Based on the panel data of 60 countries from 2008 to 2022, a double difference model was used to causally evaluate the impact of the “Belt and Road” initiative on science and technology innovation and its mechanism of action in the countries along the route. The results show that： The “Belt and Road” initiative has significantly advanced the level of science and technology innovation in the countries along the route, and its policy impact is first manifested as an immediate positive shock, which then shows an overall trend of rapid increase followed by fluctuation and decrease. The “Belt and Road” initiative enables science and technology innovation in countries along the route by advancing their level of development in the areas of trade, investment and economy. The mechanism of China’s role in science and technology innovation for the countries along the route is mainly achieved by expanding the scale of bilateral trade in high technology products with the countries along the route. The findings of the study are of policy reference value in promoting science and technology innovation in China and other countries along the “Belt and Road”, and in achieving quality development along the “Belt and Road”.

With the support of infrastructure geospatial data and OD traffic big data under multiple modes of transportation, the spatial pattern of the potential hinterland and the real hinterland of the main ports of the New Western Land-Sea Corridor is identified, and the spatial matching relationship between the two types of hinterland is evaluated. The results show that: (1) The scope of the two types of hinterlands of the major ports of the New Western Land-Sea Corridor is roughly the same, and there are differences in the spatial distribution of competitiveness within the hinterland; (2) The potential hinterland coverage of the major ports of the New Western Land-Sea Corridor is wide but the competitiveness is weak. The corridor has more attractive potential for freight with a higher value of time; (3) The real hinterland coverage of major ports in the New Western Land-Sea Corridor has significant differences between modes, with highway hinterland being adjacent to ports and railway hinterland being separated from ports; (4) The quality of transportation infrastructure and the level of transportation services are important factors affecting
the matching relationship between the two types of hinterlands. The lack of large-capacity transportation infrastructure leads to weak transportation supply capabilities in Guangxi and the west side of the corridor. The lack of competitiveness of trains restricts the share of corridor transportation in the Sichuan and Chongqing regions. In the future, the supply and demand matching of the construction of the New Western Land-Sea Corridor should be improved, and the construction of the China-Myanmar Indian Ocean New Corridor should be expanded to further ensure the supply security of my country’s overseas strategic key resources.

Based on the panel data of 41 cities in the Yangtze River Delta region from 2011 to 2021, this paper adopted principal component analysis and SDM to empiric-test the empowering effect of digital economy on the high-quality development of the manufacturing industry in the Yangtze River Delta and the comprehensive effect of multiple paths. The results show that: The digital economy in the Yangtze River Delta region can not only significantly enable the high-quality development of local manufacturing industry, but also significantly promote the high-quality development of manufacturing industry in neighboring regions, with the spatial spillover effect accounting for 79.4%; The digital economy enables the high-quality development of manufacturing industry mainly depends on the accumulation of human capital and physical capital, and human capital and physical capital have a synergistic effect, and the path of consumption power has a deviation effect from both human capital and physical capital.

Based on the panel data of 35 counties (cities and districts) in the Guangdong-Hong Kong-Macao Greater Bay Area, the entropy-weighted composite index method, K-Means clustering method and spatial econometric model were used to analyse the dynamic evolution trend and influencing factors of the level of urban-rural integration development in county level in 2010, 2015 and 2021 on the basis of explaining the connotative characteristics of urban-rural integration development in county level. The results showed that the level of urban-rural integration in the counties of the Guangdong-Hong Kong-Macao Greater Bay Area generally showed a small upward trend, but the characteristics of stratification and unevenness were significant, with the level of urban-rural integration development in the counties on the east bank of the Pearl River Estuary being significantly higher than that on the west bank of the Pearl River Estuary. In terms of influencing factors, fiscal expenditure decentralisation, fiscal expenditure on agriculture and advanced industrial structure had a facilitating effect on the development of urban-rural integration in the county, while fiscal urban-rural public service expenditure, financial efficiency and rationalisation of industrial structure showed an inhibiting effect. Based on the results of the study, countermeasures are proposed to strengthen the strategic coupling of new urbanization and rural revitalization, focus on overall promotion and local adaptation, improve the institutional mechanism of financial investment, and strengthen the synergy and mutual promotion of industrial development and urban-rural integration.

