The intensive utilization of land within development zones is crucial for the region’s high-quality development in the new era, with its dynamics emerging as a prominent research area. This study, focusing on the development zones of Ningxia, China, investigates the spatio-temporal distribution of land use intensification from 2018 to 2021. It identifies key influencing factors such as economic quality, innovation drive, open environment, green transformation, and structural optimization, employing the geographically and temporally weighted regression (GTWR) model to delineate the underlying drivers of intensive land use. The findings reveal that: (1) Land use intensification in Ningxia’s development zones exhibits a distribution pattern where the northern Yellow River irrigation area surpasses the central arid area, which in turn surpasses the southern mountainous area, with the disparity between these areas decreasing over the study period. (2) The GTWR model proficiently captures spatial and temporal variations in the driving mechanism, highlighting green transformation and structural optimization as primary influencers, followed by innovation drive and economic quality. (3) The impact of each factor on land use intensification exhibits significant spatial and temporal heterogeneity; for instance, the growth rate of fixed asset investment exerts a more pronounced influence in the northern Yellow River irrigation area, while the growth rate of industrial enterprises’ total income is more influential in the central and southern regions. Moreover, the effect of land consumption per unit of industrial income on intensification levels slightly diminishes, with the influence of other factors gradually intensifying. This study elucidates the dynamic mechanisms of intensive land use across different development zones, aiming to inform land use policy and support the development of high-quality zones in the western Yellow River Basin.

China is in a phase of high-quality development, where addressing the challenges posed by extensive land use due to rapid urban expansion is crucial for the sustainable growth of cities. While existing research predominantly focuses on the economical and intensive use of urban construction land or the status of high-quality development, the interplay and coordination between these aspects are seldom discussed. This study targets the Ningxia of China, establishing multidimensional index systems to assess the level of economical and intensive use of urban construction land and the status of high-quality development across 22 districts and counties in 2018. Through the analysis of coupling coordination degree, relative development degree, and influence coordination force, the study explores the coupling coordination relationship between these elements. The findings reveal the following: (1) The economical and intensive use level of urban construction land exhibits a pattern of being “low in the central region and high in the northern and southern areas”, whereas the high-quality development level is characterized by a “high in the northwest and low in the southeast” spatial pattern in Ningxia in 2018. (2) The coupling coordination degree of the two systems shows a “low in the central region and high in the northern and southern areas” spatial distribution, with most districts and counties in Ningxia achieving a basic state of coordination, indicating a virtuous cycle in the relationship between the two systems. (3) The innovation and security subsystems tend to negatively impact the coupling coordination of the systems, while the green and coordination subsystems generally contribute positively. These results provide an empirical foundation for promoting the economical and intensive use of construction land within the context of high-quality development in the Yellow River Basin.

The Hexi Corridor, as China’s most densely populated arid region, necessitates a thorough understanding of the evolution of its spatial patterns and the underlying driving mechanisms to reconcile regional development with environmental protection within a three-zone framework. This research employs a suite of quantitative methods, including the spatial transition matrix, landscape pattern index, and optimal parameter geographical detector, to examine the spatiotemporal characteristics and determinants of territorial spatial pattern changes in the Hexi Corridor from 2000 to 2020, focusing on “quantitative change” and “form change”. The findings reveal as follows: (1) The Hexi Corridor’s urban, agricultural, and various ecological spaces have expanded, accompanied by a notable decline of 2758.87 km² in green ecological areas. Despite heightened developmental activities across the three-zone space, ecological conservation efforts have yet to yield significant results. (2) The predominant form of territorial space transition is the internal “desert-green land” dynamics within ecological zones, marked by considerable variability in the extent of cross-transformation across different functionally oriented zones. This cross-transformation of territorial spaces is characterized by increasing fragmentation, dispersion, and complexity in landscape patterns. (3) The territorial spatial pattern evolution in the Hexi Corridor is influenced by multifaceted factors. “Quantitative change” is primarily driven by national policy directives, natural geographic conditions, transportation-related constraints, and socio-economic drivers, whereas “form change” is shaped by natural geography and further modified by transportation and socio-economic factors.

The study of the coupled coordination relationship between park green spaces and urban functional spaces, along with its influencing factors, is crucial for optimizing the layout of park green spaces and enhancing the synergistic development of urban functional spaces. This research focuses on the central urban area of Urumqi City, Xinjiang, China, employing kernel density analysis, standard deviation ellipse, coupling coordination degree model, and Geodetector. It aims to analyze the distribution patterns of park green spaces and urban functional spaces and investigate their coupling and coordination relationship and influencing factors. The findings reveal that: (1) Parks and urban functional spaces exhibit a spatial aggregation characteristic that is dense at the center and sparse at the edges, diminishing in concentric circles and expanding toward the northwest. (2) The distribution centers of parks and urban functional spaces have shifted away from the city center, with parks, residential, transportation, and public service spaces aligning in the northwest-southeast direction, while leisure and commercial spaces align in the northeast-southwest direction. (3) The predominant coupling and coordination type between park green spaces and various urban functional spaces is moderate dissonance, with the degree of coupling and coordination displaying spatial differentiation characterized by higher levels in the center and lower levels in the eastern, western side, and extremities of the north-south axis. Demographic factors and transportation conditions are identified as primary influences on the degree of coupling and coordination between parks and urban functional spaces, with socio-economic factors playing a secondary role.

