The issue of "regional development" has been a core theme throughout national development planning and economic geography study. Currently, China has established a "3+N" regional strategic framework, which consists of three core strategies—the coordinated regional development strategy, major regional strategies, and the major function zoning strategy—alongside "N" additional regional development strategies such as the new urbanization strategy. This paper reviews the formation and evolution of China's regional strategic framework, analyzes the internal mechanisms of regional strategy superposition from an economic geography perspective, and explores pathways to maximize its effects. This study suggests that the regional economic system shaped by superposing strategies exhibits five key characteristics: regional differentiation, interconnectedness, scale nesting, functional transmission, and comprehensive integration. The economic geographic mechanism through which superposing regional strategies regulate and optimize the regional economic system lies in: guiding the rational allocation of production factors based on comparative advantages, leveraging positive external spillover effects through inter-system linkages, achieving effective transmission of strategic functions across different scales by coupling regional strategy scales with functional scales, and generating emergent effects through strategic synergy. Together, these factors amplify the overall impact of superposing regional strategies. This study proposes that maximizing the effects of superposing strategies requires enhancing strategic synergy during regional strategy upgrades, leveraging the overarching and foundational role of major functional areas, systematically optimizing the Regional Coordinated Development Strategy and Regional Major Strategy, and exploring comprehensive functional zones and new territorial spatial systems. This research aims to provide theoretical foundations and decision-making references for formulating the "15th Five-Year Plan" and optimizing regional economic layouts while improving spatial governance efficiency during the "15th Five-Year Plan" period.

Taking 153 countries as the research subjects, this study decomposes economic vulnerability under the background of population aging into three dimensions: exposure degree to aging, sensitivity, and adaptive capacity. Based on the Vulnerability Scoping Diagram (VSD) framework, it constructs an economic vulnerability assessment index system for aging. Based on the methods of functional evaluation models, spatial heterogeneity indices, and ordered Logit regression models, it quantitatively analyzes the spatial differentiation patterns and evolutionary trends of global economic vulnerability to aging (GEVA) from 2010 to 2020, and explores its underlying drivers. The results show that: 1) From 2010 to 2020, global exposure degree to population aging exhibited an increasing trend, with low-exposure regions predominantly in developing countries such as Africa, Asia and Latin America. High-exposure regions concentrated in developed regions such as Europe, Oceania, North America, and East Asia. 2) During the study period, GEVA increased significantly, with 49.67% of countries experiencing vulnerability in 2020. Low-vulnerability countries are primarily located in Africa, Asia, and Oceania, whereas high-vulnerability countries are concentrated in Europe, North America, and South America. 3) Spatial heterogeneity exists between exposure degree to population aging and GEVA. Countries with low-exposure degree but high vulnerability are mainly distributed across economically developing regions such as Africa, Asia and Latin America, while those with high-exposure degree but low vulnerability are predominantly found in developed regions such as Europe, Oceania, and North America, along with select emerging industrialized countries. 4) Sensitivity factors including health expenditure, savings level, fiscal expenditure, and labor participation rate, as well as adaptive capacity factors including industrial structure, industrial diversification, foreign direct investment, labor quality, employment instability, technological innovation capability, and fiscal dependence,were identified as significant influences on GEVA evolution.

County-level factor agglomeration-diffusion capacity is a key driver for advancing urban-rural integration development. Integrating the methods of real-coded accelerating genetic algorithm and projection pursuit clustering model (RAGA-PPC), kernel density estimation, and Markov chain, this study examines the spatial pattern and multidimensional dynamic evolution of factor agglomeration-diffusion capacity across 1735 county-level units in China in 2010-2022. The results show that: 1) County-level factor agglomeration-diffusion capacity shows the steady upward trend. There are significant gradient differences among eight comprehensive economic zones, the eastern coastal economic zone remains persistently at the forefront, whereas the northeastern economic zone exhibits relatively weak development. 2) Factor agglomeration-diffusion capacity displays a clear core-periphery configuration: hotspot areas are stably concentrated in the coastal economic zones and the economic zone of the middle reaches of the Yangtze River, while coldspot areas are primarily located in the economic zone of middle reaches of the Yellow River and the greater southwestern economic zone, with their spatial extent gradually contracting. 3) The overall disparities of factor agglomeration-diffusion capacity continue to widen, with interregional differences constituting the dominant source, the disparity between the northeastern economic zone and other economic zones is more significant, while the internal disparity within the greater northwestern economic zone is the smallest. 4) Factor agglomeration-diffusion capacity exhibits strong state persistence, and there is a long-term spatial influence among adjacent counties. Over time, the phenomenon of low-low clustering gradually eases, and the upward mobility trend strengthens. High-level counties exert a pronounced siphoning effect on low-level counties, while generating spillover-driven diffusion effects for medium-level and other counties. These findings provide theoretical foundations and policy-relevant evidence for optimizing county-level factor allocation and promoting urban-rural integration development.