This paper explored the spatio-temporal differentiation characteristics and influencing factors of urban-rural integration level at the county level in the Chengdu-Chongqing Economic Circle from 2007 to 2020 by using improved entropy method, Jenks natural fracture method, and obstacle model.The results show that: (1) The level of urban-rural integration development in the Chengdu-Chongqing region continues to improve, with the urban-rural integration index increasing from 0.239 in 2007 to 0.534 in 2020, the number of low and lower level integration areas decreasing from 25 in 2007 to 8 in 2020, and the number of high and higher level integration areas increasing from 2 to 12. (2) The development of different integration dimensions is not synchronized, and the highest index of social integration development level is 0.612 in 2020. (3) The high-level integration zone forms two small-scale agglomeration areas in the western and southeastern parts of the Chengdu-Chongqing region, presenting a development pattern of “dual core dominance” but “central collapse”. (4) The obstacles degree to urban-rural integration development in the Chengdu-Chongqing Economic Circle are relatively higher in the early stage due to natural factors than population, land, and financial factors. In the later stage, the obstacles degree of natural factors decrease, while the obstacles degree of  industrial structure and financial factors are more significant.

An examination of the digital financial inclusion in 89 cities in the Yellow River Basin from 2011 to 2021 was conducted using Dagum Gini coefficient and spatial autocorrelation analysis, and the time fixed effects SDM model was employed to assess the influencing factors. The research shows that: (1)On the whole, digital inclusive finance in the Yellow River Basin is on a slow upward trend, with a distribution pattern of “high in the east and low in the west, high in the north and low in the south”, and the growth rate shows an evolutionary pattern of “fast in the southwest and slow in the north”. (2) The Gini coefficient has been gradually narrowing over the course of the study, with the intra-regional difference being downstream>middlestream>upstream, and the inter-regional difference being upstream-downstream>middle-downstream>upstream-middlestream. The main source of the overall difference is the contribution rate of hypervariable density. (3) Digital inclusive finance in the Yellow River Basin shows a fluctuating and rising spatial agglomeration trend, and is dominated by “high-high” and “low-low” types, while “high-low” and “low-high” types are relatively scattered. (4) Digital inclusive finance benefits from factors like economic development, traditional financial development, and population density, whereas education has a detrimental impact, with positive spillover effects from industrial structure and geographic location, and negative spillover effects from government support and internet development.

Based on the land use of the Beipan River Basin in Guizhou, combined with socio-economic development factors, the land use dynamic degree, land use transfer matrix, and geographic detector were used to analyse the spatial and temporal evolution patterns of its production-living-ecological spaces and their driving factors in the Beipan River Basin in the period of 2000—2020. Results show: (1) The production-living-ecological space of Beipan River Basin shows spatial divergent. Ecological, production and living spaces account for 74.0%, 25.1% and 0.9% of the study area, respectively; (2) The centre of gravity of industrial production land and urban living land have a larger migration distance, and both of them show a tendency to migrate to the south-east; (3) The distribution of the three living spaces has a significant relationship with the scale of towns, average annual precipitation, slope and elevation; (4) The production-living-ecological space is result of the joint action of natural factors and socio-economic factors, factors and the interaction effects are non-linear and two-factor enhancement. Improving the efficiency of land use, protecting the ecological environment and agricultural land, curbing the disorderly expansion of industrial land and urban residential areas, and exerting the guiding role of policies to guide the reasonable transfer of land will be conducive to the high-quality development of land space in the Beipan Basin.

Based on temporal NPP-VIIRS nighttime lighting, socio-economic statistical data, and other data sources, a GDP spatialization model is constructed, and the model is modified by combining land use data with a spatial resolution of 30 m ×30 m to study the spatial differences and evolution trends of the economy in Fuzhou City. The results indicate that: (1) The method of using land use data to modify the GDP spatialization model to improve the accuracy and validity of unit grids is feasible and meaningful for small-scale economic spatial analysis. (2) Using the output values of various industries corresponding to land use data to modify the GDP spatialization model can further improve the simulation accuracy of unit grids. (3) The synchronicity comparison shows a economic space of Fuzhou City presents a pattern of high GDP in the eastern region, with low value and scattered high value distribution in the western and northern regions.. From a historical perspective, since 2015, the expansion of high GDP areas and the growth rate of GDP in Fuzhou have significantly increased, and there has been a slight downward trend overall since 2018.

