High-quality development is essential for China’s modernization. The in-depth implementation of the new development philosophy has become crucial for promoting China’s development in the context of “domestic and international” double-cycle development. This study constructs an evaluation index based on the new development philosophy, measures the level of China’s high-quality development majorly from 2005 to 2020, dynamically examines the spatial and temporal pattern of China’s high-quality development on a multi-level spatial scale, and explores its influence mechanism with the help of the obstacle degree model. The results show that: (1) China’s high-quality development level has increased as a whole, with the high-quality development index rising from 0.056 in 2005 to 0.092 in 2020, with an average annual growth rate of 3.36% and an overall development pattern of “high level in the east and fast growth rate in the west”. (2) Spatial correlation, China’s high-quality development shows a significant positive correlation, with cities with higher levels of high-quality development concentrated in the eastern coastal region, the Pearl River Delta region, and the Beijing-Tianjin-Hebei region, and those with lower levels of high-quality development clustered in the western region. (3) In terms of dynamic evolution, China’s high-quality development level shows a small rightward shift, the polarization of high-quality development level is weakening, and the rightward trailing situation has been alleviated. (4) Obstacles to identifying the factors affecting China’s high-quality development include the amount of imports, exports, and the number of foreign direct investment contract projects. From the criterion level, openness and innovation are the biggest obstacles to high-quality development, and the obstacle degree of each criterion level shows significant spatial differentiation characteristics in the research period. The results can provide a scientific basis for China’s path to upgrading and building a modern socialist country.

As a large province with forest resources, assessing the value of forest ecosystem services in Yunnan is of great significance to maintain the sustainable development of Yunnan’s economy. Based on the latest survey data of Yunnan Province, i.e., the forest resources type II survey data, and in accordance with the Specification for Forest Ecosystem Service Function Assessment (GB/T 38582-2020), the value of forest ecosystem service function of 16 cities (prefectures) in Yunnan was assessed, and the ridge regression method was used to study the main factors affecting the value differences among cities (prefectures). The results show that: (1) The value of forest ecosystem services in Yunnan is 982.926×10⁹ yuan yr^-1, of which the value of carbon fixation and oxygen release is the largest. (2) The top four cities (prefectures) in terms of value of services are Pu’er City > Chuxiong Prefecture > Diqing Prefecture > Dali Prefecture; the bottom four cities (prefectures) are Kunming City > Yuxi City > Dehong Prefecture > Zhaotong City; (3) The main factors affecting the value of the service function of each city (prefecture) are forested land area, forest cover, GDP and population density. The findings of this study provided a reference for the sustainable development of the ecological environment in the prefectures and cities of Yunnan Province.

Habitat quality plays a crucial role in enhancing the regional ecological environment and safeguarding biodiversity, with topography being a key element influencing the structure and function of ecosystem services. This research aims to assess habitat suitability across various topographic gradients, analyze the spatial heterogeneity of habitat quality between 2000 and 2020, and explore the relationship between influencing factors and habitat quality. InVEST model is used to evaluate the spatial-temporal evolution characteristics of habitat quality in Zhaotong City, focusing on how topographic gradients impact habitat quality distribution. The study also delves into the factors affecting habitat quality in Zhaotong City, including land use patterns, elevation, slope, average annual temperature and other variables. The results indicate three key aspects of this system. (1) During the study period, the land use types were mainly forest land, farmland and grassland, with construction land experiencing the most significant increase. (2) From 2000 to 2020, the quality areas of high and medium habitats in Zhaotong City decreased, while the quality areas of medium-high, medium-low and low habitats increased. (3) The study revealed a notable topographic gradient effect on habitat quality, with the primary driver shifting from GDP to land use type and subsequently to average annual precipitation in Zhaotong City. The transfer between different grades of habitat quality mainly presents the characteristics of “descending” transfer, with medium-low quality habitats typically found on medium-low topographic gradients and medium-high quality habitats on medium-high gradients. Cross-detection results show that land use type exhibited the strongest correlation with other influencing factors. Therefore, this study can provide a scientific basis for policy makers to protect biodiversity, enhance ecosystem services and promote regional economic development.