Precisely identifying new quality productive forces and accurately assessing the spatial characteristics of its layout are crucial challenges in the current stage to develop new quality productive forces. This paper integrates text analysis with the Skip-Gram model, employing supervised machine learning alongside data from registered Chinese enterprises from 2000 to 2022 to identify new quality productive forces, analyze the overall trends, spatial distribution, evolution, and agglomeration characteristics of new quality productive forces. From the perspective of overall trends, although new quality productive forces remains smaller in scale compared to traditional productivity, it has consistently maintained a high growth rate, indicating promising development prospects. From the perspective of productivity layout, new quality productive forces have developed rapidly in the northeastern, eastern, and southern coastal regions, as well as central and western cities from 2000 to 2022. By 2022, the development of new quality productive forces across various regions had reached a significant scale, exhibiting a trend of coordinated growth. From the perspective of enterprise dynamics, there is frequent alternation between growth and decline in new quality productive forces among enterprises in different regions. The net surplus of enterprise entries over exits is key to the cultivation and development of regional new quality productive forces. From the perspective of geographical co-agglomeration among industries, the development of new quality productive forces in technological innovation requires compatible service support. This research offers policy guidance for accurately understanding the spatial distribution of new quality productive forces and fostering its cultivation and development.

Based on the panel data from 285 prefecture-level and above cities in China from 2005 to 2023, this study employs a spatial difference-in-differences model to empirically examine the mechanisms and pathways of pilot policy of national new generation artificial intelligence innovation and development (NNGAIID) on urban haze mitigation and carbon reduction in both local and adjacent cities. It's found that: 1) Spatially, urban haze pollution and carbon emissions exhibit distinct regional heterogeneity, with a pronounced "pollution lock-in effect" evident in the "coal triangle area". Temporally, the growth rate of urban haze and carbon emissions has decelerated overall, reflecting a spatial shift toward the northwestern region. 2) The NNGAIID pilot policy significantly contributes to environmental improvement in both local and adjacent cities; this result remains robust across a comprehensive set of robustness checks. 3) Mechanism analysis confirms that promoting technological progress, inhibiting urban sprawl, and facilitating economic agglomeration serve as critical transmission channels for the NNGAIID pilot policy to empower "local-neighboring" cities in reducing haze and carbon emissions. 4) Heterogeneous effects indicate that the dual "local-adjacent" impact is more pronounced in non-resource-based cities and central cities. This paper provides theoretical foundations and empirical evidence to inform the design of targeted policies that leverage artificial intelligence innovation for integrated air quality and carbon emission management under the "Dual Carbon" strategy.

The urban network along the New International Land-Sea Trade Corridor (NILSTC) is undergoing continuous development, and its spatiotemporal evolutionary patterns remain under exploration. This study takes the urban network in the NILSTC region as the research object and constructs a urban association network from 2003 to 2023 based on the headquarters-branch data of listed companies. It systematically explores the evolutionary patterns of network structures and the functional allocation dynamics among nodes. It's found that: 1)The network has transitioned from a dispersed network system to a strongly interactive complex network system. 2) The hierarchical structure of the network is constantly being refined, evolving from a "dual-core-driven" model to a "multi-core-driven" model. It has initially formed a hub-and-spoke network dominated by provincial capital city linkages, with a prominent core-periphery structure and path-dependent characteristics. 3) Most cities exhibit consistency between their importance and control capacity, provincial capitals have maintained long-term dominance in core, high-control positions, while strategic hub cities and emerging industry-oriented cities have shown significant functional upgrades. 4) The spatial form of network community have evolved from extreme fragmentation to a segmented structure of distinct territorial blocks, with reinforced spatial integration and progressively deepening land-sea connectivity. Based on the research conclusions, this study proposes pathways to optimize the urban network along the NILSTC, providing theoretical underpinnings and practical guidance for high-quality development and coordinated regional governance.