Based on the data of 2020 city physical examination questionnaire, a multi-layer linear model was used to measure the comprehensive level and differences of urban governance in 36 central cities, and to explore the key factors affecting urban governance. The research shows that：From the perspective of spatial characteristics, the cities with high governance evaluation are mostly distributed along the Yangtze River and the eastern coastal areas, while the cities with low governance evaluation are mostly distributed in the northwest and northeast areas. From the perspective of differences between cities, there is a “weak board effect” in urban governance, and there are significant differences between cities in ecological environment governance and road environment improvement; From the perspective of key influencing factors, residents’ comprehensive perception of urban governance is influenced by urban built environment, urban socio-economic conditions and individual attributes. Among the variables of urban built environment, high green coverage rate, low PM2.5 concentration and high accessibility of bus stops and shopping malls promote residents’ satisfaction with urban governance.Among the variables of urban socio-economic conditions, large economic scale and high wage level enhance residents’ satisfaction with urban governance. Among the individual attribute variables, old age, high education and “new citizens” are more sensitive to the effect of urban governance.

An evaluation index system of cultural soft power is constructed based on six dimensions of cultural attraction, display, communication, innovation, cultural investment and cultural and tourism integration. Taking 30 prefecture-level cities in the Central Plains Urban Agglomeration as examples, spatial classification, nuclear density analysis and spatial autocorrelation methods are used to analyze the spatial characteristics of cultural soft power in the Central Plains Urban Agglomeration and analyze its influencing factors. The results show that: (1) From the difference of comprehensive strength, the number of high and higher strength is small and mainly distributed in the core area, only 3 middle strength areas, and half of the cities are distributed in the low and lower strength areas. The western half of the wall shows a central and peripheral pattern led by Zhengzhou and Kaifeng, while the eastern half shows polarization characteristics led by Bozhou and Fuyang, and forms a low-value stretch from Liaocheng to Zhumadian between the eastern and western halves. (2) From the perspective of sub-dimensional spatial differences, the sub-system of cultural attraction and display power is similar to the comprehensive strength, while the sub-system of cultural investment power is “high in the northwest and low in the southeast”. In addition, the sub-systems of cultural transmission and innovation presented a completely different pattern from the previous three sub-systems, showing a distribution structure with low value surrounded by high value with Zhengzhou and Kaifeng as the core. (3) From the perspective of spatial agglomeration and correlation, the Central Plains region has formed a dual-core agglomeration situation of “one master and one pair” around Zhengzhou and Bozhou respectively, and a significant HH agglomeration group has formed near the main core area. Among them, the concentration pattern of the cultural attraction subsystem and comprehensive strength is basically the same, the concentration center of the cultural display power subsystem is weakened in Zhengzhou but strengthened in Bozhou, the cultural communication power and innovation power subsystem only form the cluster core in the central part of the country, and the cultural and tourism integration power subsystem forms two cluster cores in the southeast based on the comprehensive pattern. (4) From the perspective of influencing factors, urban GDP has the strongest influence on the soft power of urban culture, followed by the added value of the tertiary industry, and the influence of traffic facilities, the number of science, education, culture and health units and the urbanization rate is not obvious.

Workplace-originated shopping trip is an important content of residents’ consumption activities. Understanding its characteristics and causes can help improve the coordinated layout of urban employment centers and commercial centers, and enrich the theoretical understanding of urban living space. Taking Wuhan as an example, the study uses location\|based service data, sample survey data, GIS spatial analysis and structural equation modeling to measure the travel distance of workplace-originated shopping trips, and reveal its influencing factors. The study found that Wuhan residents’ workplace-originated shopping activities are dominated by short and medium-range trips, the heterogeneity of travel distances is obvious, and convenience is worse in the urban fringe areas. The commercial accessibility of employment centers, individuals’ socio-economic attributes, commuting costs, and online shopping habits are important factors. The study suggests that optimization should be carried out in more than 10 employment centers with prominent inconveniences, not only to promote comprehensive optimization based on multifactorial synergy, but also to differentiate the main causes of workplace-originated shopping difficulties, and to implement type-specific improvement measures.

