The synergistic development of urban space and the built environment is essential for achieving sustainable urban development. This study examines Lanzhou, a river valley city, by constructing a community built environment quality evaluation index system using multi-source data to analyze its urban spatial structure and influencing factors. Key findings include: (1) From the perspective of the built environment, Lanzhou’s urban space exhibits an east-west axial, belt-like “core-periphery” structure, characterized by a spatial distribution pattern combining multiple centers with a fan-shaped expansion area dominated by the axial belt. (2) Regression analysis indicates that land price, mean elevation, distance from communities to the district administrative center, and distance to transportation stations significantly influence the urban spatial structure, while distance to subway stations, community road network density, land use type, public space availability, and population size have secondary impacts. (3) The influence of land price and land use type on the urban spatial structure has steadily increased. These findings offer theoretical and practical insights for optimizing urban spatial configurations in river valley cities and promoting high-quality urban development.

The analysis of the spatial distribution and influencing factors of key rural tourism villages in the Yellow River Basin of China is of significant strategic importance for the coordinated implementation of the rural revitalization strategy, the safeguarding of the basin’s ecological barrier function, and the activation of regional cultural heritage in the basin. Using spatial analysis, this study quantitatively analyzed the spatial distribution of 244 national key rural tourism villages across nine provinces/autonomous regions and 65 cities in the Yellow River Basin in 2023. Integrating the random forest regression model and geodetector, this study systematically reveals their spatial distribution and influencing factors. The findings reveal the following. (1) Key rural tourism villages in the Yellow River Basin exhibit significant spatial agglomeration and imbalance, forming a distribution pattern of a multi-core clustering with belt-shaped extension. (2) Random forest regression and geodetector analyses show that the distance from provincial capital cities, amount of intangible cultural heritages, and elevation are key driving factors that affect the spatial differentiation of key rural tourism villages, reflecting the dominant driving mechanism of location-resource-nature synergy. (3) Factor interaction detection shows that the interaction between road network density, urbanization rate, and other factors forms the dominant factor combination that affects the spatial differentiation between key rural tourism villages. The interaction effect between distance from provincial capital cities and annual average precipitation provides the highest spatial explanatory power, revealing the coexistence of basin differentiation and the development contradictions among key villages.

Based on the high-density observation data from 19 meteorological stations (including three national-level meteorological stations and 16 regional automatic meteorological stations) in Urumqi County during the summer of 2016—2024, this study systematically analyzes the spatial and temporal distribution characteristics of summer precipitation and precipitation days in Urumqi County, as well as their corresponding response relationship with altitude. Results revealed that the summer precipitation mainly occurs from June to July, with light rain contributing the most to the precipitation, followed by moderate rain and rainstorms. Although heavy rain only accounts for 7.8% of the summer precipitation days, its contribution toward the summer precipitation is as high as 36.1%, highlighting the high risk of extreme precipitation. In addition, the spatial distribution of the summer precipitation (in days) and precipitation at different levels (in days) exhibited a northeast southwest gradient increase, with high-value precipitation areas located in the mid- to high-mountain ranges, >1600 m above sea level. The precipitation in the front mountain range was relatively low, and the probability of heavy rain events was also low. Summer precipitation (number of days) and altitude had a significant positive correlation. For every 100 m increase in altitude, precipitation increased by 13.1 mm and precipitation days increased by 1.8 days. The maximum precipitation zone existed near an altitude of 2100 m. The research results can provide quantitative basis for the development of cloud water resources, ecosystem restoration, and the optimization of mountain flood warning indicators in the central northern slope of the Central Tianshan Mountains. This study deepens the understanding of the mountain-water cycle mechanism, and the findings can be used to implement water resource management strategies in arid areas of Central Asia.

