This study integrates the “New” and “Quality” aspects of new quality productive forces, along with the constituent elements of productivity, into an evaluation index system. The development level of new quality productive forces in China’s provinces from 2011 to 2022 is assessed using the entropy weight method. Subsequently, the nonlinear Granger causality test is employed to examine the spatial correlation of new quality productive forces. Finally, the social network analysis method and exponential random graph model are utilized to analyze the structural characteristics and influencing factor of this spatial correlation network. The results show that the level of new quality productive forces in China has been rapidly improved during the sample investigation period, and the level of new quality productive forces in the eastern coastal area is relatively high. In the spatial correlation network, the eastern provinces mainly play the role of “engine”, while the central and western regions mainly accept the spatial spillover from the high-level regions. The spatial correlation of new quality productive forces is mainly one-way conduction, and the situation of “mutual benefit” coordinated development among provinces has not yet formed. In terms of the formation mechanism, improving the level of economic development, the proportion of tertiary industry, the level of marketization and the degree of opening degree will be conducive to the formation of the spatial correlation of new quality productive forces. The proximity of geographical distance and economic distance promotes the transmission of the spatial correlation of new quality productive forces among provinces, and forms internal circulation subgroups among provinces with similar levels.

Taking eight comprehensive economic zones in China as the research area, this paper constructs a new quality productivity index system based on new workers, new labor materials and new labor objects, and explores the development level, dynamic evolution, spatial differentiation and convergence of new quality productivity in eight comprehensive economic zones in China by using entropy method, kernel density estimation, Dagum Gini coefficient and conditional β convergence model respectively. The results show that: (1) The average development level of new quality productivity in eight comprehensive economic zones in China shows an increasing trend year by year from 2015 to 2022, and the development level in the eastern coastal area is the highest and that in the northwest area is the lowest regardless of the comprehensive level or the subdivision dimension of constituent elements; (2) The absolute difference in the development level of new quality productivity in each economic zone has become larger, while the relative difference has gradually narrowed; The difference between subgroups is the main source of the development difference of new quality productivity in eight comprehensive economic zones; (3) The development of new quality productivity in northern coastal areas, eastern coastal areas, southern coastal areas, the middle reaches of the Yellow River and the middle reaches of the Yangtze River is characterized by conditional β convergence; The β coefficient in the northeast, southwest and northwest regions is negative, but it fails to pass the statistical significance test, and there is no significant conditional β convergence effect. The research conclusion provides a basis for analyzing the temporal and spatial pattern of new quality productivity in eight comprehensive economic zones and has policy implications for promoting the coordinated development of regional new quality productivity.

Based on China’s interprovincial panel data from 2010 to 2022, the entropy method, nonparametric Kernel density estimation, spatial autocorrelation, and Geodetector are comprehensively applied to explore the spatio-temporal evolution of China’s interprovincial common prosperity level and its influencing factors. The results show that: (1) During the study period, China’s interprovincial common prosperity level has been increasing year by year, and the differences in the interprovincial common prosperity level have been narrowing, with higher common prosperity levels in Beijing, Shanghai and Zhejiang, and lower common prosperity levels in Xinjiang, Gansu, Qinghai and Xizang. (2) There is a significant spatial correlation between interprovincial common prosperity level in China, and the correlation is “M” type evolution. (3) The core factors influencing the spatial differentiation of China’s interprovincial common prosperity level are the level of economic development, the level of opening up to the outside world, and digital inclusive finance; There are obvious differences in the influence of different factors on the spatial differentiation of the common prosperity level, and the interaction between the factors enhances the explanatory power of the spatial differentiation.

Through a systematic review of 418 articles published in the Island Studies Journal from 2006 to 2023, this study analyzes the main topics of international island research with the aim of providing insights for the theoretical development and expansion of research perspectives in domestic island geography. The research primarily covers seven directions: island concepts and theories, island economics, island politics, island social culture, island migration, island ecology, as well as the Anthropocene, climate change and sustainable development. Notably, the fields of island concepts, economics, and social culture have yielded substantial results, while attention to other areas has been relatively limited. In recent years, influenced by geographic thought, discussions on island theory have deepened, particularly regarding space and mobility. Additionally, island research has critically reflected on traditional topics, enhancing focus on issues such as archipelagos, migration, colonialism, and sustainable development. In contrast, domestic research on islands shows an overall state of stagnation. Moving forward, domestic island geography should actively draw on international cutting-edge theories and methods to provide policy recommendations for the sustainable utilization of island regions and the sustainable development of marine territorial resources.