As an important photovoltaic (PV) power generation base, the Inner Mongolia Autonomous Region (IMAR), China has seen the problem of blindly constructing PV power stations become more prominent in recent years. It is of great significance to grasp the suitability of regional PV development, power generation potential, and emission reduction benefits for the healthy development of the PV industry. To explore the suitability of PV development in the IMAR and the benefits of emission reduction, this study makes comprehensive use of meteorological, natural geographic, economic, and social data, constructs a comprehensive evaluation index system of PV development suitability in the form of meteorology-terrain-location-vegetation, uses an analytic hierarchy process to determine the weights of the evaluation indexes, and performs a spatially explicit evaluation of the suitability of PV development in the IMAR with the aid of a geographic information system tool to quantitatively assess the potential of PV power generation and emission reduction benefits under different development intensities. The PV power generation potential of the leagues and cities and the demand for electric power are compared. The results are as follows: (1) The suitability of PV development in the western part of the IMAR is greater than that in the central and eastern parts, and the various suitable areas are mainly located in the western Alagxa League and Bayannur City, with particularly suitable areas for PV development accounting for 23.66% of the total area of the IMAR. (2) The IMAR PV power generation potential is enormous, especially for regional development, where 12.57% of it can meet the IMAR 2021 electricity consumption. (3) The distribution of PV power generation potential and electricity demand in the IMAR has strong spatial heterogeneity, and the spatial pattern is characterized by significant features. (4) The energy saving and emission reduction effect of PV power generation in the IMAR is remarkable. Compared with conventional coal-fired thermal power generation, the annual carbon emission reduction is approximately 2.947×10⁹ t if the development of a special suitable area is performed, which is 4.46 times the total carbon emission of the IMAR in 2021 and accounts for 21.20% of China’s total carbon emission in 2021. These results provide scientific references and guiding suggestions for the placement of PV power stations and the healthy development of the PV industry in the IMAR.

Promoting high-quality development in the Yellow River Basin is a necessary path for China’s economic construction to comprehensively move into the high-quality development stage. Objectively evaluating the quality of basin development is the basis for effectively improving the quality of development. Therefore, based on the five development concepts and the connotation of high-quality development, this study constructs an evaluation index system of high-quality development in the Yellow River Basin, measures the high-quality development level of 60 prefecture-level cities in the Yellow River Basin and the 5 economic growth poles from 2010 to 2021 using the TOPSIS evaluation method, explores the regional unbalanced development and the sources of differences using the Dagum Gini coefficient and the variance decomposition method, and applies the Kernel density estimation method to analyze the evolutionary trend of regional high-quality development. The results are as follows: (1) During the sample period, the high-quality development of cities along the Yellow River shows an “N”-shaped change and an upward trend, with the provincial capitals and coastal and resource-based cities leading the development level in general. (2) The overall difference in the basin is narrowing; however, the gap and the trend of change are different within and between regions. (3) Intergroup disparity is the main spatial source of high-quality development differences, and differences in the supporting environment are the main structural source of differences in the basin and the five economic growth poles. (4) The evolutionary trends of the river basin and the five economic growth poles are different, and most of the regions continue to improve their high-quality development levels. Based on these results, suggestions are made to develop a good top-level design program, strengthen cooperation between regions, create special economic growth poles, avoid homogeneous competition, strengthen the radiation-driven role of central cities, and enhance the soft power of economic development.

This study focuses on 82 cities in five major urban agglomerations in the Yellow River Basin and uses PM_2.5 data published by the China National Environmental Monitoring Centre from 2016 to 2020. Spatial autocorrelation, geographic detectors, and geographically weighted regression methods were employed to investigate the spatiotemporal distribution characteristics and main driving factors of spatial heterogeneity of PM_2.5. This provides a reference for relevant departments to improve atmospheric pollution prevention and control policies. The results are as follows: (1) The change in the annual mean of PM_2.5 roughly follows an inverted “N” shape, and the seasonal mean changes in a “U” shape with a periodicity of first decreasing and then increasing. (2) In terms of spatial distribution, a gradient-decreasing pattern is formed from downstream to midstream to upstream of the Yellow River, exhibiting a gradually decreasing trend. (3) PM_2.5 exhibits positive spatial autocorrelation and overall aggregation distribution over the five years, with high-high, low-low, and low-high agglomeration types. (4) Natural geographical factors have a stronger driving force on PM_2.5 spatial differentiation than socio-economic factors in 2016 and 2020. The interaction results show two types: bi-factor and nonlinear strengthening. (5) The geographically weighted regression model is used to fit the five factors with the largest explanatory power for differentiation. The negative effects of each factor on PM_2.5 pollution in the five urban agglomerations have increased, whereas the positive effects have decreased over the past 5 years. Significant differences in spatial direction and strength were observed.

Innovation occupies a central position in the overall situation of national modernization, and cities are the main areas where innovation activities are performed. Thus, scientific measurement of urban innovation capacity is critical for improving the competitiveness of cities and formulating innovation strategies. Taking 48 cities in the Yellow River Basin as research objects, we constructed a city innovation evaluation index system based on four dimensions: talent cultivation capacity, scientific and technological research and development capacity, economic support capacity, and environmental service capacity. We measured the innovation capacity of these cities using the entropy weight method, Jenks natural breaks classification method, Gini coefficient, Moran’s I index, and other data analysis methods. The spatial differentiation of the innovation level of these cities and the main obstacle factors were analyzed. The results are as follows: (1) The overall innovation capacity of the Yellow River Basin is not high, the score gap between a few high-value cities and the rest of the cities is significant, and the innovation capacity shows the trend of stepwise increment in the upper, middle, and lower reaches. (2) Taking Shuozhou-Longnan as a line, the urban innovation capacity shows a distribution of high in the southeast and low in the northwest, and the spatial distribution of each dimension tends to be consistent with the total innovation capacity. (3) The distribution of urban innovation capacity in the Yellow River Basin is in an unbalanced state, and the spatial agglomeration characteristics show positive spatial correlations, mainly belonging to the spatial pattern of low-value agglomeration. (4) The scientific and technological research and development capacity and talent cultivation capacity have a greater degree of influence on the improvement of the innovation capacity of the cities, where the number of effective inventions is a common obstacle indicator for all cities.