This paper identifies the concept of regional innovation resilience, employs a core variable method to measure urban innovation resilience in China from 2003 to 2019 in terms of resistance and recoverability, and uses the methods of exploratory spatial-temporal data analysis and spatial econometric model to explore the spatio-temporal interactions characteristics and influencing factors of urban innovation resilience. The results show that: 1) The overall level of urban innovation resilience in China is low with significant fluctuations. Spatially, low-resilience cities are spreading from the northwestern and southwestern regions toward the northeastern region, while medium-resilience cities are diffusing from the eastern and southern coastal areas toward the middle reaches of the Yangtze River. 2) In the process of urban innovation resilience, there is a negative correlation between resistance and recoverability. The relationship of innovation resilience between neighboring cities generally shifts from competition to collaborative development, but the spatial interactions between low resilience cities exhibit the characteristics of inertia and path dependence. 3) There are positive spatial spillover effects and negative temporal lag effects. government R&D investment and collaborative innovation exert negative and positive indirect effects on urban innovation resilience, respectively. Agglomeration effects and foreign investment have negative and positive spillover effects. The industrial structure has positive direct and spillover effects, while the level of financial development has a significant inhibitory effect on the innovation resilience of both local and neighboring cities.

Based on the panel data of 41 cities in the Yangtze River Delta region from 2000 to 2023, this paper constructs the evaluation index system of green technology innovation level, and uses the spatial kernel density estimation method to analyze the spatiotemporal evolution pattern of urban green technology innovation. Based on the above, it discusses the impact of population aging on urban green technology innovation and its mechanisms by combining the panel fixed effect model and the mediation effect model, and reveals the spatial effect and spatiotemporal heterogeneity of population aging on urban green technology innovation using the spatial panel model. The results show that: 1) The overall level of urban green technology innovation in the Yangtze River Delta region is generally on the rise, and its spatial distribution gradually shifts from polarization to a spatial equilibrium pattern. 2) Aging at the apex has a significant negative effect on urban green technology innovation, while the aging from the base has a significant positive effect on urban green technology innovation. 3) The human capital effects of both aging at the apex and aging from the base are significant, and the human capital effect is an important way for population aging to affect urban green technology innovation. 4) Spatial analysis shows that aging at the apex has a "local-neighborhood" spatial spillover effect, which has an incentive effect on green technology innovation in spatially adjacent cities. 5) Heterogeneity analysis shows that the impact of population aging on urban green technology innovation is more significant in cities with low-level green innovation, and its spatial spillover effect is more significant in cities with high-level green innovation. Moreover, the spatial impact of population aging on urban green technology innovation has a long-term characteristic, but this impact is gradually weakening.

Optimizing the zonal development strategy of territorial space is crucial for sustaining the development of growth-oriented metropolitan areas. Selecting the Changsha-Zhuzhou-Xiangtan Metropolitan Area as a case study, this study establishes a comprehensive evaluation framework for economic-ecosystem resilience and their coupling coordination. By assessing ecological sources and ecological security patterns, it examines the adaptive interactions of territorial spatial functions from the multi dimension and proposes the optimization strategies for the zonal development in Changsha-Zhuzhou-Xiangtan Metropolitan Area. The results show that: 1) Economic resilience and ecological resilience both show a core-periphery divergence with north-south differentiation pattern, while the economic-ecosystem resilience shows a gradient feature which is higher in the north and east of metropolitan area, and lower in the south and west of metropolitan area. The economic-ecological coupling coordination degree (CCD) exhibits a reverse core-periphery pattern, with the central urban area having low coordination (CCD<0.5) and eastern regions like Liling and Liuyang achieving high coordination (CCD>0.68). The higher the economic development level, the more obvious the mutual feedback and constraint effects of economic-ecological coordinated development. 2) The ecological security pattern index in research area is primarily at medium to high level. The three-tier ecological network configuration of "expansion along the river, green heart as the core, outer forest as the buffer" further confirms the spatial distribution characteristics of ecological source areas being "dominated in the east and supported in the south", highlighting the significant advantages of the regional ecological background and serving as the key spatial foundation for the integrity of the regional ecosystem. 3) The territorial space of the Changsha-Zhuzhou-Xiangtan Metropolitan Area has been rezoned into nine functional types. The study analyzes the characteristics of each zone and defines the key future directions—eastward integration and westward coordinated development—as well as the optimization strategies for each.