This study utilizes the entropy method to calculate the new productive forces within the Grand Canal cultural belt thoroughly exploring its spatiotemporal differentiation characteristics, leveraging the XGBoost-SHAP machine learning model, investigated the influencing factors to explore their interactive effects.Research indicates that the development level of new productive forces in the Grand Canal cultural belt follows a fluctuating growth pattern. In contrast to green productivity and technological productivity, digital productivity constitutes a significant proportion of the new productive forces.There are notable disparities in the development level of new productive forces across different regions. Some cities at the prefecture level in Beijing, Jiangsu, and Zhejiang Provinces excel in their development of new productive forces, while Henan and Anhui provinces lag behind. Furthermore, the level of new productive forces in various regions experienced a general improvement in 2020.The aggregation effect along the Grand Canal presents a “triangular” distribution phenomenon, and shows the development trend of “two corners of the aggregation folder dispersion”.The density of mobile phone users per one hundred individuals and total factor productivity emerge as predominant factors influencing the quality of new productive forces in the Grand Canal cultural belt, with interactions observed among these pivotal factors.This study provides insights into capturing the spatiotemporal differentiation characteristics of new quality productive forces, while also offering guidance on how to better navigate their development based on influencing factors.

Some models are used to analyze the coupl-coordination degree and the influenc-factors among them in China provinces during 2015—2021. The results show that:(1)Digi-economy and scien-tech innovation of each region are significantly improved but the eco-environment level showed a fluctuating trend.(2)The coordination level of both the binary system and the composite system was increased, where digi-economy system is the most. (3)The spatial distribution of coordination level of the composite system showed that the east is higher than the center and the west, and the coast than the interior, and there is a positive correlation between the distribution and the development level for those regions.(4)The degree of the influen-factors, whose are govern-financ support, opence to outside world, economic development and advanced industrial structure, is obvious spatial difference and decreasing in order. Based on the coupling resulsts, proposed countermeasures to promote the coordinated development in each region and even in the whole country.

From a geopolitical perspective, global shipping is no longer a microeconomic activity, but a historical development condition for maintaining world connections and resource flows. Accordingly, a theoretical research framework has been constructed from three dimensions “country, routes, and chokepoints”. Further empirical analysis reveals that key resources face significant risks. Various resources rely on a few countries or the Middle East. Shipping must pass through key geopolitical regions, with the Middle East routes presenting prominent risks. Major chokepoints are identified as high-risk area, where U.S. military bases exert strategic influence. The research then proposes countermeasures for governing geopolitical risks in resource shipping.

Taking 1 749 counties in China from 2015 to 2021 as the research object, this paper constructs a county-level common prosperity index evaluation system from the three dimensions of affluence, commonality and sharing of development results, and uses the entropy weight method to measure it, and at the same time, the regional differences and spatiotemporal evolution characteristics of county-level common prosperity development in China are investigated. The results show that the level of common prosperity in counties across the country has increased significantly, and the common prosperity among counties has a significant positive spillover effect, but the overall level is not high. Regional development differences show that the counties in the eastern region have the highest level of common prosperity, but the central and western regions have the largest growth rate, and gradually give full play to their late-mover “catch-up advantages”. The results of spatiotemporal evolution show that the spatial distribution of common prosperity presents the characteristics of “eastern leading, overlapping high and low, and obvious agglomeration”. The development of common prosperity between counties is gradual, and there is a “club convergence” effect and a certain path dependence.

Based on the inter-provincial panel data from 2011 to 2020, the development level of common prosperity is measured using the vertical and horizontal split grade method, and the Markov state transition analysis is conducted. The spatiotemporal geographical weighted regression model is used to explore the main factors affecting the development of common prosperity. The research findings are as follows: (1) During the inspection period, the development level of common prosperity in China shows an upward trend, but the regional differences are different. The development level of common prosperity in the east is the highest, while that in the west is the lowest; (2) When there are differences in the development of common prosperity in neighboring provinces, the probability of common prosperity development in this province being affected and shifting is different, and the development of common prosperity has significant space-time inertia and path dependence; (3) The strength of the influencing factors of the development level of common prosperity shows obvious spatial and temporal heterogeneity. Among them, opening up, digital finance level, and economic development level promote the development of common prosperity, while industrial structure inhibits the development of common prosperity.