The Three-River Source Region is an important ecological security barrier in China. Revealing the spatiotemporal evolution characteristics of its landscape types and ecological risks is of great significance for promoting ecological restoration and landscape pattern optimization in the Three-River Source Region. Selecting the Three-River Source Region for a case study and applying the land-use data from four periods (the 1990, 2000, 2010, and 2020), we constructed a landscape ecological risk assessment model for the region based on the landscape pattern index. We then quantitatively assessed the ecological risks and determined the characteristics of their spatial-temporal evolution. The results showed that: (1) The overall landscape ecological risk in the Three- River Source Region tended to decrease from northwest to southeast, and the distribution of landscape ecological risk was closely related to the natural plateau zones and the changes in land cover. (2) From 1990 to 2020, the areas covered by grasslands, water bodies, croplands, and construction land in the Three-River Source Region increased, while the areas of woodlands and unused land decreased. The spatial-temporal changes in the ecological landscape risk were consistent with the characteristics of the changes in the landscape types. The areas categorized as highest, higher, medium, lower and lowest risk areas, while highest and higher risk areas decreased by 9.76%, medium risk areas increased by 1.03%, lower risk areas increased by 8.99%, and lowest risk areas decreased by 0.26%, respectively. (3) Overall, the Three-River Source Region was dominated by very low to medium ecological risk, the areas of which accounted for more than 70% of the entire study area. Overall ecological risks are decreasing, and there is positive spatial autocorrelation of landscape ecological risks in adjacent evaluation units.

Urbanization has resulted in growing ecological pressures on cities, necessitating assessments of urban ecological quality. Long-term characterization of regional dynamics and drivers is critical for environmental management. This study proposes an enhanced ecological quality model (MRSEI) incorporating vegetation cover and EVI rather than just NDVI. The MRSEI model was applied to analyse ecological quality in Yulin City during 2000-2018 using Landsat TM/OLI data on Google Earth Engine. Geographic detectors also quantified anthropogenic and environmental influences on the study area. The results are summarized as follows: (1) MRSEI showed an average correlation coefficient of 0.840 with other indices, demonstrating higher representativeness than individual components. The principal component analysis indicated a 12.88% increase in explained variance. MRSEI also exhibited significantly improved identification of roads, villages, and unused lands over RSEI, better matching ground conditions, and suitability for regional ecological assessment. (2) During 2000-2020, the average MRSEI in Yulin City was 0.481, peaking at 0.518 in 2018, indicating general ecological improvement over time. Spatially, conditions were better in the southeast than northwest. While 38.81% of the area showed significant improvement, 10.15% exhibited significant deterioration, concentrated in western Dingbian and Jingbian counties, highlighting areas requiring enhanced protection. (3) Ecological conditions in Yulin City remained stable over time. High-high clusters were concentrated in eastern counties (Qingjian, Wubao, Jia, Fugu) and central lower-altitude areas near Yokoyama and Zizhou. Low-low clusters predominated in the northern Yuyang desert and high-altitude western Dingbian regions. (4) Enhanced vegetation cover had the greatest influence in improving Yulin’s ecological quality. Rainfall was the most impactful environmental driver, while precipitation and land use change interactions showed the strongest combined effects. In contrast, air quality had minimal explanatory power in Yulin City. (5) The MRSEI model significantly impacts the ecological assessment of urban areas, thereby enhancing urban ecological monitoring accuracy. Moreover, our analysis demonstrates applicability to watershed regions, facilitating comprehensive regional ecological assessment and monitoring.