Xinjiang requires timely and accurate monitoring of soil salinization dynamics to support effective management and sustainable land use. This study examines the Weigan-Kuqa River Delta Oasis (Weiku Oasis) in Xinjiang. Based on Sentinel-1 synthetic aperture radar imagery and Sentinel-2 optical imagery from July 2022, characteristic parameters that were significantly correlated with measured soil salinity values were extracted and optimized. Six feature space models were constructed, including three polarization combination models from Sentinel-1 ([V²-H]-[H], [V²-H]-[(V²+H²)/V], and [V²-H]-[V-H]) and three spectral index models from Sentinel-2 (CRSI-COSRI, CRSI-NDWI, and CRSI-GARI). Using the optimal model, soil salinity in the study area was inversely estimated, revealing its spatial distribution patterns and enabling precise monitoring of typical salinized areas within the Weigan-Kuqa River Delta Oasis. The results indicate that (1) The Sentinel-2-based CRSI-COSRI model achieved the best inversion performance, with a correlation coefficient (r) of 0.639 and a coefficient of determination (R²) of 0.670, significantly outperforming all other models. (2) The simulated spatial distribution of soil salinization indicated that the overall degree of soil salinization in the study area is relatively high, with an increasing trend from west to east. This study verifies the effectiveness of feature space models in the remote sensing-based inversion of soil salinization in arid regions, providing reliable data support and methodological references for regional salinized soil monitoring and management.

While the synergistic development of rural public services and rural tourism is critical for advancing rural revitalization, academic research focusing on coupling coordinated development between these two domains remains notably scarce. This study analyzes coupling coordination between rural public services and rural tourism and its impact on rural revitalization, This study uses methods including the coupling coordination degree model, the gravity center and standard deviation ellipse model, and spatial econometric models to quantitatively measure the spatiotemporal characteristics of the coupling coordination degree between the two in western China from 2010 to 2023, as well as their impacts and spatial spillover effects on rural revitalization. The findings reveal that the coupling coordination between rural public services and rural tourism in western China has increased year by year, with the overall level shifting from extreme disorder to intermediate coordination, and presenting a spatial differentiation pattern of high coupling coordination in the south and northwest, and low in the northeast. The gravity center of the coupling coordination degree exhibited a southwestward migration trend, while the standard deviation ellipse consistently maintained a northwest-southeast orientation, demonstrating a trend of first clustering and then dispersing. Furthermore, the degree of coupling coordination has a significant positive impact on rural revitalization and exhibits spatial spillover effects. The research findings can provide a theoretical basis and policy recommendations for the coordinated development of the two aspects and the region’s overall rural revitalization.

Based on the “six elements” theory of tourism, this study explores the spatial distribution characteristics and influencing factors of tourism elements in the counties of Inner Mongolia, China, in 2023. Specifically, it utilizes tourism point of interest data at the county level and employs methods such as the nearest neighbor index, kernel density estimation, entropy method, comprehensive index, spatial autocorrelation, and geographical detector. The findings reveal the following. (1) The tourism elements in counties of Inner Mongolia exhibit significant clustering characteristics, with “food”, “accommodation”, and “shopping” being the most clustered elements, followed by “entertainment” and “transportation”, whereas the “tourism” element is relatively dispersed. (2) An imbalance in the density distribution of tourism elements is observed, where areas south of the fitting line (Alagxa Left Banner to Jalaid Banner) generally have higher densities than those in the northern regions. Notably, cities such as Hohhot-Baotou-Erdos, Chifeng, and Tongliao, have dense clusters of tourism elements. (3) Tourism elements demonstrate significant positive global autocorrelation, which includes four local autocorrelation patterns: low-low, low-high, high-high, and high-low. (4) The factors influencing the spatial distribution characteristics of tourism elements in the counties of Inner Mongolia span multiple dimensions, including economic, social, cultural, and natural environments, with economic and cultural factors identified as the core influences.