91 national and provincial-level traditional villages on Hainan Island were selected as the research objects, and their distribution characteristics, influencing factors, and driving mechanisms were explored using methods such as GIS spatial analysis, geostatistical methods, and geographic detector models based on optimal parameters. The results show that: (1) Traditional villages on Hainan Island have strong spatial distribution imbalance and obvious clustering characteristics, showing an overall pattern of “high in the east and low in the west, high in the north and low in the south, with multiple points in one cluster”. (2) In terms of the connection between natural and cultural elements, most traditional villages on Hainan Island tend to be distributed in urban intersections or suburban areas with low terrain, abundant water sources, high vegetation coverage, and concentrated cultural relics units, and rely on county roads as connecting roads. (3) In terms of influencing mechanisms, overall, regional cultural influence is the strongest, followed by economic development level, and the natural environment is the weakest, with enhanced interaction between various factors. In the stage of the formation of traditional villages on Hainan Island, natural and cultural factors dominate the formation of villages, while natural factors, especially resource conditions, influence the development of traditional villages. Economic and cultural factors dominate the transformation and protection of villages. (4) Through comparative analysis of various provinces, cultural factors have a dominant driving role in Hainan Island and some southwestern regions, and cultural development should be valued, cultural diversity should be fully utilized, and cultural background should be protected.

Taking the 105 counties (cities) in Henan Province as the research object, this paper uses the super-SBM model to measure the territory spatial efficiency and uses the modified gravity model and social network analysis to analyze the spatial correlation network from 2000 to 2022. The conclusion is as follows: (1) There are significant differences in efficiency gradients among different spaces from 2000 to 2022, with both spatial dynamics and heterogeneity characteristics coexisting. (2) The evolution level of the efficiency network transitions significantly, but each space is still dominated by a five level network with low connectivity levels, and the spatial correlation in the southern region of Henan is at the edge of the network. (3) The network density first increases and then decreases, and the spatial correlation network pattern appears, but there are still problems such as poor network structure stability and loose relationships. (4) The core position of the network presents a ribbon structure from Zhengzhou-Luoyang to Zhengzhou-Kaifeng-Xuchang, and Zhengzhou has always had a strong spatial spillover effect. Xinxiang and Xuchang are key nodes connecting the northern and southern regions of Henan. Moreover, the spatial clustering phenomenon between each plate is significant, but it has not formed a good cycle transmission framework.

The rural areas around large cities serve as typical regions for rural revitalization and urban-rural integration. Analyzing the rural transformation process and the driving mechanisms of this special area will contribute to a deeper understanding of the laws governing rural development. This study, based on actor-network theory, uses Xiantan Village in Zhejiang Province as a case study example and employs a systematic approach to analyze the process and driving mechanisms of the transformation and development of rural areas in the vicinity of large cities. The study shows that: (1)Xiantan Village has transformed from a production-oriented rural area to a consumption-oriented one and then to a multifunctional rural area. The rural transformation actor network of Xiantan Village, including both human actors such as Deqing County government, Moganshan Town government, village committees, homestay owners, and villagers, and non-human actors such as houses and landscapes, has also experienced two stages, namely, construction and transformation. (2)The core actors have shifted from homestay owners, consisting of foreign value discoverers, rural elites, and local farmhouse restaurant owners, to their collaboration with local governments. The OPP (obligatory passage points) has changed from “developing homestay economy and building a consumption-oriented rural area for urban residents” to “building a multifunctional rural area integrating production, ecology, and life functions”. (3)Based on the actor network, rural transformation is jointly driven by rural situation changes, subject interactive structures and policy tool combinations. In the future, rural areas around big cities need to combine their own endowments and historical foundations, attach importance to the absorption of diverse subjects, and coordinate the promotion of rural transformation and development.