Night-time cultural tourism consumption agglomeration areas serve as notable models for advancing the high-quality development of cultural and tourism integration, playing a crucial role in steering the growth of the cultural and tourism industry and unleashing the latent potential of night-time consumption. This study employs GIS spatial analysis methods, alongside geographical detectors and other approaches, to investigate the spatial pattern and influencing mechanisms of night-time cultural tourism consumption agglomeration areas in China. The findings indicate the following: (1) The distribution trend of night-time cultural tourism consumption agglomeration areas exhibits clustering, characterized by a “dense in the east and sparse in the west, more in the south and less in the north” trend. The layout features are conspicuous, emphasizing proximity to the city, water, and scenic locales. The spatial structure is marked by “one main, two pairs, and multiple micronuclei”. (2) The spatial distribution of night-time cultural tourism consumption agglomeration areas demonstrates a significant positive correlation, portraying a circularly decreasing spatial differentiation pattern of “hot in the east and cold in the west”. (3) Regarding type structure, historical sites and relics are concentrated in areas with rich cultural histories, local customs and traditions thrive in ethnic minority regions, industrial-themed categories exhibit broad spatial distribution, scenic spots are relatively evenly spread, and comprehensive categories encompassing cultural, tourism, and commerce predominantly manifest in economically developed areas. (4) Fundamental factors such as topography, rivers, and climate significantly influence the distribution of night-time cultural tourism consumption agglomeration areas. Meanwhile, factors such as population quality, passenger transport capacity, industrial development, and policy support emerge as pivotal determinants affecting the distribution of night-time cultural tourism consumption agglomeration areas.

Achieving high-quality development in ethnic minority areas of China is essential for promoting co-ordinated regional development and building a modern socialist country. Considering eight ethnic provinces and autonomous regions as research areas, this study constructs an evaluation index system for the high-quality development of ethnic minority areas. We apply the entropy weight TOPSIS method, geographical detector, and other methods to study the spatial evolution pattern and influence mechanism of high-quality development in ethnic areas from 2000 to 2020. The results show that: (1) High-quality development in ethnic minority areas has generally maintained an upward trend from 2000 to 2020. From the perspective of spatial differentiation, inter-regional distribution is “high in northwest China, low in south China, southwest China, and Qinghai-Tibet”, interprovincial distribution is “high in north China and low in south China”, and intraprovincial distribution is “polarization and equilibrium coexist”. (2) The high-quality growth rate showed a spatial trend from “high in the northwest and southwest China, low in Qinghai-Tibet and south China” to “high in southwest China and Qinghai-Tibet, low in south and northwest China”. (3) The spatial evolution of high-quality development in minority areas will change from “low level-low growth, low level-medium growth, and medium level-low growth” to “low level-medium growth, low level-high growth, and medium level-medium growth”. (4) The high-quality development level of ethnic minority areas is most affected by investment intensity, followed by income level and government regulation.

Wetland parks are crucial to China's natural protection system. Strengthening the construction and management of national wetland parks holds immense importance for effectively protecting wetland resources and harnessing the full ecological potential of wetlands. Focusing on the national wetland parks in the Yellow River Basin of China, this study employs kernel density estimation, hot spot analysis, standard deviation ellipse, and a geographical detective model to investigate the spatiotemporal differentiation, center of gravity evolution, and driving factors of wetland parks in 2010, 2015, and 2022. The results include the following: (1) In 2010, wetland parks in the Yellow River Basin presented a “double core and multiple points” density feature, evolving into a “multi-core and continuous patch” distribution trend in 2015 and 2022. The number and area of parks greatly increased, underscoring their growing role in regional economic development and ecological protection. (2) From 2010 to 2022, the spatial center of gravity of national wetland parks moved 247.31 km to the northeast, revealing a distinct “northeast-southwest” directional feature in its distribution pattern. Interbasin differences highlighted the largest movement of spatial center of gravity in wetland parks in the middle reaches of the Yellow River and the smallest movement in downstream provinces. (3) Natural environmental factors have a limited impact on the number and distribution of wetland parks, whereas social and economic factors decisively influence wetland protection, restoration, and park construction. Notably, the per capita regional gross domestic product and the digital elevation model have the greatest effect on the dimensions of social and natural driving, respectively.

The co-ordinated development of the tourism economy in the Yellow River Basin of China is essential for promoting the region's high-quality development. Considering the level of tourism specialization as the research object, this paper constructs a driving factor index system from five dimensions: regional economy, innovation capability, production factors, tourism services, and tourism policies. Based on the panel data of 61 cities in the Yellow River Basin from 2008 to 2020, we apply kernel density estimation, Moran index, and a geographically and temporally weighted regression model to study the spatio-temporal evolution of tourism economic differences and driving factors in the Yellow River Basin. The results show that: (1) Regional differences in the tourism economy in the Yellow River Basin continue to expand, and right-trailing phenomena have occurred in some years. (2) The Global Moran's I index of tourism specialization level is positive, and there is a spatial agglomeration trend. In the types of local spatial agglomeration, the scopes of “high-high” “low-low” and “high-low” agglomeration areas expand, whereas the scopes of “low-high” agglomeration areas narrow. From a spatial perspective, the differences in the Yellow River Basin tourism economy also expand. (3) The promotion effects of the nine driving factors on the tourism economy present three temporal characteristics: stable, decreasing, and increasing. (4) The key driving factors of economic development through tourism in upstream cities of the Yellow River Basin are regional economy, innovation capability, and tourism services. The factors that drive midstream cities are regional economy, tourism services, and policies, and the major driving factors in downstream cities are innovation capability, production factors, and tourism policies.