Utilizing quantitative methods such as kernel density estimation, nearest neighbor index method, Kriging spatial interpolation analysis, and multi-scale geographically weighted regression, this paper explores the spatio-temporal evolution characteristics and influencing factors of childcare service resources in Xi’an City from 2016 to 2023. The results show that: (1) The childcare service in Xi’an can be divided into three stages: initial stage, rapid development stage, and explosive growth stage. The three-core is developmented into multi-core and mainly concentrated in the three districts of the city. (2) The distribution of childcare service resources in Xi ’an is concentrated, and the degree of agglomeration increases year by year. It has the characteristics of centralized agglomeration on the whole and outward development at the same time. The west and north directions are the main directions of expansion. (3) High-capital childcare service resources mainly cluster in business districts and colleges and universities, presenting four high-capital hot areas, which expect to provide more competitive childcare service resources. (4) Population factors, education factors, and industry factors significantly affect the distribution of childcare service resources, while traffic factors and economic factors have little impact on the spatial distribution of childcare service resources.

The function of urban rail transit stations reflects of the status of urban land use and spatial vitality. The coordinated development of rail transit stations and urban land use plays a positive role in alleviating traffic congestion pressure and improving land use efficiency. This study investigated the evolution of station functions and influencing factors in the central area of Xi’an from 2011 to 2020, using information entropy, dominance, equilibrium, and multiple regression model. The results indicated that the station functions during this period were characterized by a wave-like rise, intermediate stability with peripheral changes, and mixed-initiative. Commercial functions and the distance to the city center were the main factors driving the evolution of station functions. Among these factors, commercial functions had a positive impact on the mixing degree of station functions, while the distance to the city center had the opposite effect. Meanwhile, during the planning phase, the urban spatial pattern had a significant impact on station functions. During the construction phase, the regional economic level gained prominence as a determining factor. Subsequently, during the operational phase, the commercial service industry emerged as the primary force driving the evolution of station functions. Based on the investigation of the spatial and temporal variation of urban rail transit station function evolution and the influencing factors, it is helpful to optimize the land use of the area around the stations and enhance the vitality of urban rail transit stations.

Taking urban live-streaming e-commerce as a typical case to study the profound changes in function and organization of urban space caused by the vigorous development of such new economic activities in the era of mobile internet. Using Tianyan database to check the data of enterprises, analyze the spatial agglomerationn and diffusion trends of live-streaming e-commerce enterprises in the main urban area of Hangzhou City from 2016 to 2022 and found that live-streaming e-commerce, a new economic activity, presents a distinct phenomenon under the combined effect of virtual agglomeration and physical agglomeration the characteristics of the emerging production service industry: （1）The physical space of urban live-streaming has obvious agglomeration characteristics, showing a multi-center distribution pattern that is dislocated from traditional commercial centers; （2）The evolution of urban live-streaming space presents the characteristics of adjacent diffusion and near-field encryption. With the continuous upgrading of the industry, spatial agglomeration has gradually changed from being influenced by both goods and talents to being mainly influenced by talents, and the attributes of the mid-to-high-end production service industry have become increasingly prominent. The above spatial characteristics and trends not only reflect the existing mechanisms and laws of physical agglomeration, but also demonstrate the spatial empowerment and talent orientation of virtual agglomeration.

By constructing a theoretical framework with four dimensions of geography, culture, institution and economy, this paper analyzed the spatio-temporal characteristics of inbound tourists with different distances countries to the Yangtze River Economic Belt（YREB）  from 2010 to 2019 through location entropy, and their influencing factors are explored using the augmented gravity model. The results show that：（1）Inbound tourists in the YREB are mainly from South Korea, Japan and France, with a high concentration of tourists from countries with middle and long distances and a balanced tourist structure. （2）Tourists from countries with close distances prefer provinces of Hunan and Yunnan etc. in the southern part of the region as their destinations. In contrast, those from countries in the middle- and long-distance ranges are concentrated in the northern part of the region. Compared with tourists from countries with close and long distances, the agglomeration core of those with middle distances is more stable and concentrated. （3）Geographic and cultural distances negatively affect destination choice, institutional and economic distances positively affect it, and linguistic and climatic differences insignificantly affect it. The significance of the effects of multidimensional distances is weaker during 2015—2019 than during 2010—2014. Furthermore, the directions of the impact on tourists from countries with close and long distances are roughly opposite to those from countries with middle distances. 