Focusing on Hefei's central urban area and based on the multi-source data such as Landsat data, NPP-VIIRS-like nighttime light data, land cover data, green space data, and building footprint data, this study systematically investigates the gradient differences and marginal effects of urban morphological indicators on heat island intensity using the DEMATEL-ISM model with GBRT (Gradient Boosted Regression Trees). Key findings reveal that: 1) Heat island intensity increased with urban expansion from 2006 to 2020, but decelerated over time. 2) Urban morphology indicators exhibit gradient-dependent impacts on urban heat island intensity. Critical optimization pathways vary across development gradients: land-use configuration dominates in high-development zones, while green space patterns are prioritized in low-development zones. 3) Marginal effects of morphological indicators show distinct gradient variations. The intensity and direction of key indicators' impacts shift with their values, accompanied by divergent thresholds and positive/negative critical points.

Multi-Channel Network (MCN), as internet celebrity incubators, serves as a critical link connecting internet celebrities, digital platforms, and manufacturers in the internet celebrity economy industrial chain. Exploring their location choice characteristics and influencing factors holds significant implications for constructing the theory of enterprise location behavior in the digital economy era and guiding the practice of regional industrial development. Based on the data from the Douyin platform, this study employs the exploratory spatial data analysis (ESDA) to examine the location choice characteristics of MCN in China and uses spatial econometric models to reveal their influencing factors. The results indicate that: 1) Chinese MCN is characterized by large-scale disparities and wide distribution, with a long-tail distribution in quantity and significant inter-city differences. Sixty-one percent of the enterprises are concentrated in the top 20 megacities, while some MCN has sunk to small and medium-sized cities as well as central and western regions. 2) MCN presents a spatial pattern of "overall dispersion and local agglomeration", distributing across regions and cities of different scales. Meanwhile, four high-density agglomeration areas have formed, namely the Yangtze River Delta Urban Agglomeration, Pearl River Delta Urban Agglomeration, Beijing-Tianjin-Hebei Urban Agglomeration, and Chengdu-Chongqing Economic Circle, showing the coexistence of "physical agglomeration" and "virtual agglomeration". 3) There is a significant negative spatial spillover effect in the location choice of MCN. Skilled talents, institutional thickness, production proximity, information proximity, public service facilities, green coverage area, and social vitality exert significantly positive impacts, while industrial foundation has a significantly negative impact. This study aims to provide references for the industrial layout of China's internet celebrity economy and the industrial development path selection of late-developing regions.

Promoting the development of core digital economy enterprises is the core engine for consolidating the foundation of digital economy development and driving high-quality economic development. Based on the data of core digital economy enterprises in 284 cities of China from 2000 to 2022 at the micro-enterprise level, this article uses the methods of the Mann-Kendall test, kernel density analysis, standard deviation ellipse analysis, and geographical detectors to reveal the spatiotemporal differentiation characteristics and influencing factors of core digital economy enterprises in China. The results show that: 1) The development of core digital economy enterprises in China exhibits the characteristic of phased transitions, with 2011 as an inflection point, transitioning from a "low-speed foundation-laying period" to a "high-speed growth period". The structure of digital core enterprises simultaneously diverges, with digital technology application enterprises accounting for the largest proportion, while digital factor-driven enterprises grow the fastest. 2) Overall, core digital economy enterprises in China present a stepped spatial distribution pattern of "high in the east of China and low in the west of China", while also exhibiting high regional agglomeration characteristics in the Pearl River Delta and Yangtze River Delta. 3) From the perspective of spatial distribution directionality and gravity center trajectory, the development of core digital economy enterprises in China exhibits a "southwest-northeast" contracting distribution, with the gravity center showing a spatial characteristic of "first shifting eastward and then northward". 4) Talent, innovation environment, and digital infrastructure factors are important factors explaining the spatial differentiation of core digital economy enterprises in China. Local governments should tailor measures to local conditions, combine regional endowments, and differentially arrange core digital economy industries. It should continue to optimize the innovation ecosystem and talent environment, enhancing their radiation ability in high-end digital industries in the eastern coastal areas. In the central and western regions, it should increase investment in digital infrastructure and focus on cultivating and introducing digital technology application industries that are integrated with local traditional industries, in order to narrow the regional digital divide and promote the balanced and coordinated development of China's digital economy.