Studying and assessing the efficiency of urban green development and delineating its optimization path constitute a key aspect in promoting high-quality development within the Yellow River Basin of China. This endeavor also aligns with the important strategy of realizing the strategic goal of “carbon peak and carbon neutrality”. The EBM-GML model was used to calculate the urban green development efficiency of 58 cities in the Yellow River Basin from 2005 to 2020. The evolution characteristics of the study area were outlined through HP filter analysis and spatiotemporal interaction methods, quantitatively identifying multiple lifting paths. The results show the following facts: (1) During the study period, urban green development efficiency in the Yellow River Basin increased from 0.509 in 2005 to 0.651 in 2020, traversing three successive stages of “fluctuation-improvement-symbiosis”. Notably, the characteristics of intraregional imbalance were remarkable. (2) The local spatial structure of green development efficiency in the Yellow River Basin is robust, with a highly variable spatial movement direction. Additionally, the degree of spatial collaboration in green development efficiency among cities is greater than that of spatial competition. (3) The fsQCA result shows four optimization paths: economic-driven, dual-driven, resource integration, and comprehensive improvement. Economic development and scientific and technological innovation are indispensable prerequisites for achieving these goals.

Integrating the dynamic balance between economic resilience and eco-efficiency is important for achieving sustainable regional development. This study focuses on 30 provincial units in China from 2001 to 2020 as the research objects. Economic resilience, measured within the framework of the domestic provincial, regional adaptive cycle theory, and the driving-pressure-state-response (DPSR) model, was assessed using the combined weight model. Eco-efficiency, evaluated under the input-output theory, employed the global undesired superefficient slack based measurement (SBM) model. The synergistic evolutionary characteristics of economic resilience and eco-efficiency were elucidated using an improved Harken model. The results indicate the following factors: (1) Economic resilience substantially increased during the sample observation period, accompanied by notable regional differences and unbalanced development in the north and south regions, exemplifying a certain “East-Central-Northeast-West” ladder effect. (2) The overall trend of eco-efficiency levels decreased, with regional differences undergoing the phases of “expansion-shrinking-re-expansion”. This was marked by a considerable step imbalance and a decreasing spatial distribution from “coastal-inland”. (3) The synergistic evolution between economic resilience and eco-efficiency progressed through three stages of stabilization, decline, and stability. Importantly, no step imbalance was observed between these regions. Economic resilience, serving as a sequential parameter of synergistic evolution, emerges as the dominant factor influencing the sustainable development of the region.

Community living circles are closely related to residents’ lives, and are the basic units for the construction of urban grassroots public service facilities and an important grip for urban renewal. The scientific delineation of the scope of community living circles and the comprehensive measurement of their construction level provides theoretical exploration for promoting the construction of community living circles, achieving efficient allocation of public resources, and providing new perspectives and cases for the study of the relationship between the geographic environment and residents’ behavior. Based on the research idea of scientific delineation of the scope of the living circle and evaluation of its level of construction, this study explored the optimization method of community living area delineation by combining the data of walking planning and Mapbox living circles, constructed a comprehensive index system for measuring the construction level of living circles in terms of the layout of facilities, spatial accessibility, and residents’ satisfaction, among others, and performed empirical research by taking the Urumqi City, Xinjiang, China as an example. The results showed the following: (1) Merging the walking route planning circle and Mapbox living circle to divide the scope of the living circle could improve the timeliness and boundary accuracy of the division results. (2) The density of facilities and access per capita had a more significant impact on the level of construction of the living circle. (3) The average radius of the 15-min living circle of Urumqi City was 812.75 m, and the average area was 2.10 km². The construction level of old urban areas was higher than that of new urban areas, and the construction level of commercial services was higher than that of health management, education, travel, and other facilities. The lack of facilities and layout imbalance were the main reasons for the difference.

Driven by multiple factors such as population growth, resource development, and urbanization, resilience provides a new research perspective for the sustainable development of regional social-ecological systems. To clarify the trend of the coordinated development of the social-ecological system in Shaanxi Province, northwest China from the perspective of resilience and provide theoretical support for the sustainable development of the regional social-ecological system based on the three subsystems of society, economy, and ecology, comprehensively considering the vulnerability and coping capacity of the system, a resilience evaluation index system was constructed. The social-ecological system resilience of 107 county-level administrative units in Shaanxi Province was measured using set-pair analysis. According to the results of the resilience measurement, the coupling coordination degree model was used to analyze the coordinated development degree of binary (social-economic, social-ecological, and economic-ecological) and ternary (social-economic-ecological) subsystems. The spatiotemporal evolution characteristics of the coordinated development degree of the subsystems from 2000 to 2020 were revealed at the regional level. The bivariate spatial autocorrelation model was introduced to further explore the quantitative and spatial correlation characteristics of the coordinated development degree changes in the binary and ternary subsystems. The results showed the following: (1) During the study period, the social and economic resilience of Shaanxi Province increased significantly, ecological resilience showed a weak downward trend, and social-ecological system resilience increased from 0.303 to 0.779. (2) The coordinated development degree of the subsystems showed an upward trend; the coordinated development degree of the social-economic subsystem increased from 0.422 to 0.823, and the difference between the high in the south and low in the north weakened. The coordinated development degree of social-ecological and economical-ecological subsystems increased from 0.471 and 0.394 to 0.714 and 0.727, respectively. These two types of binary subsystems formed a coordinated development pattern of low in the middle and high in the north and south, respectively. The coordinated development degree of social-economic-ecological subsystem increased from 0.424 to 0.755 and generally maintained the spatial distribution characteristics of high in the south and low in the north. (3) The changes in the coordinated development of the social-economic, social-ecological, and economic-ecological subsystems were positively correlated with the change in the coordinated development of the social-economic-ecological subsystem in quantity and space. There were obvious spatial agglomeration characteristics in the coordinated development degree changes of the three types of binary and ternary subsystems. The positive correlation of high-high and low-low type evaluation units was mainly distributed in the northern and middle parts of Shaanxi Province, whereas the correlation was not significant in the southern part; the evaluation units with agglomeration characteristics were scattered.