In order to achieve the balance between economic development and carbon emission reduction, the Tapio decoupling index, spatial autocorrelation and spatial Markov chain models were used to explore the spatial and temporal dynamic evolution characteristics of inter-provincial carbon emission decoupling in China from 2001 to 2022, and based on the convergence model conducts club division analysis so as to reveal the evolution of inter-provincial decoupling relationships in China, aiming to seek the path of low-carbon development. The results show that: (1) The type of decoupling in China’s provinces gradually develops from diverse coexistence to dominated by weak decoupling from 2001 to 2022, showing an overall improvement in development. (2) The global spatial positive autocorrelation of carbon decoupling is notable, with local areas showing a tendency towards LL aggregation. Additionally, the east-west spatial differentiation is becoming increasingly pronounced, with polarization effects occurring. (3) There are few leap-forward decoupling transfers, and the transfer probabilities vary depending on the decoupling status of the neighborhood. Provinces that achieve ideal decoupling can generate positive spatial spillover effects and promote low-carbon lock-in, whereas provinces with undesirable decoupling experience negative spillover effects. (4) The overall level of decoupling in China has not yet reached the same steady state. A total of 6 convergence clubs were obtained through local testing, showing a significant convergence effect internally.

Through comprehensive application of coupling coordination model and geographical detectors, this paper conducts an empirical analysis on the level of ecosystem services and economic development, coupling coordination status, and driving factors in Shanxi Province from 2009 to 2019. The research shows that: (1) Affected by land use changes, the land-average ecosystem service value in Shanxi Province from 2009 to 2019 shows a trend of first decreasing and then increasing, showing the spatial distribution characteristics of high value in the south and low in the north, high-value areas and low-value areas are staggered from east to west. (2) During the study period, the level of economic development has steadily increased from 0.21 to 0.26, showing the spatial distribution characteristics of a combination of “point distribution” and “band distribution”. (3) The coupling coordination degree of the two systems increased from 0.57 to 0.60 during the study period. The coupling coordination state is dominated by basic coordination and intermediate coordination. The type of coupling coordination in the whole province shows a trend of shrinking economic lag area and gradual expansion of ecological lag area. (4) During the study period, the general public budget revenue, per capita GDP and coal reserves have the greatest impact on the coupling coordination degree, and the interaction effect is mainly enhanced by two factors, supplemented by nonlinear enhancement.

Regional holographic theory applies holographic cognitive principles to regional studies,and it is a deconstruction of regional research with a philosophical framework. The core idea is that the region is a multi-level, multi-dimensional and bounded holographic system composed of countless interconnected holographic elements. Each holographic element is the epitome of the whole region, and the correlation between holographic elements drives the evolution of the region. The theory dialectically treats the integrity and partiality of the region, unifies the uniqueness, integrity and relevance of the region from the perspective of information, and provides a new theoretical perspective for regional research. Based on holographic theory and regional research, this paper systematically sorts out the concept, structure and relationship of holographic region, as well as the theoretical connotation and application paradigm of regional holographic theory, and carries out application practice in four aspects: holographic geographic database, regional holographic integrated development strategy, regional holographic coordinated development model and acupuncture treatment of diseases in big cities, with a view to providing theoretical reference for regional coordinated development in the new period.

This paper explores the spatial distribution characteristics and influencing factors of the first, second and third batches of key demonstration villages of beautiful countryside in Anhui Province by using the methods of nearest neighbor index, unbalanced index, kernel density estimation and geodetector. It is found that: (1) The spatial distribution of the key model villages in Anhui Province showes clustering and unbalanced characteristics. Although the spatial distribution of each batch of model villages tends to be balanced, the spatial distribution of created model villages tends to be clustered. (2) The evolution of spatial distribution pattern of model villages is characterized by “the number of major agglomerations remains unchanged, the scope keeps expanding and the degree of agglomeration keeps deepening”. The final distribution shows “two horizontals and three verticals” pattern. The “two horizontals” are the agglomeration belt along the Yangtze River and the agglomeration belt along the north bank of Huaihe River. The “three verticals” are the clustering belt along Fuliu Railway-the eastern foot of Dabie Mountain in central Anhui, the clustering belt along Jiuhua Mountain-Huangshan Mountain in southern Anhui, and the clustering belt around Nanjing in southern Anhui. (3) Road density, GDP per capita, and river density are the dominant factors of spatial differentiation of demonstration villages. The interactions of road density, GDP per capita with the distance to the 5A scenic spot respectively have the greatest effects on the spatial differentiation of demonstration villages. Overall, location access and government intervention are the main influencing factors of the spatial differentiation of model villages.