Street greening is a popular topic in urban design research. Traditionally, assessments for urban greening levels using Normalised Difference Vegetation Index (NDVI) from satellite remote sensing images, often overlooking street greening from a human-scale perspective. This study combined spatial syntax, machine learning techniques, streetscape images, and remote sensing data to comprehensively assess thoroughly analyse street greening levels in Chengdu’s Fourth Ring Road. Additionally, by integrating accessibility analysis with Green View Index (GVI), this study identified areas that should be prioritised for street greening interventions. The results indicate that: (1) Streets in the western and southern regions of Chengdu City’s Fourth Ring Road possessed higher GVI. (2) There is a significant difference in the overall distributions of GVI and NDVI, particularly in the central and eastern regions. (3) Streets with “high commuting and walking accessibility (low GVI) overlapped in the area east of Shuncheng Avenue. The methodology presented in this study can serve as a reference for human-scale street greening in Chengdu and other cities.

Duolun County, located in the Xilingol League, is a typical agro-pastoral ecotone in the north and is also the source of the Luan River system. Whether the development and utilization of regional water resources are reasonable and whether the water ecological environment is sustainable are the key issues that local government departments cannot ignore. By investigating the current situation of water resource development and utilization in Duolun County, this study revealed that the per capita water usage and the water usage per ten thousand yuan of GDP in Duolun County in 2020 were lower than the average level in the Inner Mongolia, and the level of water usage was relatively better. By using the nine-scale method and the analytic hierarchy process to construct an evaluation model of the water ecological environment of Duolun County, the comprehensive score of Duolun County was 8.35 (total score is 10), indicating that the water ecological environment in the study area was currently in a good state. The evaluation model has reference value for the future management of the water ecological environment in Duolun County and for continuous related research.

Land use/cover change (LUCC) is a measure that offers insights into the interaction between human activities and the natural environment, which significantly impacts the ecological environment of a region. Based on data from the period from 2000 to 2020 regarding land use, topography, climate, the economy, and population, this study investigates the spatial and temporal evolution of land use in the Liuchong River Basin, examining the interaction between human activities and the natural environment using the land use dynamics model, the transfer matrix model, the kernel density model, and the geodetic detector. The results indicate that: (1) The type of land cover in Liuchong River Basin primarily comprises cropland, forest, and shrubs, with the land use change mode mainly consisting of an increase in the impervious area and a decrease in surface area covered by shrubs. (2) The dynamic degree for single land use of barren, impervious, and waters indicates a significant increase, with areas covered by shrubs decreasing by 9.37%. In addition, the change in the degree of single land use for other types of cover is more stable, with the degree of comprehensive land use being 7.95%. The areas experiencing the greatest land use change in the watershed went through conditions that can be described as “sporadic distribution” to “dispersed” to “relatively concentrated”. (3) Air temperature, rainfall, and elevation are important factors driving land use changes in the Liuchong River Basin. The impact of nighttime lighting, gross domestic product (GDP), and normalized difference vegetation index (NDVI) on land use change have gradually increased over time. The results of the interaction detection indicated that the explanatory power of the interaction between the driving factors in each period for land-use changes was always greater than that of any single factor. The results of this study offer evidence-based support and scientific references for spatial planning, soil and water conservation, and ecological restoration in a watershed.

The spatial spillover effect of energy insecurity on total factor productivity in the iron and steel industry, as well as the potential moderating role of industrial agglomeration, remains poorly understood. This study investigated the spatial spillover effect of energy security on total factor productivity and the moderating role of industrial agglomeration in the relationship between energy security and total factor productivity in the iron and steel industry. Panel data from 24 provinces in China spanning the years 2010 to 2019 were used for this analysis. The research findings demonstrate a positive spatial spillover effect of energy security on total factor productivity, which displays a distinct pattern of attenuated spatial spillover effects. Moreover, evidence from quasi-natural experiments shows a negative spillover effect on total factor productivity when using the energy security-policy interaction term, highlighting the significant impact of policy factors on total factor productivity. Threshold effect tests reveal a “strong-weak” V-shaped trend in the impact of energy security with the increase of industrial agglomeration levels. In addition, this study found an inverted U-shaped relationship between energy security and the impact of industrial agglomeration, suggesting that enhancing energy security contributes to the growth of total factor productivity in the iron and steel industry. The ultimate objective of this research is to provide valuable policy recommendations to the government for ensuring energy security and promoting the sustainable growth of total factor productivity in the iron and steel industry.