Taking the Ili River Valley as an example，the spatial distribution characteristics of the accommodation industry in the region were analyzed using DBSCAN algorithm and geodetector. The results of the study show that: (1) The accommodation industry in the Ili River Valley presents a spatial distribution pattern of overall dispersion and local aggregation. Among them, Yining City and Nalati Tourism Scenic Area in Xinyuan County are the core areas with high aggregation. (2) The accommodation industry in the region is divided into 18 spatial clusters of 5 classes, which are spatially expressed in a south-east-north-west direction and most of the accommodation industry is radially distributed outward with tourist attractions as the center. (3) The degree of influence of different factors on the accommodation industry has a large degree of heterogeneity, in which scenic spots, star-rated hotels, transportation facilities and population are the core influencing elements.

Based on the classification of 116 camping travel and leisure destinations in Wuhan City, this paper used metrological mathematics and spatial analysis to analyze its temporal-spatial distribution characteristics and influencing factors, the following conclusions show that: (1) Since the rise of camping travel and leisure in Wuhan City in the 1980s, camping travel and leisure have experienced four distinct development stages of “initial brewing-rapid expansion-vigorous development-upgrading transformation”.(2) The spatial cold-hot spots formed by the polarization development of Wuhan-s camping travel and leisure areas are characterized by agglomeration and disequilibrium. Finally, a “northwest-southeast” trend is formed in the northwestern region, a “northeast-southwest” trend is formed in the central and western regions, and a “northeast-southeast” trend is formed in the central and eastern regions. (3) At present, the camping travel and leisure destinations in Wuhan City mainly fall into four types, namely leisure travel, entertainment activities, education training, and countryside adventure. There are differences in agglomeration scale and evolution trend. (4) Urbanization, policy, demand, nature and location jointly affect the temporal-spatial distribution characteristics of camping travel and leisure destinations in Wuhan City.There is some heterogeneity in the effect of different factors.

Based on both representational and non-representational perspectives, this paper takes Xi’an Yongxingfang as an example. It represents symbol perception in three aspects: material landscape attraction, intangible cultural atmosphere and localization of consumption space. The non-representational tourist practice is represented by interpersonal interaction, co-production and individual experience. The research model of tourists’ place identity in intangible heritage tourism streets is established. The results show that: (1) The physical landscape attraction, intangible cultural atmosphere and the localization of tourism consumption space have different impacts on tourist practice. Among them, material landscape attraction has a significant positive impact on the three aspects of tourist practice, intangible cultural atmosphere only has a significant positive impact on co-production, and the localization of consumption space has a significant positive impact on interpersonal interaction and personalized experience. (2) Interpersonal interaction, co-production and individualized experience have significant positive effects on tourists’ place identity. (3) Tourist practice plays a complete mediating role in the relationship between symbol perception and tourist place identity. The research results provide a theoretical basis for introducing intangible heritage projects into historic districts and enhancing tourists’ place identity.

Taking the Langde Miao Ethnic Village in Qiandongnan Prefecture of Guizhou Province as a case, historical institutionalism was applied to evaluate the “workpoint system” of tourism involvement through in-depth interviews and fieldwork. It expanded on the common prosperity logic and outlet of community-led rural tourist development by analyzing the history, rationale over the long term, and future direction of the “workpoint system” reform. The findings demonstrated that the “workpoint system” was shaped by the social logic and cultural foundation of Langde Miao Village, and that the historical key nodes determined the rationale for the system’s selection. Even while the “workpoint system” to safeguard residents’ rights to participate was hard to avoid being “lazy” and had drawn criticism, Langde Miao Ethnic Village had continued to use it, and the system’s institutional inertia had been bolstered by the rising return. Besides, the “workpoint system” was integrated into the system network structure as a component of the community system, creating a correlation dependency that leaded to the system lock. The combination of institutional inertia and institutional lock decided that the “workpoint system” survived. The “workpoint system” was effective in terms of human capital characteristics, although path deviation was exacerbated by changes in the external environment and group divergence within the community. Institutional reform is more likely to follow the co-prosperity route that upholds the village’s traditional values.