This study is based on the data from 125 national desert (rocky desert) parks published by the National Forestry and Grassland Administration. The spatial differentiation characteristics and factors influencing the national desert (rocky desert) parks were detected using spatial analysis, geographic detector, and a geographically weighted regression. The results revealed the following: (1) The distribution of the national desert (rocky desert) parks is “more in the north and less in the south” and the construction sequence is “first in the north and then in the south”. (2) The nearest neighbor index of the national desert (rocky desert) parks is 0.537, showing significant agglomeration distribution characteristics, but the agglomeration degree and scale are significantly different. (3) The national desert (rocky desert) parks show a pattern of “sparse in the south and dense in the north and dual-core belt” in space, with substantial spatial differentiation characteristics. (4) Physical geographic factors have stronger explanatory power than human factors for spatial differentiation of the national desert (rocky desert) parks，and the interaction effect between the physical geographical factors and the human factors is significantly stronger than the interaction of their internal factors. (5) The effects of the six factors with the strongest explanatory power on the spatial differentiation of national desert (rocky desert) parks showed a trend of increasing positive effect and decreasing negative effect from southeast to northwest, and the northwestern region was the strongest influenced by natural geography and human factors.

The development of inclusive tourism plays a crucial role in promoting social justice, protecting the rights and interests of vulnerable groups, and ensuring equitable benefits from tourism, particularly in developing countries. However, existing studies lack quantitative assessments of inclusive tourism development at the country and regional levels. In this study, a comprehensive evaluation system of inclusive tourism development was constructed, consisting of nine indicators across three dimensions: tourism participants, economic inclusiveness, and resources and environment. Based on panel data from 2010 to 2019 and applying the entropy method, the inclusive tourism development level of 287 cities in China was assessed in this study. Spatial analysis methods were employed to reveal the spatial distribution characteristics and evolution trends of inclusive tourism. Furthermore, the gray correlation degree method was used to identify the factors influencing inclusive tourism development in China. The results are as follows: (1) Significant spatial differences exist in inclusive tourism development in China, transitioning from zonal to clustered distributions, and finally forming a point-like distribution. The disparity in inclusive tourism development has widened, spatial polarization has intensified, and unbalanced development has become prominent. (2) Inclusion tourism development in China can be divided into four types: underdeveloped, low-development, medium-development, and highly developed areas. The highly developed areas of inclusive tourism are mainly concentrated in the eastern region. (3) The level of inclusive tourism development in China shows a “W-shaped” trend of fluctuation and rise, with increasing spatial differences. It can be divided into two stages: slow growth from 2010 to 2014 and rapid growth from 2015 to 2019. (4) The urban registered unemployment rate, the number of star-rated hotels, and the per capita green park area are the major factors affecting the spatial pattern of inclusive tourism development in China, while air quality and the proportion of tertiary industry in the GDP are secondary factors. This study provides a scientific basis for optimizing the spatial distribution of inclusive tourism development in China. It contributes to enriching the global knowledge system of inclusive tourism development and aids scholars and practitioners in gaining a deeper understanding of inclusive tourism development in China.

Promoting the modernization of agriculture and rural areas is a major task in the overall development of a powerful socialist modernization country. This study constructs a comprehensive evaluation index system to measure the level of agricultural and rural modernization development in 30 provinces (cities, autonomous regions) of China from 2010 to 2020 and analyzes their spatiotemporal characteristics. The coupling coordination degree model is introduced to analyze the coordination between agricultural and rural modernization and to explore its spatial correlation. Identify the shortcomings of agricultural and rural modernization development by judging the lagging types. The results are as follows: (1) From 2010 to 2020, the level of agricultural and rural modernization, rural modernization, and agricultural modernization development in China exhibited a fluctuating upward trend. Higher levels of agricultural and rural modernization are concentrated in small areas along the coast, whereas the rest of the areas are at lower levels. Furthermore, there is a significant spatial difference between the development level of agricultural and rural modernization. (2) The coupling and coordination between agricultural and rural modernization are constantly improving; however, the trend of opposition between high and low-value agglomeration areas is increasing. (3) Shanghai, Tianjin, and Beijing have a relatively low level of agricultural modernization development; Shandong, Zhejiang, and Fujian have a relatively low level of rural modernization development, whereas Jiangsu and Guangdong have a balanced level of both. Other regions belong to the category of barely coordinated or below, with backward levels of rural modernization development or low and imbalanced levels of agricultural and rural modernization development.

Common prosperity is a fundamental requirement of socialism with Chinese characteristics, and reducing the urban-rural income gap is a practical challenge in achieving common prosperity and urban-rural integration. This study analyzes the spatial-temporal evolution of China’s urban-rural income gap using kernel density estimation, exploratory spatial data analysis, and other research methods based on urban-rural income ratio data from 366 urban research units between 2012 and 2021. Furthermore, a geographical-weighted regression model is used to explore the spatial differentiation of various factors influencing the urban-rural income gap across different regions in China. The results show that: (1) From 2012 to 2021, the urban-rural income gap in China gradually reduced, and the relative difference in the urban-rural income gap among cities also reduced. (2) Low-value areas of the urban-rural income gap are mainly distributed in the southeast coastal areas, along with a few cities in Heilongjiang Province and Xinjiang Uygur Autonomous Region. In contrast, high-value areas are mainly distributed in the Yunnan-Guizhou mountain area, the Tibet Autonomous Region, and some cities in the middle and upper reaches of the Yellow River. Overall, the urban-rural income gap in China exhibits a spatial distribution pattern, which is high in the west and low in the east, high in the north and low in the south, and high in the middle and low at both ends. (3) At the city-level scale, the urban-rural income gap in China exhibits a significant spatial positive correlation, and the cities with large and small urban-rural income gaps tend to cluster. (4) Regional heterogeneity exists in the influencing factors, emphasizing the need for tailored policies to address the urban-rural income gap and promote coordinated urban-rural development based on local conditions in all regions.