This study examines the coupling and coordinated development of the competitiveness system of the convention and exhibition industry in China’s prefecture-level cities. Using an index system, the entropy weight method, and the coupling coordination degree model this study quantitatively measures and investigates the characteristics and influencing mechanisms of change in the convention and exhibition industry. The analysis shows that between 2013 and 2019, in China’s urban convention and exhibition industry, the competitiveness subsystem and its comprehensive development level have improved significantly. Additionally, among the factors influencing the convention and exhibition industry in China, the economic strength of cities exerts the greatest impact, followed by the capacity of the post and telecommunications sectors, while vitality has the least impact. The level of informatization plays a crucial role in the coupling, coordinated development, and change of the competitiveness system of an urban exhibition industry. Improvement in the competitiveness of the urban exhibition industry is closely related to a variety of resource elements. Each city should highlight its own endowment advantages and status, clarify its scale and positioning, and form a regional development pattern of differentiated development and dislocation competition with surrounding cities through the development strategy of consolidating advantages and addressing shortcomings.

Improving rural multifunctionality (RM) is crucial for achieving the Sustainable Development Goals (SDGs) target of sustainable consumption and production. This study establishes a clear link between functional composition, interaction and urban-rural integration, constructs a system of indicators for evaluating RM, and examines the interactions between functions using Spearman’s rank correlation coefficient to determine the dominant function type. The results show that: (1) Villages in most counties in Henan Province are in the polarized or dominant development type. Only a few villages dominated by non-agricultural production are able to realize comprehensive and balanced development. (2) Functional and spatial differentiation exists in rural areas of different types of counties. The non-agricultural production function is more prominent in villages around cities, while villages in mountainous and hilly areas emphasize the ecological conservation function. The development of villages in plains and remote areas focuses on agricultural production function. (3) The relationship between RM is complex and diverse. Agricultural production often constrains other functions. The development of non-agricultural production functions has a positive effect on the improvement of social security functions. Cultural tourism and ecological conservation functions are mutually reinforcing. This study enhances the understanding of overall pattern and type differences of RM and provides valuable insights for formulating more targeted regional economic development policies in the future.

Based on the coupling coordination development model, this study evaluated the coupling and coordination degrees between agricultural economic growth and rural ecological environment using data from Hunan Province, China, from 2007 to 2021. The results revealed that: (1) Except for a slight fluctuation in 2013, Hunan Province’s agricultural economy has steadily developed. The eco-environmental evaluation index first decreases and then increases. Together, this index and that for the agricultural economy exhibit a “scissor shape.” However, since 2013, they have maintained a stable, synchronized development trend. (2) The coupling degree is slightly low in 2007, high in other years, and indicates high-quality coupling overall. (3) The coordinated development degree exhibits two stages: fluctuations from 2007 to 2016 and stead growth from 2017 to 2021. Currently, coordinated development is at a moderate level. (4) The composite system of agricultural economic growth and ecological environment in Hunan Province has successively exhibited the following phases: Economic extremely lag, economic serious lag, environmental relatively lag, and environmental serious lag.This suggests that the agricultural economy's high-quality growth should be coordinated with the ecological environment. Areas of focus can include optimizing the agriculture industry structure; developing environment-friendly agricultural industries; strengthening the role of science and technology, especially big data technology, in agricultural economic growth; and strengthening the government’s macro-guidance.

Under the rural revitalization strategy, farmers’ livelihood strategy is transitioning from unitary traditional agriculture to multiple dominant strategy. The adoption of non-agricultural livelihood strategy is not only a mitigation plan for agricultural livelihood vulnerability, but also a means to achieve the goal of rural revitalization. Based on the relevant literature from 2000 to 2023, this study adopts meta-analysis method to comprehensively review the researches on non-agricultural livelihood strategy selection at home and abroad, and discusses the influence of livelihood capital on non-agricultural livelihood strategy selection from the perspective of sustainable livelihood. The findings are as follows: First, the direct effects of livelihood capital on non-agricultural livelihood strategy selection are different: financial capital, human capital and social capital all have promoting effects on farmers’ non-agricultural livelihood strategy selection; Natural capital has inhibitory effect on farmers’ choice of non-agricultural livelihood strategy. The effect of physical capital on farmers’ non-agricultural livelihood strategy selection is not significant. Second, non-agricultural livelihood types and terrain characteristics have a moderating effect on non-agricultural livelihood strategy selection: both non-agricultural livelihood types (engaged in industry or business) and terrain characteristics have a moderating effect on the relationship between livelihood capital and non-agricultural livelihood strategy selection. Therefore, farmers can be guided to choose non-agricultural livelihood strategies by optimizing the allocation of livelihood capital.