Based on the headquarters' branch data and patent cooperation data, this paper constructs the spatial correlation network of the biomedical industry chain and innovation chain (hereinafter referred to as "dual chains") in the Yangtze River Delta, uses the multivariate network coupling model to identify its coupling characteristics, and introduces the weighted link between specific cities through the system to promote the production spatial correlation network to approach the Pareto optimal state. The results show that: 1) In terms of spatial pattern, the industrial chain presents a strong triangle linkage of the "Shanghai-Jiangsu-Zhejiang", while the innovation chain shows a unipolar leading "core-edge" structure taking Shanghai as the core. 2) In terms of the coupling characteristics, weak coupling is dominant within the industrial chain, especially in the manufacturing of APIs and preparations. The strong coupling characteristics within the innovation chain are significant, but the technical innovation barriers are still high. In terms of the inter-chain coupling of "dual chains", the upstream basic research is disconnected from the innovation of raw materials, there are "three low" bottlenecks in the midstream clinical transformation and device autonomy, and the efficiency of downstream market access and capacity allocation is not high. 3) The optimization path simulation reveals that improving the internal coupling of the innovation chain is the key to the gain of network efficiency. Industrial collaboration and innovation integration need to be promoted in stages, while the spiral dimension of dual chain conjugation needs to continue to strengthen the link cultivation mode of "supporting the strong with the weak", especially the coupling strength of the finished drug link in the middle reaches of the "dual chains".

Based on the panel data of 502 counties in the Yangtze River Economic Belt from 2012 to 2023, this study employs ArcGIS spatial analysis, coupling coordination models, and spatial econometric models to examine the spatiotemporal evolution of the coupling coordination between rural industrial integration and green agricultural development, along with its influencing factors. Results indicate that: 1) The relationship between rural industrial integration and green agricultural development in the Yangtze River Economic Belt shifted from moderate imbalance to primary coordinated. 2) Significant regional disparities exist in the coupling coordination levels among counties of the Yangtze River Economic Belt, with gaps continuously widening. It has consistently maintained leading coupling coordination levels in the middle and lower reaches of the Yangtze River Economic Belt, while it is at the relatively lower level in the upper reaches of the Yangtze River Economic Belt. 3) There is a significant positive spatial spillover effect in the coupling coordination degree between rural green development and rural industrial integration, with this spillover effect strengthening annually. 4) Population density, public budget expenditures, economic development and agricultural economic contributions exert varying degrees of influence on the coordinated development of agricultural green development and rural industrial integration. Among these factors, the population density exerts the strongest influence.

In the pursuit of China's "dual-carbon" goals, green financial agglomeration (GFA) plays a crucial and increasingly prominent role. Based on the panel data from 30 provincial-level regions of China from 2010 to 2021, this study measures the spatiotemporal evolution of GFA level and carbon peak pressure through the entropy method, employs spatial Durbin model to examine the the local and spatial spillover effects of GFA on relieving carbon peak pressure, and further tests its underlying transmission mechanisms. The results show that: 1) In terms of spatiotemporal dynamics, carbon peak pressure is relatively high in northwest and northeast China but low in eastern China, gradually forming a distribution pattern which is higher in the north of China and lower in the south of China. 2) GFA significantly reduces carbon peak pressure and exhibits clear spatial effects. Its local mitigation impact is primarily transmitted through structure upgrading, green technological innovation, and social supervision, while industrial structure upgrading plays a more pronounced mediating role in the spatial spillover effect. 3) Development stage and geographic location substantially influence the effectiveness of GFA. After the carbon-peaking target was proposed, strengthening policy support and enhancing pollution-control measures further amplified its mitigation effect. Provinces in the southeast of the Hu Huanyong Line benefit from stronger financial foundations and display notable mitigation outcomes, whereas provinces in the northwest regions are constrained by weaker financial infrastructure and exhibit less significant effects. Overall, these findings provide actionable insights for leveraging GFA to accelerate China's carbon-peaking and carbon-neutrality transition while promoting high-quality economic development.