Exploring the mechanism through which the digital economy influences the urban-rural income gap holds significant importance for promoting integrated urban-rural development and achieving common prosperity. Based on relevant data from 14 cities (prefectures) in Gansu Province of China from 2012 to 2022, this study employs a fixed effects model and a spatial econometric model to empirically analyze the impact mechanism and spatial effects of the digital economy on urban-rural income gap. The findings are as follows: (1) The impact of the digital economy on the urban-rural income gap in Gansu Province exhibits a nonlinear “narrowing-widening-narrowing” pattern and has entered a critical phase since 2022, with the digital economy widening the urban-rural income gap. (2) Regional heterogeneity analysis reveals that the influence of the digital economy on the urban-rural income gap varies across different regions of Gansu Province. Specifically, a pronounced “inverted N-shaped” relationship is observed in the southeastern region of Gansu, while the impact is relatively weak in the central region and statistically insignificant in the Hexi Corridor region. (3) Mechanism analysis indicates that industrial structure upgrading and agricultural socialized services are crucial channels through which the digital economy affects the urban-rural income gap in Gansu Province. (4) There is a notable spatial clustering phenomenon in the urban-rural income gap across Gansu Province. The direct, indirect, and total effects of the digital economy on the urban-rural income gap all demonstrate an “inverted N-shaped” relationship, implying the presence of spatial spillover effects in the digital economy’s influence on the urban-rural income gap.

Promoting high-quality urban development in the Jiziwan metropolitan area of the Yellow River is crucial for establishing a significant growth pole within China’s Yellow River Basin. This study focuses on the 15 prefecture-level cities in the Jiziwan metropolitan area, developing a comprehensive evaluation index system for high-quality urbanization based on four dimensions: population, economy, society, and ecology. To analyze the spatial and temporal divergence characteristics and driving forces of high-quality urbanization from 2012 to 2021, the study employs the entropy method, Theil index, standard deviation ellipse, and geographic detector research method. The findings reveal the following. (1) The overall level of high-quality urbanization in the Jiziwan metropolitan area of the Yellow River exhibits a fluctuating upward trend from 2012 to 2021. (2) High-quality urbanization levels in this region shows significant spatial disparities, following a “core-edge” distribution pattern. Overall differences in development levels initially rise before falling, with intra-regional disparities being the primary contributor to overall variances in high-quality urbanization. The standard deviation ellipse indicates a spatial distribution directed from “northeast to southwest”, with its center of gravity located in Ordos City, highlighting notable spatial clustering. (3) The economic base serves as the dominant factor influencing high-quality urbanization, whereas the market environment, government regulatory capacity, and scientific innovation also play critical supporting roles. This study offers theoretical insights and serves as a reference for promoting high-quality urbanization and coordinated regional development in the Jiziwan metropolitan area of the Yellow River.

The assessment of inclusive green development efficiency (IGDE) using a water cycle perspective is pivotal for the promotion of ecological sustainability and high-quality growth in the Yellow River Basin. This study addresses regional water scarcity challenges, incorporating indicators of the water cycle into an IGDE evaluation framework, relying on a super-efficiency slacks-based measure model to analyze IGDE's spatiotemporal evolution across 77 cities from 2013 to 2022. Methods of spatial autocorrelation and geographically temporally weighted regression were used to identify regional disparities and dynamic mechanisms of influence. Key findings include the following: (1) IGDE demonstrated a persistent upward trajectory, including accelerated growth, following the implementation of a national strategy for basin development, highlighting the role that policy interventions play. (2) Significant spatial heterogeneity emerged, revealing efficiency gaps between upper-basin and middle-lower basin regions. (3) High-efficiency clusters centered on economically advanced cities exhibited weakening spatial dependency over time. (4) Urbanization, natural resource endowments, institutional governance, and social innovation were identified as core drivers, and their impacts displayed distinct spatiotemporal variabilities. Theoretically, the research in this study advances sustainability science by integrating water cycle dynamics into green development metrics in a way that addresses limitations in conventional efficiency assessments. Methodologically, it establishes a novel spatiotemporal analytical framework that combines the measurement of efficiency, spatial econometrics, and regression modeling to decipher complex regional interactions. In a practical perspective, the findings provide actionable insight to optimize resource allocation, enhancing cross-regional governance and formulating adaptive policies tailored to basin-specific conditions. Bridging ecological objectives and socioeconomic inclusivity, this study offers empirical evidence that supports the coordinated management of water resources and green development in the Yellow River Basin.