Coal burning is the prevailing way of heating in winter in rural areas of northern China, especially in Beijing, Tianjin, Hebei and their surrounding areas. Regrettably, the direct burning of large amounts of bulk coal is a major contributor to the serious air pollution and frequent heavy pollution days in winter in northern China. It is urgent to find ways for promoting the smooth implementation and sustainable development of clean heating in rural areas, while ensuring affordable heating solutions for rural residents. Conducting research on the WTP of rural residents for clean heating and its influencing factors can provide greater technical support for better promoting clean heating in rural areas. Through field visits and questionnaire surveys in rural areas of Shandong, Hebei, Henan and Shaanxi provinces, data on the willingness of rural residents to pay for clean heating was obtained. A multivariate regression model was then constructed based on the Contingent Valuation Method (CVM) to measure and analyze the willingness of residents to pay for clean heating and its influencing factors. Findings reveal that the highest willingness to pay (WTP) was in Hebei at 2388 yuan and its lowest was observed in Shandong at 1595 yuan, with Henan and Shaanxi registering 1608 yuan and 1929 yuan, respectively. WTP is significantly negatively correlated with age and financial burden of clean heating costs after retrofit. WTP is significantly positively correlated with total household heating hours per year, total household heating area, total household income in 2023, affordable price increase, satisfaction with the overall clean heating project, satisfaction with gas (electricity) prices, satisfaction with heating equipment, and satisfaction with indoor temperature.

As the severity of climate change escalates, agriculture, being one of the primary contributors to global carbon emissions, has progressively come under scrutiny. Thus, fostering a low-carbon agriculture system is paramount in achieving the ambitious “dual carbon” goals of reaching peak carbon and attaining carbon neutrality. This study engages urban panel data from the Yellow River Basin spanning 2001-2020 to compute the agricultural carbon emissions therein. The research harnesses a spatial Durbin model to probe the influencing mechanisms and spatial effects while examining the implications of agricultural mechanization on such emissions. The findings reveal: (1) From a spatiotemporal perspective, total agricultural carbon emissions within the Yellow River Basin exhibited an oscillating “M”-shaped pattern. Upon analyzing spatial patterns, the carbon emissions were highest downstream, moderate midstream, and least upstream, signifying pronounced regional disparities. (2) Concerning the causal elements, agricultural mechanization, from a direct effects standpoint, tends to somewhat diminish local agricultural carbon emissions. Regarding spillover effects, agricultural mechanization similarly represses carbon emissions in adjacent locales. (3) Heterogeneity analysis suggests that in the midstream cities, agricultural mechanization results in a significant decrease in agricultural carbon emissions. Contrarily, upstream and downstream cities witness a stimulating effect. At present, with China’s agricultural economy navigating intense environmental pressure, these insights lend invaluable support to practices aimed at curbing agricultural carbon emissions. By shedding light on the interaction between agricultural mechanization and carbon emissions, they offer a novel perspective and empirical data. In turn, these can contribute to formulating policies that seek to reignite rural areas while concurrently striving to meet the strategic objectives of peak carbon and carbon neutrality.

