an area located in the suburb of Beijing—as a case study area, and combined spatial syntactic modeling with spatiotemporal characteristics of residents' daily activities. By conducting a spatial environment evaluation at the scale of urban community life circle, we put forward recommendations for spatial optimization. The study found that space with high availability in spatial syntactic measurement results is usually rarely used in residents' daily life due to access control management, behavioral needs, work arrangements and other factors. The fact that residents indirectly use facilities in other communities reveals the need for sharing of space between communities. Within the community life circle, there are shortcomings such as inadequate facility allocation and insufficient public spaces. Shopping facilities are located far from residential areas, leading to fewer shopping activities within the community life circle. The lack of leisure spaces forces residents to use the major transportation hub as leisure spaces. Finally, the low activity of working professionals within the community life circle during weekday evenings reflects the inadequacy of spatial flexibility planning. We recommend that in the future, human behavioral needs should be integrated with the spatial structure characteristics of the built environment in communities. This includes advocating for increased openness and sharing between communities within community life circles, diversifying the functions of public spaces, and appropriately adding flexible activity spaces. These efforts aim to create more livable and harmonious living activity spaces.

Urban afforestation has been a significant artificial forestation approach in China. In theory, it serves as a crucial sink for urban carbon emissions, but it remains challenging to quantitatively assess the current status and potential of carbon sequestration of urban forest vegetation. This study, based on the biomass-age relationship in forest succession theory (FCS model), used 30-m high-resolution remote sensing imagery data and integrated IPCC climate scenario data to assess and predict the current status and potential of carbon sequestration in newly added forest vegetation in the Beijing-Tianjin-Hebei urban area from 1985 to 2020. The research findings indicate that the total carbon sequestration in newly added forest vegetation in the area from 1985 to 2020 is approximately 14.28 × 10⁴ t, with Beijing urban area having the highest carbon sequestration amount of about 10.34 × 10⁴ t, possibly due to the largest growth rate of urban forest area in Beijing. By 2060, the potential carbon sequestration of this newly added forest vegetation is expected to be close to 39.72 × 10⁴ t, with Beijing urban area still having the highest potential of around 25.93 × 10⁴ t. From the perspective of city or district-level administrative units, in the period from 1985 to 2020, the district with the highest carbon sequestration in newly added forest vegetation in Beijing urban area was Shijingshan District, while in Tianjin urban area it was Jizhou District, and in Hebei urban area it was Chengde City. However, carbon sequestration potential differs, with Shunyi District becoming the area with the highest potential in Beijing urban area, Jizhou District remaining the highest in Tianjin urban area, and Langfang City becoming the highest in Hebei urban area. It is evident that there are significant differences in historical carbon sequestration and future carbon sink potential among different urban areas, which also suggests that future management of urban forest carbon sinks needs to integrate the current status and potential of carbon sinks comprehensively. This study innovatively proposed an accurate assessment method for quantifying urban forest carbon sinks, and its research findings provide important references for the scientific management and optimization strategies of urban forest carbon sinks.

In the context of China's rapid urbanization, the migration of ethnic minority population is becoming increasingly more active, and has become an important component of China's migration groups, which has attracted widespread attention. This article reviewed the existing studies from the perspective of geography, which is conducive to enhancing interdisciplinary dialogue and expanding the research direction of ethnic minority population migration in China. Based on the reality of ethnic minority migration in China, this study incorporated the relevant migration theories on the basis of Chinese ethnicity theories, and established a macro-micro analytical framework. The study found that the migration of ethnic minority population has entered an active period, and the overall pattern of migration was from rural to urban areas, mainly within the provinces and across provinces from west to east; China's ethnic minority migration was also affected by factors that are common for the overall migration of the country, including ethnic minority languages, specific cultural practices, and co-ethnic network connections. Other factors related to ethnic culture also played an important role, but existing studies are weak in examining the mechanism of cultural factors; Ethnic minority migration in China not only promotes urbanization but also facilitates a wide range of interaction, communication, and integration among all ethnic groups, and its impact on urban-rural integration and the protection and revitalization of ethnic villages in ethnic minority areas requires the joint attention of different disciplines. Looking forward to future research, the study can be expanded in terms of the dispersal pattern and characteristics of change of ethnic minority migrants in urban scale hierarchies, the examination of the role of cultural factors in whether and how to migrate, and the effects of migration on the development of urban-rural transformation in ethnic minority areas and on ethnic minority individuals, respectively.