Rural social space is a space constructed by the social relations and behaviors of rural residents, and it is closely related to the rural market, which is a place for commodity exchange and trading activities in rural society. Based on the social network analysis method (SNA), this paper takes Yunshan Town, Qin'an County, Gansu Province, which is located in Longzhong loess hilly region, as the empirical research area, analyzes the evolution process and characteristics of rural social space by constructing a social network model, and explores the interactive relationship and mechanism between the evolution of rural social space and the development of rural market. It's found that:. 1) In the traditional society stage, the urbanization stage and the informationization stage, the rural social space of Yunshan Town has changed significantly, showing an ever-expanding tendency. 2) With the continuous expansion of the rural social space, the interaction between the structure of the rural social network and the nodes of the network in Yunshan Town have become increasingly complex, the rural social network has significant small-world characteristics at different stages of development, the relationship between the network nodes is relatively stable. 3) The evolution of rural social space has a significant impact on the development of rural markets. With the continuous advancement of urbanization and the rapid development of rural informatization, the rural social space in Yunshan Town has been expanding, the traditional functions of the rural market have gradually been eroded and are showing a trend of decline.

Taking 552 national traditional villages in Fujian Province as the research subject, this study employs the methods of optimal parameter geographic detection and multi-scale geographically weighted regression model to analyze the formation mechanism of their spatial patterns and effectively implement strategies. The results show that: 1) The traditional villages in Fujian Province exhibit a concentrated spatial distribution characterized by the phenomenon of "one axis, three cores, boundaries", with a band-like features that runs parallel to the coastline from the northeast to the southwest. The spatial structure of these villages demonstrates two primary modes: "living near the mountains" and "living near the rivers, lakes and ocean". with distinct regional landscape characteristics and foundational elements of landscape construction. 2) The average altitude has the most significant explanatory power regarding the distribution of traditional villages, with natural factors generally exerting a greater influence than human factors. 3) The influence degrees of five factors—average slope, proportion of cultivated land, per capita construction land, urban accessibility, and traffic accessibility—exhibits significant heterogeneity in spatial distribution. 4) Natural ecology plays a fundamental role in shaping spatial patterns, while human ecology serves as an intervening and catalytic force in these patterns. Based on the above, it puts forward two refined implementation suggestions: establishing a robust ecological barrier and fostering a harmonious countryside, while also preserving cultural heritage and enhancing landscape resources. By accurately identifying the heterogeneity and significance of the spatial distribution of villages, this study offers an objective foundation and methodological approach for developing a collaborative strategy for the centralized and contiguous protection of traditional villages, as well as for addressing differentiation within the area.

This paper summarizes the typical facts about the intelligent transformation of Chinese agriculture, constructs a theoretical framework for the agricultural intelligence transformation empowered by the digital economy, and verifies the feasibility and practicality of the theoretical framework through case studies. The research finds that: 1) Trends of intelligent transformation in Chinese agriculture are evident in aspects such as agricultural and rural informatization, the use of intelligent agricultural machinery, the development of rural e-commerce, and the driving forces behind agricultural intelligentization in China. 2) The digital economy can optimize the allocation of factors, increase the supply of data and information, drive the intelligentization of agricultural equipment, enhance agricultural human capital, and promote the intelligent upgrading of the entire agricultural industry chain, thereby empowering and driving the intelligent transformation of agriculture. Based on these findings, a policy system for the digital economy to empower the intelligent development of agriculture is constructed from four implementation paths, a "one body with two wings" promotion mechanism, and four safeguard mechanisms. This paper provides more specific policy insights for the continuous advancement of agricultural intelligentization in China and is of great significance for building a strong agricultural country.