This paper investigates ecological asset accounting methods tailored for agricultural cultural heritage sites, specifically through the ancient tea forest cultural landscape of Jingmai Mountain in Pu'er. These heritage sites globally act as reservoirs of extensive cultural history and ecological richness, yet they face increasing risks and challenges from urban expansion and modernization. (1) The research develops a comprehensive methodological framework that merges ecological, economic, and cultural valuation techniques. This framework identifies and evaluates crucial ecological assets such as land, water, vegetation, fauna, and microorganisms, categorizing their value into direct values (e.g., agriculture), indirect values (e.g., flood control), and non-use values (e.g., biodiversity and cultural heritage). (2) It emphasizes the necessity of integrating cultural heritage preservation with ecological stewardship. This dual approach supports the sustainability of both cultural and natural resources, underpinning broader conservation goals and necessitating innovative management strategies for heritage conservation. (3) The study advocates for sustainable management practices that maintain the ecological and cultural integrity of these vital sites. Through detailed ecosystem analysis, the paper proposes balanced policies that cater to both ecological preservation and the socio-economic needs of local communities, promoting a replicable model for similar heritage sites worldwide. Overall, this model exemplifies how to effectively utilize ecological and cultural assets for sustainable development, ensuring the coexistence of natural and cultural values in a harmonious environment.

Rough tourism growth does not promote dual-carbon goals nor the implementation of a comprehensive saving strategy. Accordingly, the booming development of the digital economy in recent years has provided new momentum for structural upgrades and green growth in the tourism industry. This study aims to test the impact and mechanism of developments in the digital economy on the green innovation efficiency (GIE) of the tourism industry. Using provincial panel data from 2011 to 2019, this study quantifies the GIE of the tourism industry using the Super-SBM model of unexpected output. In this study, the digital economy development index was measured using principal component analysis and empirically analyzed using a two-way fixed effects regression model. The results of the study revealed that the development of the digital economy has promoted in large part the improvement of Chinese tourism GIE; the enhancement effect of the digital economy development on the eastern region is more noticeable than that of central and western regions; the digital economy can promote the enhancement of Chinese tourism GIE by promoting innovation in green technology and upgrades to industrial structure. Moreover, a distinct threshold in the promotion of tourism GIE by the digital economy exists, corresponding to a nonlinear diminishing marginal product. This study provides a new perspective for assessing the impact of the digital economy on the development of tourism GIE. Moreover, it provides a policy reference for exploring the path of tourism GIE and realizing high-quality development.

This study introduces a novel framework to dissect and understand tourists' cultural perceptions within river basins. The framework consists of two complementary parts: first, it develops a multi-dimensional system to identify cultural perceptions through textual analysis; second, it uses advanced methods like deep learning and spatial clustering to analyze and compare these perceptions across different cities and regions. The findings from the Yellow River Basin reveal six key dimensions of cultural perception: historical, architectural, folklore, food, religious, and leisure. The basin exhibits three distinct cultural patterns: an upstream polycentric network, a central ‘cultural circle’ around Xi’an, and a city-to-city pattern downstream. Furthermore, the basin is categorized into ten unique cultural perception regions, each highlighting diverse tourist perceptions. This framework not only offers a methodological beacon for future regional tourism studies but also equips managers with strategic insights to enhance the quality and cooperation in river basin tourism development.

This study employs the comprehensive index method and the coefficient of variation method to explore the integration mechanism of regional culture and tourism. It measures the integration development degree of culture and tourism subsystems in 16 prefecture-level cities in Anhui Province. Additionally, the decision-making trial and evaluation laboratory (DEMATEL) method is used to investigate the integration mechanism. The results indicate the following: From 2012 to 2021, the comprehensive index, integration degree, and integration development degree of cultural subsystems in the 16 prefecture-level cities in Anhui Province exhibited noticeable periodic changes. Between 2015 and 2019, the growth rate in eastern prefecture-level cities was significantly faster than that in central and western cities. In 2019, all regions—eastern, central, and western—experienced a downward trend, and the spatial difference in recovery growth in 2020 was minimal. Within the cultural and tourism integration system, the industry foundation and activity scale of the cultural subsystem are interdependent, while the industry foundation of the tourism subsystem results from the market scale. The central factors are primarily focused on the industrial base and the activity or market scale of the criterion layer of both subsystems. Conversely, the economic contribution of the criterion layer of the two subsystems has a minimal impact on centrality.