China's vast agro-pastoral ecotone, primarily located in ecologically fragile areas, comprises complex livelihood types and was concentrated areas of poverty in the past. By 2020, these areas had eradicated absolute poverty, marking a significant contribution to global poverty alleviation efforts. Focusing on Zhangbei County in the northern agro-pastoral ecotone, we explored the spatiotemporal patterns of farmers' income from 2016 to 2022, differences in income factors among three livelihood types, and their temporal changes using annual village-level field survey data, spatial autocorrelation, standard deviation ellipse, and geodetector analysis. The findings reveal that: 1) The average income of farmers in Zhangbei County increased from 7000 yuan in 2016 to 11000 yuan in 2022, and the income gap widened. High-income areas shifted from the center of Zhangbei County to the northern villages by 2020, while low-income areas dispersed from the northwestern concentrated area to larger areas of the county since 2019, with spatial variability in per capita income increasing. 2) The factors that influence farmers' per capita income exhibited significant temporal changes and differences across livelihood types. The role of grassroots-level government in driving income change for all three types of livelihoods has significantly strengthened. In farming-dominated areas, growth in farmers' income was more reliant on the provision and support of external market resources by local governments. In pastoral-dominated areas, it depended more on the guidance of experienced leaders in linking the labor force to the local market. In areas with mixed farming and pastoral activities, the influence of local governments is weaker compared to predominantly farming and pastoral areas, and farmers' income growth relied more on internal regional interactions. 3) Over time, the influencing factors have shifted from a sole focus on infrastructure and labor elements to a greater emphasis on the role of grassroots-level government, transportation accessibility, and market connectivity. 4) Future policies for increasing farmers' income should consider the differences in livelihood types more carefully, strengthen the capacity of grassroots-level governments, improve education levels, enhance transportation facilities, and promote the effective integration of resources. This study may provide a scientific reference for global poverty alleviation efforts and sustainable rural development in ecologically fragile areas.

Rural and urban spatial systems are a spatial support for implementing the rural revitalization strategy. Against the backdrop of increasingly prominent issues in individual village development, constructing a rural and urban spatial system identification path that serves rural cluster development is an effective way to achieve regional coordinated development. This study established a rural and urban spatial system identification path of "rural development poles-rural development clusters" and used multi-source data from 379 villages of 18 towns in Jinghai District, Tianjin Municipality, to analyze the spatial network characteristics of villages and towns. Based on the rural and urban spatial system identification path, rural development clusters were then delineated, and revitalization paths for different development clusters were proposed. The main conclusions are as follows: 1) The spatial network characteristics under the dimensions of economic development, resource endowment, and living environment vary, with notable local agglomeration characteristics of comprehensive development levels. The network density exhibits a distribution pattern that decreases from the northeast to the southwest. 2) Based on resource characteristics, villages were categorized into four types and eight variants: multi-resource dominant (P-C-A), dual-resource dominant (P-C, P-A, C-A), single-resource dominant (P, C, A), and non-resource dominant (p-c-a), with single-resource dominant and non-resource dominant villages being the majority in Jinghai District. 3) According to the rural and urban spatial system identification path, central villages, characteristic villages, and rural development clusters were sequentially identified based on the spatial network. Furthermore, sub-clusters of rural development were identified based on the dominant resource evaluation results. A rural and urban system in the study area was ultimately mapped, comprising 24 central villages, 13 characteristic villages, 9 rural development groups, and their 30 subordinate rural development sub-groups. 4) Based on the optimization pattern of the rural and urban spatial system, the characteristics of rural development clusters were further analyzed, and a clustered development path for promoting rural revitalization by zoning and classification was proposed.

Population is the dominant factor of regional development. In the context of coordinated population and regional development, this study took the Hu Huanyong line as reference to define the westward migrants, whose outflow place is in the southeastern side of Hu Huanyong line, while inflow place is in the northwestern side of Hu Huanyong line. Based on this definition, this study analyzed the settlement intention of China's westward migrants and its influencing factors. The analysis used the data of the China Migrants Dynamic Survey in 2017 and the corresponding regional data, and the non-parametric test and multilevel mixed-effects logistic regression methods. The results are as follows: 1) About 30% of the westward migrants chose stable residence, and the settlement intention is at a relatively low level while the vast majority of migrants chose temporary residence. With regard to destination cities, with the increase of urban scale, the settlement intention of migrants became higher. 2) The westward migrants from central China to the northwestern provincial capital cities or regional central cities were more likely to choose stable residence. 3) Settlement intention was influenced by both economic and non-economic factors. At the individual level, residence time, family size, family income, employer status, ownership of housing, active social interaction and psychological integration, and participation in social health insurance had positive effects on settlement intention. The migrants from the northern cities to the southeast of the Hu Huanyong line had a higher settlement intention. At the regional level, altitude had an inhibitory effect on settlement intention, while local development vitality and city size played a positive role. However, GDP per capita and medical and health conditions played no significant role. Based on the above research findings, this study recommend to promote the settlement intention of the westward migrants by steadily increasing income, constructing family-friendly policy system, creating inclusive social and cultural environment, and let urban agglomerations play a leading role.