This study aims to explore the mechanism of co-evolution between new quality productivity and new urbanization and alleviate the contradictions between them to contribute to achieving Chinese-style modernization. For this purpose, this study considers 31 provinces (including municipalities and autonomous regions) in China as research objects, constructing a theoretical framework for the co-evolution of “new quality productivity-new urbanization”, and uses the CRITIC weight analysis method and the Haken co-evolution model to measure new quality productivity and new urbanization levels and analyze their co-evolution mechanisms. The following results are obtained: (1) During the observation period, new urbanization and new quality productivity levels significantly improved, and the characteristics of spatial differentiation have become more obvious, presenting a regional development trend of “the east is leading, the middle is catching up, and the west is lagging behind”. (2) New quality productivity plays a dominant role in the dual-new complex system and is the core variable driving the system’s orderly evolution. Meanwhile, there are positive feedback mechanisms within and between the systems, and the cumulative and self-enhancing nature of the internal elements are key driving forces for the formation of positive feedback mechanisms. (3) The co-evolution of the dual-new system has undergone two stages: Rapid advancement (2014—2020) and stable operations (2020—2023). Spatially, it continues to show a distribution feature of “strong in the east and weak in the west”. Cultivating new quality productivity and building new urbanization in a way that is tailored to the local conditions, optimizing the co-evolution mechanism of the dual-new system, and continuously injecting new elements into the system are key paths toward achieving upward evolution. The findings provide a reference for achieving coordinated development of new quality productivity and new urbanization, resolving the contradictions between economic efficiency and social equity, and achieving Chinese-style modernization.

This study addresses the critical need for precise agricultural population distribution data to inform modern agricultural system development and policy formulation. We integrated country-level demographic data from the Seventh National Population Census with the China Land Use Remote Sensing Monitoring Dataset to develop a novel grid-based spatial distribution model. This methodological approach enabled the first comprehensive visualization of China’s agricultural population density at a 1 km resolution, with validation metrics confirming the high statistical reliability of the results. Our spatial analysis revealed three significant geographic patterns: (1) The Hu Huanyong Line (Hu Line) presents a profound demographic divide, with southeastern regions exhibiting an average agricultural population density (30.57 persons·km^-2) nearly 15.9 times higher than northwestern regions (1.92 persons·km^-2). (2) Agricultural population distribution follows China’s three-tiered topographical gradient, with densities increasing significantly from the western plateau (0.98 persons·km^-2) through the central highlands (11.27 persons·km^-2) to the eastern plains (30.76 persons·km^-2). (3) Environmental determinants strongly influence agricultural settlement patterns, creating a clear dichotomy between densely populated warm, humid, low-altitude agricultural zones, and sparsely distributed cold-arid plateau and hilly agricultural regions. These findings provide an empirical basis for targeted agriculture development strategies: Prioritizing digital agriculture technologies in high-density regions like the Huang-Huai Plain; developing integrated agritourism models in ecologically sensitive areas; and implementing specialized training programs to cultivate a professional agricultural workforce adapted to regional conditions.

Under the influence of global warming, the disaster risks associated with extreme precipitation events have intensified. These risks pose serious threats to regional socioeconomic development and the safety of life and property. Considering historical daily meteorological data from 1981 to 2024, this study examines the spatiotemporal distribution patterns of extreme precipitation indices in the Ili River Basin, Xinjiang, China. Furthermore, using data from multiple models under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and applying the multimodel ensemble mean and Sen’s slope estimation method, this study estimates the changes in these indices under different scenarios from 2025 to 2050. The results indicate that: (1) From 1981 to 2024, most extreme precipitation indices in the Ili River Basin exhibited an increasing trend, especially in the eastern and southwestern mountainous regions. (2) From 2025 to 2050, under the SSP245 and SSP585 scenarios, extreme precipitation is estimated to result in large fluctuations but in an upward trend. In particularly, under the SSP585 scenario, precipitation events are expected to become more frequent and intense, with remarkable increases in annual precipitation and extreme precipitation events in the eastern and southern mountainous regions of the Ili River Basin, indicating a stronger upward trend and increased risk. By contrast, extreme precipitation events are projected to be relatively fewer in the northern and central plains. This spatial heterogeneity may have differentiated impacts on the frequency of natural disasters and agricultural and pastoral production in the region. The findings provide a scientific basis for preventing and mitigating extreme precipitation hazards and support high-quality regional development in the Ili River Basin.