This study uses green patent data to characterize green innovation by taking 89 prefecture-level and above cities in the Yellow River Basin of China from 2005 to 2020 as the research object. It employs a standard deviation ellipse and spatial autocorrelation to unveil green innovation’s spatial and temporal evolution pattern. In addition, it uses a spatial Durbin model to analyze the factors influencing green innovation and decompose the spatial effects of various factors. The results indicate that: (1) green innovation in the Yellow River Basin and its upstream, midstream, and downstream areas demonstrate a rapid development trend. (2) The standard deviation ellipse of green innovation reveals a “northeast-southwest” distribution pattern with stable parameters. The center of gravity exhibits a moving pattern of “first east and then west”. (3) Global spatial autocorrelation of green innovation is evident, with local spatial autocorrelation primarily characterized by high-high and low-low patterns. (4) Science and technology investment substantially positively impacts green innovation. The full-time equivalent of urban research and experimental development personnel and the proportion of the tertiary industry exhibit a substantial negative spatial spillover effect. Conversely, the number of books in public libraries and the green coverage of built-up areas demonstrate a substantial positive spatial spillover effect. (5) Science and technology investment has the strongest positive effect of promoting green innovation in the upper reaches. The upgrading of industrial structure substantially promotes the development of green innovation in the middle reaches. Simultaneously, social culture plays a strong positive role in advancing green innovation in the lower reaches.

The coupling coordinative relationships between rural tourism and the rural human settlement environment in 11 prefecture-level cities of Shanxi Province, China, were quantitatively analyzed using an analytic hierarchy process and a coupled coordination model, based on the development of an evaluation indices system for rural tourism and the rural human settlement environment. Obstacle factors of the coupling coordinative relationships were diagnosed using an obstacle-degree model. The results showed that: (1) There were relatively high regional disparities in the levels of rural tourism and the rural human settlement environment in various prefecture-level cities, leading to significant spatial mismatches between the two. (2) Jinzhong, Linfen, and Yuncheng belonged to the rural tourism leading type of moderately coupled coordination level. Jincheng, Changzhi, and Lüliang belonged to the synchronous type of moderately coupled coordination level. Taiyuan and Yangquan belonged to the rural tourism lagging type of moderately coupled coordination level. Xinzhou and Datong belonged to the synchronous type of barely coupled coordination level. Shuozhou belonged to the rural tourism lagging type of primary coupled coordination level. (3) Infrastructure, public services, and industrial institutions were the key obstacle factors restricting the coupling coordinative development of rural tourism and the rural human settlement environment in Shanxi Province. There were significant disparities in the distributions of obstacles among the seven dimensions, and the key obstacle factors varied for each prefecture-level city. (4) In the future, Shanxi Province should strengthen infrastructure construction, improve public service levels, and optimize the supply of rural tourism. Based on the coupling coordinative relationships and the status of obstacle factors in each prefecture-level city, appropriate measures should be taken to promote sustainable and coordinated development of rural tourism and the rural human settlement environment.

The issue of imbalanced and insufficient development in China’s tourism industry remains prominent. Clarifying the spatiotemporal evolution characteristics and driving forces of tourism efficiency is crucial for enhancing efficiency and promoting the high-quality development of regional tourism. Using the data envelopment analysis model, this study assesses the tourism development efficiency of 31 provinces (excluding Hong Kong, Macao, and Taiwan regions) from 2009 to 2019. It employs spatial autocorrelation, cold and hot spot analysis, and regression models to analyze the spatiotemporal evolution characteristics and factors influencing China’s provincial unit tourism efficiency. The research reveals the following: (1) Between 2009 and 2019, China’s tourism industry efficiency exhibited a steady upward trend. Significant differences in the spatial distribution of various efficiency levels were observed, with strengthening spatial agglomeration characteristics. The tourism growth mode is transitioning from extensive to intensive development. (2) There is a notable spatial positive correlation in the development efficiency of China’s provincial tourism industry. The average comprehensive efficiency, average pure technical efficiency, and average scale efficiency of tourism industry development exhibit a spatial pattern of “hot in the south and cold in the north” at the local level. (3) The comprehensive efficiency of the tourism industry is strongly influenced by the quality of tourism resources. Pure technical efficiency is primarily affected by the positive impact of transportation reachability, while the quality of tourism development is the main positive impact factor of scale efficiency. (4) Enriching tourism product formats, improving regional tourism cooperation mechanisms, and optimizing the tourism industry structure emerge as crucial strategies for enhancing the development efficiency of China’s provincial tourism industry. The research findings provide a theoretical basis and practical paradigm for formulating regional tourism collaborative development strategies and achieving the high-quality development of the tourism industry.