With the increased rate of urbanization, health problems resulting from the distant separation of jobs and housing as well as increased reliance on motorized travel have become increasingly prominent. As a healthy and sustainable mode of transportation, active travel holds significant positive potential for achieving the peak emission and carbon neutrality goals and realizing the Healthy China strategy. The impact of active travel on residents' physical health has garnered significant interest among scholars in geography, transportation, and urban planning. However, research on its impact on psychological health and well-being is still in an early stage. This study aimed to contribute to this area by providing a systematic summary of the empirical effects surrounding the relationship between urban active travel and psychological health and well-being, drawing on relevant journal publications in China and internationally. The results of our review show that the majority of the studies have confirmed the positive impacts of active travel on psychological health and well-being. However, these impacts were also moderated by personal and spatial factors, resulting in heterogeneity. Furthermore, this study found that the impact path of active travel on psychological health and well-being is complex, involving the joint action of multiple direct and indirect factors. The main action paths include: the direct effect of intrinsic characteristics, the mediation effect of individual physiological functions, the moderating effect of the physical environment, and the mediation effect of the social environment. In addition, psychological health and well-being can also have a feedback effect on active travel behaviors by influencing travel willingness. Finally, based on the current status of the research conducted, this article also put forward relevant recommendations for improvement, especially to provide new ideas for conducting similar research in China. These findings offer insights for promoting active travel through policy measures and urban planning strategies, and facilitating the research and development of healthy cities in China.

From the perspective of urban science, this study assumed that the development of built-up areas follows certain natural law. Using the conventional and reconstructed scaling expression of rank-size distribution models, this study analyzed built-up area and population size distributions, and examined whether the size of built-up areas follow the Gibrat's law. The conventional expression of rank-size distribution is from empirical patterns while the reconstructed one is mathematically derived from a hierarchical fractal system. Thus, the reconstructing process itself is to connect the empirical phenomenon to the hidden order, which is consistent with the perspective of urban science. Specifically, to match the area and population datasets, this study first applied city cluster algorithm to delineate all built-up areas in China, using the global impervious area data. Then the boundaries of built-up areas were used to aggregate population size from the LandScan world population product. The study found that the area size of built-up areas follows the rank-size distribution under both models, while the population size follows that only under the reconstructed model. Moreover, the Gibrat's law is not suitable for explaining the rank-size patterns of the built-up area system. The research results reveal the structural differences in the dynamic mechanism of urban development and population mobility within built-up area systems in China. Urban development shows a tendency of centralized management, and area expansion is easier/quicker than population growth. The potential contribution of this research is two-fold: first, the reconstructed scaling model can filter data noises algorithmically and thus can be used as an optimization algorithm for large sample size sequence-scale analysis; second, the reconstructed scaling model has a macroscopic structure that provides an explanation for rank-size distribution, that is, the rank-scale schema is a macroscopic pattern and hidden order, which needs to be rediscovered through reconstructing the empirical data.

Vegetation phenology is a critical indicator reflecting the impact of climate change on ecosystems. Northeast China boasts rich vegetation types and has experienced stronger warming than the national average, thus research on its vegetation phenological responses to climate change is particularly significant for providing scientific underpinnings for ecosystem management under global change scenarios. This study used the MODIS Enhanced Vegetation Index (EVI) and Solar-Induced Chlorophyll Fluorescence (SIF) data from 2000 to 2020 to extract greenness and photosynthetic phenology in Northeast China. It analyzed the spatial-temporal variations of spring phenology in the region and combined meteorological data to diagnose the dominant factors that affect spring phenology across different vegetation types. The results revealed that: 1) From 2000 to 2020, the spring phenology of vegetation in Northeast China exhibited an advancing trend. Specifically, the start of growing season derived from the EVI data (SOS_EVI) advanced significantly at an average rate of 0.657 days per year (P < 0.05). Similarly, the start of growing season derived from the SIF data (SOS_SIF) showed a statistically significant advance at an average rate of 0.443 days per year. Spatially, 76.8% and 88.5% of the pixels displayed an advancing trend for SOS_EVI and SOS_SIF, respectively. 2) Among the environmental factors, spring temperature (temperature of air at 2 m above the surface) and soil moisture (volumetric soil water in the surface layer) content exerted a strong influence on the spring phenology in Northeast China. For SOS_EVI, approximately 44.5% of the pixels were primarily dominated by spring temperature, while about 24.5% were governed by soil moisture content. For SOS_SIF, spring temperature played a dominant role in around 61.5% of the pixels, and soil moisture content was the primary driver in about 20.0% pixels. Thus, rising spring temperatures and increased soil moisture levels were identified as the main factors driving the earlier onset of spring phenology. 3) The dominant factors influencing spring phenology varied among different vegetation types. The spring phenology of deciduous broadleaf forests was mainly affected by spring temperature, whereas the spring phenology of grassland was predominantly more sensitive to soil moisture conditions. This study disclosed the spatial-temporal patterns and dominant factors of spring phenological changes of various vegetation types in Northeast China, providing robust evidence for the understanding of climate change impacts on regional vegetation dynamics.