Rural tourism serves as a catalyst for rural revitalization and plays an important role in poverty alleviation in Inner Mongolia. This study analyzes the spatial distribution of key villages and star-rated rural (pastoral) households in Inner Mongolia as rural tourism destinations, clarifies their distribution patterns, and contributes to the development of rural tourism in Inner Mongolia. By selecting rural tourism destinations in Inner Mongolia, importing the coordinate points obtained from Baidu Map API into Arc GIS 10.8, and using indices such as the nearest neighbor index, location quotient, kernel density analysis, the geographic concentration index, and the geographic correlation ratio for quantitative analysis, this study explores the distribution patterns and identifies the driving factors influencing the distribution of rural tourism destinations in Inner Mongolia using geographic detectors. The results are：(1) Rural tourism destinations in Inner Mongolia exhibit agglomerated distribution in space, with uneven distribution among different leagues and cities. (2) The spatial density of rural tourism destinations in Inner Mongolia shows the characteristics of “a single core center, with decreasing density toward the periphery, and dispersed secondary cores, and dispersed secondary cores.” The actual geographic concentration index G is 30.23, while the distribution index G₀ under uniform conditions is 29.14. Since G is greater than G₀, a certain degree of agglomeration exists in the spatial distribution of rural tourism destinations in Inner Mongolia, but the overall degree of agglomeration is not strong. (3) Tourism infrastructure, economic development, tourism potential, and natural factors collectively influence the spatial distribution of rural tourism destinations in Inner Mongolia. Among them, economic development, tourism potential, and tourism infrastructure have significant impacts on the distribution of key villages. In terms of subsystems, the number of A-level scenic resources has the highest explanatory power (q=0.848), followed by the number of tourists received (q=0.788), employment in the tertiary industry (q=0.687), and the resident population (q=0.603), which are the main factors influencing the spatial differentiation of rural tourism destinations.

The integration of intangible cultural heritage (ICH) and tourism is a vital component of the holistic development of culture and tourism. This study examines the spatial distribution characteristics and tourism integration development models of Hulunbuir City through a spatial geography lens, employing nearest neighbor index and kernel density analysis. The results indicate the following: (1) Arts and crafts, as well as performing arts ICH resources, play a dominant role and are of a higher level, exhibiting a distinct agglomeration pattern centered around the main core area, sub-core area, and marginal area, which reflect the current distribution status. (2) Based on these findings, a spatial integration and optimization model is proposed, initially centered on the core area of ICH resources. Subsequently, a characteristic resource culture and tourism integration model is developed from three perspectives: resource-driven penetrative integration, product-driven restructured integration, and market-driven extension integration. (3) This study argues that the dynamic system driving the integrated development of ICH and tourism consists of three key subsystems: thrust, tension, and support. Their interactions constitute the dynamic mechanism underlying integrated development. Ultimately, this study provides a rational framework for the preservation and utilization of cultural heritage, thereby broadening the scope of cultural heritage studies.

Taking Shanghai as an example, this study obtained the online travel notes data from Xiaohongshu and Qunar in the past 10 years to construct the Shanghai tourist flow network (STFN) and used the methods of change point detection (CPD) and complex network analysis (CNA) to reveal the spatial structure characteristics of Shanghai tourism flow and the dynamic evolution process of STFN. The results showed that: (1) In the past 10 years, Shanghai tourist market had experienced a process of evolution from stable and orderly to short-term fluctuation and then gradual recovery, and the year of 2019 was the turning point of tourist flow network evolution. (2) The small-world and approximate scale-free characteristics of STFN were verified, and the network changed from disassortative to temporary assortative, showing a development trend of external expansion and internal separation. (3) While the centrality indicators of tourist flow network remained stable as a whole, the attention to cultural nodes was also increasing with the emergence of new nodes; (4) In terms of spatial connection, new popular nodes emerged and the relationship between them and the surrounding nodes was strengthened; (5) The spatial pattern of tourist flow network presented an inverted “V” shape and gradually expanded to southwest and southeast, forming a network with core nodes as the center and radiating outward. At the same time, newly emerging nodes at the periphery had formed relatively independent clusters.