Achieving high-quality tourism development relies on the rational layout of regional tourist attractions, which serves as an inherent requirement and fundamental guarantee. This study delves into the spatial pattern evolution and influencing factors of A-level scenic spots in northwestern China from 2010 to 2020. Using GIS spatial technology, we analyze the spatial and temporal distribution characteristics of scenic spots and construct an index system that encompasses social, economic, and environmental aspects. In addition, geographic detectors are employed to elucidate the internal mechanism of spatial pattern evolution and influencing factors. The findings reveal the following: (1) A noticeable imbalance exists in the number of A-level tourist attractions in northwestern China, with an increasing spatial concentration trend along a “northwest-southeast” axis. The central axis is delineated by the “Turpan City-Jiuquan City-Haibei Tibetan Autonomous Prefecture-Lanzhou City-Baoji City-Xi’an City” line. The spatial structure of scenic spots undergoes an evolution process from “scattered point” to “group-type patch” and ultimately to an “inverted L-shaped strip”. (2) Five influential factors, namely resident population, per capita GDP, tourism income, traffic mileage, and policy intensity, significantly shape the spatial pattern evolution of A-level tourist attractions. (3) The impact of social factors demonstrates a two-stage pattern of initial decline followed by steady increase, indicating rising influence. Economic factors exhibit periodic ups and downs in their influence, whereas environmental factors, although displaying a tendency to rise, experience a relatively stable range of change.

The quantification and assessment of carbon emission efficiency and its influencing factors in the tourism sector are crucial for advancing environmentally-friendly development in the tourism economy of Yellow River Basin, China. This study develops an input-output table for evaluating the carbon emission efficiency of tourism. In addition to traditional factors such as capital, labor, and energy, we incorporate technological innovation. The desired output is the total tourism revenue, while the non-desired output is the carbon emission during tourism, integrated into the Super-Slack-Based Measure (SBM). Employing the Malmquist-Luenberger index and the kernel density estimation method, we analyzed tourism carbon emission efficiency from both static and dynamic perspectives. Furthermore, we established a spatial Durbin model to examine spatial spillover effects. Our results revealed the following: (1) During 2000—2019, the carbon emission efficiency of tourism in the Yellow River Basin initially experienced an upward fluctuation followed by a subsequent downward trend. Provinces and regions exhibited a diminishing difference, with a spatial distribution pattern that indicated lower efficiency in the west and higher efficiency in the east. (2) Regarding dynamic efficiency, both the Malmquist-Luenberger index and kernel density estimation trends indicated a weakening polarization phenomenon in carbon emission efficiency. Technological progress significantly contributed to changes in the tourism industry’s carbon emission efficiency. (3) Influencing factors that include positive spillover effects from environmental regulation and urbanization, enhanced local tourism carbon emission efficiency. Conversely, industrial structure, openness, technology level, and tourism industry agglomeration were found to have adverse effects. Economic development levels hindered the improvement of carbon emission efficiency in tourism; however, they exhibited a notable positive spillover effect on surrounding regions. These findings aim to establish a theoretical foundation for governments to formulate targeted policies for energy-saving and carbon-emission reduction in the tourism sector.

Achieving high-quality development for both the Xinjiang Production and Construction Corps (XPCC) and the local government of Xinjiang, China necessitates integrated tourism development. This paper, grounded in the theory of symbiosis, utilized tourism resources and economic data from XPCC and Xinjiang. Employing methodologies such as the accessibility model, tourism economic linkage strength model, kernel density estimation, average nearest neighbor analysis, and Tyson polygon, it investigates the symbiotic evolution of tourism resources, economic contact changes, and network structure characteristics within XPCC and Xinjiang. The study aims to uncover the tourism symbiotic development pattern, structure, and mechanism between the two entities. The findings revealed the following key insights: (1) Spatial agglomeration characteristics of tourism resources between XPCC and the local government are consistently strengthening, with resource exploitation showcasing a partial-benefit symbiotic relationship. (2) Pronounced unbalanced symbiotic characteristics exist in tourism resources between XPCC and Xinjiang, illustrating a distribution pattern where “XPCC relies on Xinjiang, the weak depends on the strong”. This distribution pattern manifests as a symbiotic evolution of “one heart in the center with multiple points around→multiple hearts with multiple points on the periphery”. (3) Accessibility, relying on the tourism transportation network to establish a more beneficial symbiotic link, exhibits an attenuating structure from the central to outer sphere. (4) Tourism economic connections exhibit characteristics of distance attenuation, north-south differences, gaps between XPCC and the local government, and coupling effects among neighboring cities. (5) The paper introduces a regional symbiosis model encompassing “intermittent parasitic, intermittent symbiosis, and mutualism”, and traces the progression of cultural symbiosis from primary to secondary stages, along with dimensions such as resource symbiosis and industrial symbiosis in host-guest interactions. The study concludes by summarizing the symbiotic development structure of “one core, three points, eight centers, two circles, and three belts”, alongside the symbiotic development mechanism of “respective development→cooperative development→mutual development”.

Forestry is a pivotal domain in the construction of ecological civilization and constitutes a fundamental industry for economic and social advancement. Functioning as a specific cornerstone of the forestry industry economy, analyzing the spatial evolution and influencing factors is crucial for decision makers to judiciously organize the forestry industry layout and foster its development. Drawing on data spanning from 2000 to 2020 for forestry enterprises in Shaanxi Province, China, this study employs geographic information system (GIS) spatial analysis techniques, including average nearest neighbor, standard deviation ellipse, and kernel density analysis, to scrutinize the spatial and temporal evolution characteristics of these enterprises. In addition, ordinary least squares regression and geographically weighted regression models were used to explore the spatial heterogeneity of factors influencing the distribution of forestry enterprises across 107 counties and districts. This study unveils the influence of various factors and spatial differentiation characteristics. The findings reveal the following: (1) The number of forestry enterprises in Shaanxi Province has steadily increased, demonstrating a discernible agglomeration pattern with strengthening degrees of concentration. (2) The overall spatial distribution of forestry enterprises in Shaanxi Province shifts eastward, yet the central nuclear density hotspot remains consistently situated in Xi’an City, forming a contiguous high-value area with Xianyang City. (3) Forestry enterprises in Shaanxi Province exhibit a distinct business scope, primarily revolving around sales and services related to forestry. As the industrial structure is optimized, there is an evident increase in the technical content of forestry enterprises, accompanied by the expansion of related service offerings from primary processing to reprocessing and deep processing. (4) Regarding the influencing factors of forestry enterprise distribution, socioeconomic factors such as total retail sales of consumer goods, gross regional product, and the number of permanent population exert the most substantial impact. However, industry-related factors, including the proportion of primary industry value added and forest area, also positively influence the distribution of forestry enterprises. Conversely, a negative correlation was observed between the registered capital average of enterprises, garden plot area, highway density, and the number of forestry enterprises, indicative of competitive pressures and the reality of expansive land area the forestry enterprises owned. These outcomes align with the characteristics of the forestry industry, which is predominantly driven by the primary sector. The factors influencing of forestry enterprise distribution in Shaanxi Province exhibit notable spatial heterogeneity. Consequently, when formulating industrial policies, it is imperative for the government and relevant departments to consider regional nuances and adopt targeted strategies to facilitate the healthy and coordinated development of the forestry industry.