Households are a key carrier for urban spatial reconfiguration and socioeconomic transition, and also a crucial intermediate level between the individual, the community, and the city. Existing studies have recognized the importance of research on spatial-temporal behavior from the perspective of households, but they usually take the characteristics and division of responsibilities of households as background and explanatory factors. The interactions and connections between household members are rarely considered, and the complexity of intra-household behavioral interactions of various households and different types of behavior is not well understood. This research focused on household and intra-household behavioral interactions. First, it created a time-space-society framework to measure behavioral interactions in three dimensions, that is, temporal interaction, spatial interaction, and social relationship interactions, and refined the patterns of intra-household behavioral interactions. Second, it revealed the mechanisms of influence and effects of intra-household behavioral interactions, taking China's socioeconomic background into account. Finally, aiming to improve the quality of life of household members, it proposed an optimization scheme of living space with the household-friendly orientation. The research contributes to reintroducing the household level in urban research based on spatial-temporal behavior, and promoting behavioral geography research to emphasizing individuals' interactions. It also provides new ideas for examining social issues such as fertility, as well as child and elderly care, offering a scientific reference for the optimization of community life circle and urban space, and promote household-friendly urban planning and social governance.

Research on crime geography has traditionally focused on objective criminal activities and neglected subjective perceptions such as fear of crime, which is its major shortcoming. Using the deep learning algorithm of image regression, we analyzed the level of fear of crime under different streetscape environments on a large scale in the central urban area of Beijing. This approach compensates for the limitations of social surveys in terms of spatial coverage, spatial resolution, and reliability and validity of measures. Our indigenous deep learning models also make up for the lack of established models that rely on western city street view images and overseas labelers. Our study shows that, first, the spatial pattern of fear of crime has a circular, multi-cluster, and radial structure, and its level gradually increases from the city center to the suburbs. In contrast, the density/number of theft and violent crimes have the spatial distribution with the opposite trend. Second, according to the relationship between the spatial distribution of fear of crime and criminal activities in general, we find a low match between subjective and objective security in the city center, with the objective situation being more dangerous than the subjective perception; in the suburban areas, the degree of match between the two increases; to the outer suburbs, these two still have a low degree of match, but the objective situation is safer than the subjective perception. Third, the built and social environmental factors that influence subjective and objective security are not always identical. A high-density and highly mixed environment would reduce fear of crime, but may accelerate crime. To reduce both fear and crime, it is recommended to add cul-de-sacs, improve the sense of enclosure, increase the amount of greenery, and eliminate various types of physical disorder. As for the effect of social disorganization, concentrated disadvantaged communities tend to have high levels of fear and are more prone to violent crime; population mobility can help reduce fear of crime; residential heterogeneity would exacerbate criminal behavior. Our findings help to clarify the differential explanatory power of classical crime geography theory for subjective and objective security, which in turn facilitates a comprehensive assessment of the security consequences of environmental intervention policies.

To support the safe and effective growth of regions, resilient city networks should be built in metropolitan areas. Current research is focused on understanding how disaster risk propagates in city networks and assessing network resilience. This study developed a multiplex city network model composed of facility and function based on the fundamental concept of the city network, and investigated the functional, physical, and geographic relationships across networks. Second, we examined the resilience of the multiplex city network in terms of both the structure and function and the network as a whole and local areas. Third, we illustrated how disaster risks spread in the multiplex city network from three perspectives—propagation path, propagation process, and propagation impact, which establish a logical relationship between disaster impact and network resilience. Lastly, we proposed a three-step framework for assessing the resilience of multiplex city networks: modeling the multiplex city network, simulating risk propagation of the network, and using indicastors to measure the network's resilience. The feasibility and validity of the framework were verified by the case study of resilience assessment of the "road-people's flow" multiplex city network in the Wuhan metropolitan area under the impact of flooding. The case results demonstrate that as disaster risks spread through the network, certain cities' structural and functional status will alter, drawing attention to these changes as a means of enhancing network resilience. For instance, some cities and network paths will have much less connectedness and as a result, these cities should improve their own preparedness during the latent phase of disasters and recovery capacity during the mitigation phase. Certain cities and paths have an absorptive capability during the risk outbreak period that helps keep the city network operating as intended. This research offered a fresh look at the theory and methodology of city network resilience assessment that considers disaster risk transmission. It concentrated on the real requirements for the development of regional network security. By examining and altering the interactions between cities, the suggested framework can contribute to making city networks more resilient.