Taking Shishou City as the research object and based on the Landsat5, 8, and 9 remote sensing data from 2000 to 2022, this study calculates greenness index, heat index, humidity index, and dryness index on the basis of Google Earth Engine, and constructs the Remote Sensing based Ecological Index (RSEI), which aims to dynamically monitor the changes in the ecological quality of Shishou City and identify the priority areas for ecological restoration. It uses the methods of spatial statistics and landscape pattern index to explore the spatial and temporal changes and aggregation characteristics of ecological quality in Shishou City. The results show that: 1) The average values of remote sensing ecological index in Shishou City were 0.682, 0.746, 0.769, 0.765 and 0.753 in the five time periods from 2000 to 2022, which were all at the level of "good" or above. 2) The ecological quality of Shishou City in the five periods was "excellent" and "good" in a wide range of areas, accounting for a large proportion. 3) From 2000 to 2010, the ecological quality of Shishou City improved more and degraded less. From 2011 to 2022, the ecological quality of Shishou City improved and degraded basically the same. 4) The Moran's index in Shishou City from 2000 to 2022 was 0.423, 0.550, 0.332, 0.340 and 0.543 in order, showing positive spatial correlation, with high-high clustering and low-low clustering predominating. 5) In the past two decades, the density of ecological quality landscape patches in Shishou City has tended to decrease, the shape of patches has tended to be regular, and similar patches have become more aggregated. The combination of RSEI and spatial statistical analysis is able to monitor the spatial and temporal changes of ecological quality, and identify priority areas for ecological restoration. The methods can provide certain reference for regional ecological security and ecological protection.

The rise of digital inclusive finance has brought new opportunities for poverty reduction and income increase to state-designated poverty-stricken counties. It is of great significance for consolidating the achievements of poverty alleviation and preventing a return to poverty. Based on the data of 815 former state-designated poverty-stricken counties in China from 2014 to 2022, this paper uses the fixed effect model to explore the poverty reduction effect of digital inclusive finance and its realization path. The research results show that: 1) The development of digital inclusive finance has significantly increased the per capita disposable income of rural residents in former state-designated poverty-stricken counties, enhanced the effect of poverty reduction, and played a positive role in consolidating the achievements of poverty alleviation and promoting the sustainable development of poverty-stricken areas. 2) Digital financial inclusion promotes equitable distribution and poverty reduction by leveraging the trickle-down effect and optimizing resource allocation, thereby mitigating wealth concentration. 3) The poverty reduction path of digital inclusive finance mainly relies on the positive role of savings and insurance financial services, while credit services are not conducive to poverty alleviation. Based on the above, this paper puts forward some suggestions: improving the service level and quality of digital inclusive finance, making full use of its trickle-down effect to improve income distribution. Additionally, based on the actual conditions and needs of different regions, differentiated strategies should be implemented that prioritize savings and insurance while adopting a prudent approach to credit expansion.

Based on the traffic network data and land use data of Changsha-Zhuzhou-Xiangtan metropolitan area in 2020, this article uses the transport dominance model to calculate the transport dominance degree, and the equivalent method to measure the value of ecosystem services. Based on the above, it uses the Spearman rank correlation coefficient to test their correlation, the coupling coordination model and the synchronous development model to measure their coupling coordination level, and analyze their constraints. The results show that: 1) There is a significant negative correlation between the transport dominance degree and the value of ecosystem services. 2) The traffic dominance degree of the Changsha-Zhuzhou-Xiangtan metropolitan area shows a significant "center-periphery" structure with obvious administrative directional characteristics. 3) There is a "Matthew effect" in the value of ecosystem services: the medium- and high-value areas show the scattered distribution characteristics and are far from the urban areas, while the low-value areas are concentrated in the urban areas. 4) The overall coordination level between the traffic dominance degree and ecosystem service value of Changsha-Zhuzhou-Xiangtan metropolitan area is low, most districts and counties are caused by the advanced development of transportation, which suggests that the traffic is highly restrictive on the ecosystem, the coordination degree between the two depends positively with the distance from the urban area.

The high-quality development of the tourism industry is an essential aspect of overall high-quality development. The development of new quality productive forces is an intrinsic requirement and a key focus for promoting high-quality tourism development. Exploring how new quality productive forces empower the high-quality development of tourism is a significant practical necessity and an important scientific proposition in the context of China's modernization. Therefore, this study systematically reviews relevant research progress and constructs a conceptual matrix model for empowering high-quality tourism development based on the theory of new quality productive forces and systems thinking paradigms. It also proposes important topics that future research should urgently address and explore. The findings reveal that: 1) The conceptual matrix model serves as a tool to organize and analyze the complex relationships between concepts, providing a systematic, logical, and intuitive theoretical framework to clarify the intrinsic link between new quality productive forces and high-quality tourism development. 2) By using the core concepts of new quality productive forces (technological breakthroughs, factor allocation, industry upgrading) as rows and the classic "six elements" of tourism (food, accommodation, transportation, attraction, shopping, and entertainment) as columns, a 3 multiplied by 6 conceptual matrix model is established to offer theoretical and practical references for exploring a uniquely Chinese path of tourism development. 3) Future research should be grounded in the context of the deep integration of culture and tourism, focusing on the synergy of elements, innovative subjects, and realization pathways that empower the high-quality development of tourism through new quality productive forces. This focus aims to contribute to achieving high-quality development in the tourism industry and advancing China’s modernization.