Taking 64 units of county level in Fujian Province as research objects, this paper comprehensively used social network analysis method, QAP analysis method and GIS spatial analysis to explore the evolution characteristics and influencing factors of county level economic link network structure in Fujian Province from 2013 to 2019. The findings indicate that: (1) From 2013 to 2019, the intensity of county level economic links in Fujian Province increases year by year, but the spatial imbalance is persistent. The network pattern evolution showed a significant “Matthew effect” and formed an obvious three-core structure. (2) The centrality of Xiamen, Zhangzhou and Quanzhou metropolitan circle and Fuzhou metropolitan circle along the east coast of Fujian is significant, followed by the central Fujian region represented by Sanming urban area. Fuzhou urban area, Sanming urban area, Xiamen urban area and Longyan urban area play an important intermediary role in their respective large areas. (3) The four factors of administrative affiliation, cultural affiliation, resource agglomeration and factor circulation have significant positive effects on the county level economic link network, among which the influence of administrative and cultural factors is weakening. The two factors of elevation and traffic distance have a significant negative influence, and the influence of traffic factor is increasing.

The spatial differentiation and evolution of urban housing price is an important perspective to analyze urban spatial structure. This paper analyzes the spatial structure and evolution of housing prices based on the housing transaction data in Shanghai from 2015 to 2022 using the geographical weighted regression model to explore the spatio-temporal changes of the impact of education, transportation, location and other factors on housing prices. The study indicates that the housing price in Shanghai generally presents a decreasing structure with multiple centers and circles, and there is a trend of high concentration in the central urban area and residential suburbanization; The spatial pattern of housing price presents the pattern of “circle+fan+enclave”. The housing price is significantly affected by the distance from the city center, education resources, and transportation convenience. In terms of time, the impact of high-quality education resources and park green space on the price of neighboring houses is increased, while the impact of transportation convenience on the house price is decreased. In terms of space, the influencing factors have significant spatial heterogeneity, and education resources, park green space and commercial supporting resources have a greater impact on suburban housing.

Taking Xinjiang as an example, the spatial autocorrelation, multiple linear regression, geographical weighted regression and other models were used to explore the spatio-temporal evolution characteristics and driving factors of non-grain conversion of cultivated land in the northwest arid region. The results showed that: (1) From 2000 to 2020, the non-grain rate of cultivated land in Xinjiang increased from 57.33% to 64.50%. Among them, in the development stage of characteristic agriculture (2000—2007), the degree of non-grain cultivated land increased continuously, in the optimization stage of agricultural layout (2007—2014), the degree of non-grain cultivated land showed a “W” shape, and in the stable and high-quality development stage of agriculture (2014—2020), the degree of non-grain cultivated land fluctuated slightly but not much in the stable. (2) During the study period, there was a significant difference in the spatial distribution of the non-grain level of cultivated land in Xinjiang, showing a distribution trend of “high in the east and low in the west” as a whole, while there was a clustering feature. The areas with serious degree of non-grain were mainly concentrated in Bazhou and Turpan, while the areas with low degree of non-grain were concentrated in Kezhou and Hotan. (3) Urbanization rate, precipitation, sunshine duration, food protection policy, land transfer rate, land productivity, per capita cultivated land area and per capita GDP were the main driving factors of cultivated land non-grain conversion in Xinjiang, and the influence direction and intensity of each driving factor showed obvious spatial heterogeneity. Based on this, differentiated management and control measures are put forward, which has important reference significance for Xinjiang cultivated land planning and management.

Based on the 30 m×30 m resolution land use remote sensing data of China in 2000, 2010, and 2020, this study analyzed the spatio-temporal pattern and coupling coordination characteristics of urban-rural construction land in China. The bivariate spatial autocorrelation analysis model was used to explore the spatio-temporal correlation and dependence of the spatial distribution characteristics of urban-rural construction land. Concurrently, the coupling coordination and decoupling model was employed to reveal the coordinated development level of urban-rural construction land and the decoupling relationship between them. The findings were revealed as follows: (1) From 2000 to 2020, the area of urban-rural construction land in China continued to increase, with the transfer of cultivated land and grassland representing the primary source of this expansion. (2) The level of coordinated development of urban-rural construction land showed a downward and then upward trend over time, while the distribution pattern of high in the northeast and low in the southwest was shown in space. (3) The types of construction land decoupling were mainly weak decoupling with both urban and rural growth and ahead of the growth rate of urban construction land. Compared to 2000—2010, there were notably more strong negative decoupling and expansionary negative decoupling in 2010—2020, indicating that the development of urban construction land was ahead of rural settlements.