To investigate the impact of new quality productive forces on the high-quality development of tourism, clarify their mutual influence, and improve the high-quality development of tourism. This study used nine provinces and autonomous regions in the Yellow River Basin as the research subject to establish a measurement index system for new quality productive forces and the high-quality development of tourism. Entropy values, fixed-effects models, and mediation effect models were used to measure new quality productive forces and the high-quality development of tourism in the nine provinces and autonomous regions from 2013 to 2022, analyzing their mutual influence. The results reveal that (1) New quality productive forces significantly and positively affect the high-quality development of tourism. (2) Cultural-tourism integration and technological progress mediate the relationship between new quality productive forces and the high-quality development of tourism. (3) New quality productive forces exert a more pronounced promotional effect on the high-quality development of tourism in regions with lower economic development levels. (4) Each component of new-type productive forces (new technologies, laborers, objects of labor, and means of labor) promotes the high-quality development of tourism, with laborers and means of labor playing more prominent roles at present. Therefore, localities should completely recognize the guiding values of new quality productive forces, formulate differentiated developmental strategies based on regional realities, and advance the high-quality development of tourism to help achieve the goals of Chinese modernization.

To examine the historical and projected variations of cold and warm extreme temperature indices in Xinjiang, China under global warming, this study provides a scientific basis for developing climate adaptation strategies. Using observational data from 52 meteorological stations in Xinjiang (1960—2021) and Coupled model intercomparison project phase 6 (CMIP6) climate model outputs (1960—2100), models with superior simulation accuracy were selected. Multi-model ensemble means were then applied to analyze four cold and four warm extreme temperature indices during the historical period and under three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The results show that: (1) From 1960 to 2021, cold indices significantly decreased, while warm indices increased, with nighttime changes exceeding daytime variations, reflecting an overall regional warming trend. (2) Future projections (2025—2100) indicate continued decreases in cold indices and increases in warm indices across all scenarios, with the SSP5-8.5 pathway exhibiting the most pronounced changes. (3) Spatially, cold and warm indices change consistently across Xinjiang, with both regional differences and commonalities. Summer days and warm nights exhibit strong similarity under all scenarios, whereas frost days, cool nights, cool days, and growing season length show higher consistency under SSP2-4.5 and SSP5-8.5. Xinjiang is already undergoing an extreme warming process, which is expected to intensify. Strengthening adaptive capacity is therefore essential to ensure sustainable regional development.

Changes to glaciers in the Ulugh Muztagh region significantly impact water resources in southern Xinjiang. This study extracted glacier area and terminus changes in Ulugh Muztagh region glaciers using multi-source remote sensing data from 1960 to 2023 and deep learning methods. Differences and driving factors were analyzed from the perspectives of glacier units and topographic features. The results show that (1) Overall, Ulugh Muztagh glaciers retreated from 1960 to 2023, with an average annual area loss of 0.83 km²·a^-1 and a terminus retreat rate of 2.21 m·a^-1. (2) In terms of intra-glacier regional differences, the retreat rate of glacier area was higher on south- and east-facing slopes and decreased with increasing elevation and slope. The terminus retreat rate was greater on east- and west-facing slopes (4.42 m·a^-1 and 4.01 m·a^-1, respectively) than on south- and north-facing slopes (1.63 m·a^-1 and 1.45 m·a^-1, respectively). (3) The spatial differences in glacier area and terminus changes in the Ulugh Muztagh region are mainly influenced by topography and climate. Sunny slopes receive more solar radiation, accelerating glacier melt, while lower elevations are prone to retreat due to rising temperatures. These findings provide a scientific basis for understanding the mechanisms by which alpine glaciers respond to climate change and offer important references for water resource management and ecological security assessment in southern Xinjiang.