This paper explores the pathway toward harmonious coexistence between humanity and nature through the lens of ecotourism, delving into its impact on tourists’ cognition of the natural environment, cultivation of emotional connections, and its pivotal role in shaping environmentally responsible behavior. At the Luya Mountain Scenic Area, a case study was conducted in July 2021, collecting 632 valid tourist questionnaires to investigate the nexus among “ecotourism experience”, “emotional experience”, and “environmental responsibility behavior” using structural equation modeling. Moreover, the relationship between tourism and daily environmental behavior was scrutinized with canonical correlation analysis. The findings unveil several substantial revelations: (1) Engagement experience significantly and positively influences tourists’ inclination toward responsible behavior. (2) Emotional experience mediates the relationship between educational, engagement, and escapism experiences and the inclination to act responsibly. (3) The utilization of digital information technologies positively moderates the conversion of emotional experience into a willingness to behave responsibly. (4) Ecotourism responsibility is linked to daily behavior, and cognitive and emotional experiences foster long-term environmental protection. This study provides a pioneering approach to enhancing tourism offerings within the scenic area and nurturing a sustainable human-environment relationship.

Based on the theories of sustainable tourism development, tourism lifecycle, and stakeholder theory, and guided by the “production-living-ecological space” concept, this study refines and supplements the research established by relevant scholars to construct a structural equation model focusing on production, living, ecology, and residents’ attitudes towards the development of mountain outdoor tourism. The purpose of the study is to promote the participation and support of residents in tourist areas in the development of outdoor tourism, which holds certain significance in advancing rural revitalization and sustainable development in the region. Through analyzing the data gathered primarily from residents of Siguniang Mountain Town using SPSS and SmartPLS data analysis software, this research reveals following conclusions: (1) There is a significant interaction between “production, living, and ecological space”, with living spaces having the most notable impact on the relationship with ecological spaces; (2) Perception of production has a marked impact on both living perception and ecological perception; (3) The lifestyle and ecological concepts of residents have a significant impact on their attitudes towards the development of mountain outdoor tourism. The results of this study will contribute to further exploration of mountain outdoor tourism and residents' attitudes, providing reference for local management and tourism development.

Based on data from Beijing museums spanning 1980 to 2020, this study employs spatial analysis methods such as geographical concentration index, imbalance index, kernel density and standard deviation ellipse characterize the temporal and spatial evolution of Beijing museums and analyze their influencing factors. The research shows that the museum development in Beijing has undergone three stages: a slow start, high-speed development and high-quality upgrading. The development of cultural relics and industrial museums tends towards balance, and the market-oriented development of museums continues to improve. The “single core” concentration distribution of Beijing museums is prominent, showing a typical “center edge” distribution with a trend of new core formation during expansion. Temporally, Beijing museums exhibit an inverted “L” evolution pattern, trending from north to east with Haidian and Chaoyang districts poised to become new centers. Distribution across intervals is uneven, yet the overall pattern is evolving towards a balanced distribution. The research on factors influencing the spatial distribution of museums, including population, resources, economy, and transportation, innovatively introduces educational factors. It shows that Beijing museums are transforming from “population driven” and “resource driven” to “education driven” over time.

Stray dog invasion caused by human activities poses a significant challenge to wildlife communities worldwide. Conservation biology efforts must prioritize controlling stray dog populations to maintain equilibrium within local wildlife communities. In the Helan Mountains, ungulate population recovery and the absence of top predators present critical issues. The presence of a stray dog as a predator may complicate ecological restoration efforts in the region. Through molecular and camera trapping data analyses, we investigated the overlap of ecological niches between stray dogs and local carnivores across nutritional and spatiotemporal dimensions. The results revealed a high overlap between stray dogs and local carnivores across various niches, likely linked to food abundance, suggesting the possibility of increased future competition between them. Stray dogs cannot be ignored when conservation of wild carnivores involved.