Focusing on the perspective of digital ecology, this paper uses network analysis and exponential random graph model to take into account the overall and individual effects and explores the impact mechanism of China’s smart city construction on carbon emission efficiency from the perspectives of relevance, dynamics and aggregation. The results show that: (1) From the perspective of the overall network and individual network, the construction of smart city significantly improves the index performance of the carbon emission efficiency network, promotes the cooperation between cities, and ensures the rational allocation and utilization of resources. Developed and resource-based cities occupy a dominant position in the network and have greater control capabilities. (2) From the perspective of network topology, the scale-free nature and small-world nature are not significant, while the number of core cities in the southeast coastal area and North China gradually increases, and with the gradual maturity of smart city construction, the local agglomeration is significantly strengthened. (3) From the perspective of influencing factors, reciprocity has a positive correlation with the network, the impact of smart talents on the network is the most significant, and the development of smart environment, smart economy and smart technology has an improvement effect on carbon emission efficiency, but there are periodic changes, and the impact on carbon emission efficiency is not regular.

Based on the morphological, structural,  and functional dimensions, as well as the economic and social welfare output per unit of carbon emission, the paper measured the compactness and carbon performance of 41 cities in the Yangtze River Delta, and studied the spatial and temporal correlation between the two respectively, as well as used spatial econometric methods to analyze the three sub-indicators of compactness, connectivity, proximity， and functional mix, on carbon performance. The results show that: (1) Regional urban compactness is increasing in the Yangtze River Delta from 2012 to 2020, but the distribution varies obviously,the overall spatial pattern of carbon performance is “high in the central-east and low in the north-west”. (2) Compactness and carbon performance both have certain spatial correlation characteristics, and the proportion of cities in the localized high-high agglomeration and low-low agglomeration areas of the two are highly coincident. The aggregation of highly compact cities will bring about the aggregation of cities with high carbon performance in the same area. (3) Connectivity, proximity, and functional mix significantly promote the carbon performance of this city and its neighboring cities, with connectivity having the greatest impact on the carbon performance of this city and proximity the lowest; and proximity having the greatest impact on carbon performance of its neighboring cities, and connectivity the lowest.

This study focuses on the southern Shaanxi region, incorporating POI-driven factors into the PLUS model and using LASSO regression for driver system selection and accuracy validation. Three scenarios, namely natural development, economic protection, and ecological protection, were set. After selecting the driving factors, the land-use pattern in southern Shaanxi in 2030 was simulated for each scenario.The InVEST model was then used to analyze the spatiotemporal differentiation of carbon storage from 2000 to 2020, exploring the impact of land-use changes on carbon storage in southern Shaanxi under different development scenarios. The results indicated:(1) From 2000 to 2020, construction land in southern Shaanxi increased from 23 648.49 hm2 to 78 000.21 hm2, encroaching on the living space of farmland, forest, and grassland, leading to respective reductions of 39 415.05 hm2, 8 787.51 hm2, and 17 476.56 hm2. In 2030, under all three development scenarios, construction land continues to expand. (2) Introducing POI-driven factors and using the LASSO algorithm in the PLUS model improved accuracy and operational efficiency, increasing the Kappa coefficient and OA coefficient by 2.53% and 0.20%, respectively. This enhancement enabled the model to simulate the distribution of construction land more accurately. (3) Carbon storage in southern Shaanxi decreased from 2.188 7×109 t in 2000 to 2.177 5×109 t in 2020. In 2030, under the three simulated scenarios, the total carbon storage in economic protection and natural development scenarios was lower than in 2020, with the ecological protection scenario having the highest total carbon storage at 2.183 0×109 t. (4) In 2030, the ecological protection scenario is more conducive to sustainable development in southern Shaanxi. The carbon density distribution map can serve as a reference for regional development and carbon balance, offering insights into the impact of land-use under different scenarios on regional carbon storage and spatial planning under a dual-carbon background.

Taking Liangping District, Chongqing City as the research object, the paper used morphological spatial pattern analysis and circuit theory to identify key areas for ecological protection and restoration, including ecological source areas, ecological pinch points, ecological obstacle points, and ecological rupture points. The results show that: (1) There are 19 ecological source areas in the study area, with a total area of 359.82 km2, showing a spatial distribution feature of “two belts and multiple points”; There are 42 ecological corridors with a total length of 241.27 km, constructing an ecological security pattern of “three areas, three screens, one network, and multiple nodes”; (2) Identifying 5 ecological pinch points, 12 ecological obstacle points, and 5 ecological fracture points are key areas for ecological protection and restoration, mainly distributed in the central and eastern regions; (3) Based on the ecological characteristics of key areas, propose corresponding main directions and suggested measures for ecological protection and restoration. The research can provide a path and method reference for the ecological protection and restoration of land space in Liangping District and other regions.