This study aims to comprehensively understand the spatiotemporal patterns and dynamic evolution of rural nonfarm employment in Qinghai Province of China at the county level, contributing to the realization of “common prosperity”. Leveraging panel data spanning 2010 to 2020 from 43 county-level units in Qinghai Province, China, we employ global trend analysis, standard deviation ellipse, and Moran’s I index to unveil the spatiotemporal evolution characteristics of rural nonfarm employment from both static and dynamic perspectives. In addition, we use kernel density estimation and Markov chain to explore the dynamic evolution characteristics. Our findings indicate the following key insights: (1) The overall level of rural nonfarm employment exhibits a fluctuating upward trend, marked by distinct stages of rapid and slow growth driven by robust economic development and effective employment policies. (2) Spatially, the distribution pattern is characterized by a “high in the eastern and western, low in the middle” trend, with a noticeable shift from “due east-due west” to “northeast-southwest”. (3) Spatial correlation analysis reveals that neighboring counties, sharing similar resource endowments, nonfarm industry development concepts, and interactive effects in employment policy formulation, exhibit significant positive spatial autocorrelation. Notably, “high-high” and “low-low” agglomerations are prominent. (4) Dynamic evolution, as evidenced by kernel density estimation, indicates a narrowing of regional differences in rural nonfarm employment across Qinghai Province. Despite stable “club convergence” phenomena due to terrain conditions, resource distribution, and economic development disparities among the 43 counties, spatial factors play a crucial role that cannot be overlooked in enhancing rural nonfarm employment. The development process also reflects a noteworthy “spatial spillover” phenomenon in Qinghai Province.

In a comprehensive study conducted in 2022, 798 popular science education bases issued by the China Association for Science and Technology took center stage as the research object in this investigation. Using a multifaceted analytical approach, this study delved into the intricate spatial dynamics and typological structure of these educational establishments. The methods employed included the average nearest neighbor index, nuclear density analysis, and unbalanced index. Furthermore, this study probed the factors influencing the spatial distribution pattern of popular science education bases in China, by leveraging geographic detection and superposition analysis. This research showed important findings: (1) The spatial distribution of popular science education bases in China is uneven and clustered. The high-density clusters are mainly concentrated areas with good economic foundations and high market openness in the east, such as the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta regions. In contrast, the central and western regions exhibited low-density clusters centered around provincial capitals. (2) When examining the typology of these education bases, science and technology venues accounted for the highest proportion, showing the spatial characteristics of “dual-core and multipoint.” In contrast, “agriculture, rural areas, and farmers” popular science education bases had the lowest proportion, showing the spatial structure of “one belt and multipoint.” All types of popular science education bases exhibited unique spatial differentiation patterns. (3) The spatial distribution of these education bases was affected by a combination of human factors, such as social economy, traffic conditions, education level, scenic spot resources, and policy systems, and natural environmental factors, such as elevation and rivers. These research results have substantial implications for optimizing the spatial layout of popular science education bases in China and promoting the efficient use of popular science resources.

Scientific and well-organized rural restructuring in the northern agropastoral area of China is an important path to modernization in these areas and national rural revitalization. This study focuses on the Inner Mongolia section of the Yellow River Basin, a typical agropastoral area, to explore the characteristics of rural restructuring and identify problematic areas using rural development indicators and econometric models. Key results from this study include the following: (1) Rural development levels in all dimensions of the study area have improved to different degrees from 1990 to 2020. Generally, the level of economic development is higher than space utilization and social development during this period. (2) During the same time frame, the average level of economic restructuring degree in the counties within the study area displays an initial increase and then a decrease. In contrast, the spatial restructuring degree increased continuously, while social restructuring degrees were considerably low during this period. Spatial distributions of rural comprehensive restructuring across the study area from 1990 to 2020 indicate higher degrees in the southern and eastern regions and lower degrees in the northern and western areas. Notably, the spatial differentiation in the degree of economic restructuring is relatively slight, whereas the degree of social restructuring is considerably great, with higher levels in the southern areas and lower levels in the northern parts of the study areas. Spatial restructuring demonstrated high degrees in the Hetao Plain areas. In addition, the coupling and coordination degrees of rural economic-social-spatial restructuring in the study areas from 1990 to 2020 first increase and then decrease, with higher coordination degrees observed in the eastern parts and lower degrees in the western areas. (3) This study identified 11 counties categorized into six problem areas of rural development and restructuring, mainly distributed in the western Yellow River and northern Yinshan Mountains within the study area. These problematic counties reflect the comprehensive impacts produced by the interaction of geographical environment, resource conditions, location and transportation, economic basis, regional policies, and other factors, which must be implemented countermeasures according to the actual situation of the region.