As a product of tourism development in the era of information and communication technology (ICT), investigating the matching relationship and spatial production mechanisms between virtual and physical spaces of internet-famous tourist spots can deepen the understanding of emerging consumption spaces in Chinese cities. From the perspective of virtual-physical spatial interaction, this paper adopts an empirical-structuralist mixed methodology and employs network text mining, kernel density estimation, and a coupling coordination model to analyze the spatial characteristics and matching mechanisms of virtual and real spaces in Nanjing. The findings reveal that: 1) The physical construction density of internet-famous tourist spots exhibits a pronounced monocentric pattern, whereas the density of virtual spatial perception displays a core-periphery expansion. Overall, the coupling between virtual and physical spaces shows a concentric layered structure, There is a notable mismatch between physical construction and virtual perception in certain central areas. 2) From a mechanistic perspective, spatial practice constitutes a production process dominated by capital, in which interest-based collaboration between platforms and scenic spots, together with users' transformation into tourists, serves as a key bridge linking virtual and real spaces. Spatial representations reflect a virtual-physical interaction embedded within power relations, manifested through strategic negotiations among platforms, scenic spots, governments, and tourists. Finally, representational space embodies a process of social evolution shaped by cultural contexts, characterized by the transformation of profit-oriented consumption culture, socialized experiential culture, and labeled popular culture.

The construction of digital villages serves as a crucial pillar in driving the transformation, upgrading, and innovative development of rural tourism. Based on the panel data of 30 provincial-level regions in China from 2015 to 2024, this article employs the methods of benchmark regression models, mediation effect models, and spatial Durbin models to analyze the impact of digital technology innovation on rural tourism public service and its spatial effects. The results indicated that: 1) The level of rural tourism public service in China at provincial level showed fluctuating growth but a slow pace of increase, with a clear spatial differentiation characteristic which was higher in the eastern and central regions and lower in the western regions. Henan was at the highest level in rural tourism public service, while Shanghai was the lowest. 2) Digital technology innovation has a significant promoting effect on public services in rural tourism, and human capital and industrial upgrading are the main influencing mechanisms. 3) The impact of digital technology innovation on rural tourism public service varies due to differences in geographical location and economic development level, with a more significant promotional effect observed in the eastern region and regions with a high level of economic development. 4) Digital technology innovation has a significant spatial spillover effect on rural tourism public service, with inter-provincial spillovers being stronger than inter-regional spillovers within provinces. Based on the above, it proposes some countermeasures and suggestions for promoting rural tourism public service through digital technology innovation from three aspects: factor input, mode innovation and collaborative governance.

The rapid development of new media technology has led to a high incidence of online public opinion in tourism crisis emergencies. These emergencies are characterized by swift dissemination, broad impact, and increasingly significant negative effects. Taking the ticket refund incident of Harbin Ice and Snow World as a case study, this paper integrates sentiment analysis models and spatial statistical methods to systematically reveal the spatiotemporal differentiation patterns and driving factors of online public opinion in tourism crisis emergencies. The findings indicate that: 1) The evolution of online public opinion exhibits stage-specific and spatially polarized characteristics, with the outbreak phase concentrated in the three northeastern provinces and the decline phase diminishing with increasing spatial distance. 2) Spatial autocorrelation analysis demonstrates that geographical proximity and cultural identity jointly shape the diffusion pathways of online public opinion. 3) Online attention, population migration intensity, economic level, and spatial distance synergistically drive the distribution of online public opinion, with significant interaction effects observed. By conducting a dual-dimensional spatiotemporal analysis of online public opinion in tourism crisis emergencies, this study provides insights for public authorities to accurately identify public opinion risks and formulate differentiated spatial governance strategies.