Based on the classical statistics, spatial analysis of Geographic Information System (GIS), gravity center model, spatial autocorrelation and other model methods, this paper mainly focused on the spatial-temporal evolution of the cultivated land grain production in 122 evaluation units in Henan Province from 2001 to 2020, and delimited the functional zoning of grain production.The main results indicated that the grain production (total output and average yield per unit area) increased significantly in Henan Province from 2001 to 2020.The average value of total grain output and average yield per unit area in 2020 increased by 61.50% and 31.71% respectively compared with 2001, but the growth rate slowed down and the space for grain output improvement tightened.The high-yield areas of grain production had been expending from 2001 to 2020.The Eastern Henan Plain, the Northern Henan Plain and Nanyang Basin were the three core areas of grain production in space. The spatial distribution of total yield and average yield per unit area was mismatched. The construction of cultivated land quality was the key to the improvement of grain production capacity in the Eastern Henan Plain and Nanyang Basin in the future. From 2001 to 2020, the gravity center of grain production was in Yanling County, which moved 14 073 metres along the direction of 17.3° south by east, the center of gravity of grain production moved to the southeast from 2001 to 2010, and moved to the northwest slowly after 2010, and the moving distance of gravity center decreased step by step, the grain production trended to be balanced in Henan Province.The total grain production has a strong positive autocorrelation in space, there are two types of high-high and low-low autocorrelation. In combination with the distribution of grain output, the primary core areas, secondary core areas,  potential improvement areas and general production areas of grain production are defined.

Based on the data of the number of TikTok rural internet celebrities with more than 200 000 followers in Henan Province, the number of fans, and live streaming in Henan Province were used to construct an evaluation system, and the development level and spatial differences of TikTok rural internet celebrities in Henan Province were analyzed by using analytic hierarchy process, position-scale method, spatial autocorrelation and other methods, and their influencing factors were explained. The results show that: (1) There are obvious regional differences in the development level of TikTok rural internet celebrities in Henan Province, with the high-level area forming a strip-like agglomeration area in Luoyang-Shangqiu, and the medium-and low-level areas spreading around the high-level area, mainly distributed in Nanyang City, Zhumadian City, and Anyang City; Most of the top 10% of internet celebrities in terms of development level are concentrated in Zhengzhou, Kaifeng, Luoyang and Shangqiu, and these internet celebrities are in a leading position in terms of their ability to carry goods, video support and fan stickiness. (2) From the perspective of order-scale characteristics, the fitting curve belongs to the type close to the first type, and the phenomenon of “warped tail” is obvious. The number of “head cities” is small but the influence is strong, and the number of “central cities” is relatively large but the influence is not as good as that of “head cities”. (3) From the perspective of spatial distribution,The areas with high-level of rural internet celebrities are distributed in Kaifeng, Shangqiu, Zhoukou, and Pingdingshan; The number of rural internet celebrities in Jiyuan and Luohe is relatively backward in the province. In addition, in terms of spatial correlation pattern, the number of rural internet celebrities showed obvious agglomeration characteristics, and Shangqiu City formed a significant HH area. (4) From the perspective of influencing factors, government support, scientific and technological literacy, internet environment support and e-commerce development level play an important role in improving the development of rural internet celebrities.

Based on 407 samples of micro-farmers’ field research data in Yueyang City, an ordered discrete Probit model is applied to empirically test the degree of influence of livelihood capital on farmers’ satisfaction with homestead remediation and the differential effect pattern of different asset structures. The results show that :(1) Farmers’ physical capital, human capital, financial capital, social capital and natural capital all have a significant effect on farmers’ satisfaction with homestead remediation, and their stronger effects are mainly the number of family cadres, main sources of income, neighborhood relations, number of family members, total family size and distance of cultivated land， etc. (2) Farmers with different asset types show different satisfaction results on the behavior of homestead remediation, and farmers with reasonable asset types have higher satisfaction. (3) Among the factors influencing the satisfaction of farmers with different capital types, the capital rational type of farmers preferred the improvement of social capital and human capital brought about by homestead remediation, while the capital-deficient type of farmers preferred the improvement of financial capital, natural capital and physical capital.