As the core spatial units of oasis systems—hosting concentrated population functions, economic activities, and public services—the expansion of oasis cities is constrained by ecological patterns while simultaneously driving oasis evolution. Systematically identifying the spatial-temporal evolution of oasis and oasis cities is fundamental for coordinating ecological protection and spatial development in arid zones. This study delineates the spatial distribution of oasis in northwest China from 2000 to 2023 using evapotranspiration and the normalized difference vegetation index, while urban expansion data are extracted from the annual China land cover dataset. A synergy assessment is conducted by constructing an oasis and city synergy index (OCSI) to quantify the coordination between oasis and urban expansion across 31 typical oasis cities. Further, the impacts of various urban expansion patterns on oasis landscape structures are classified. The findings reveal that: (1) From 2000 to 2023, oasis areas increased by 0.90×10⁵ km², representing a 36.89% expansion. Concurrently, the number of oasis patches declined from 135 to 101, indicating a trend toward larger and more consolidated oasis, mainly through edge expansion and infilling. Urban areas expanded by 4.34×10³ km²—a 361.60% increase—outpacing oasis growth. Urban spatial expansion was categorized into four patterns: Infilling, edge expansion, leapfrogging, and river-dependent expansion. (2) OCSI analysis indicates that the urban and oasis expansion rates were similar in 8 cities, while critical disparities existed in the remaining 23. Terrain complexity and resource limitations contributed to mismatches, whereas economically developed or well-managed cities exhibited higher synergy levels. (3) Cities dominated by edge or infilling expansion modes displayed higher OCSI values, reflecting stronger spatial synergy with oasis expansion. By contrast, cities characterized by leapfrogging or river-dependent expansion showed low and fluctuating synergy owing to their dispersed spatial patterns or linear development along water bodies. This study elucidates the complex spatial interaction between urban development and oasis evolution in the northwest arid zone. Although these processes are dynamically coupled, coordinated development does not spontaneously occur. Achieving sustainable long-term balance necessitates region-specific strategies to optimize urban and oasis spatial configurations, thereby fostering synergistic evolution and ensuring ecological security and sustainable development in arid regions.

The water resources of rivers and lakes are essential for human survival and development, and their protection and sustainable use have become a global priority. In this study, rivers and lakes in western Mongolia were investigated through field surveys conducted in the summer of 2023 to evaluate water quality contamination. By measuring chemical parameters, heavy metals, and comprehensive indicators, the spatiotemporal variation in water quality was analyzed using the single-factor evaluation method, the comprehensive pollution index method, and the comprehensive trophic status index. The aim was to provide a scientific basis for ecological protection and the region's sustainable socio-economic development. The results showed that: (1) Surface waters in western Mongolia were alkaline, with spatial variations in different indicators. Except for Uvs Lake, Kyrgyz Lake, and the lower reaches of the Khovd River, the remaining areas complied with relevant water quality standards of the world, Mongolia, and China. (2) The main pollution indicators were the permanganate index and ammonia nitrogen, with excessive organic matter primarily linked to grazing activities and domestic sewage discharge. (3) Significant spatial differences in lake trophic status were observed, with some lakes exhibiting severe eutrophication. Although areas with low nutrient concentrations presented a relatively small risk of eutrophication, continuous monitoring of nitrogen-phosphorus ratios remains necessary.

This study examines the spatial distribution patterns of 899 ski resorts across China from a multi-scale perspective, integrating national natural geographical zones and provincial regions. Using spatial analysis techniques including the Voronoi coefficient of variation, kernel density estimation, and geographic detector models, we investigated both the spatial differentiation characteristics and driving factors of Chinese ski resort distribution. Our analysis revealed three key findings: (1) Regional distribution pattern: China’s ski resorts exhibit a distinct “dense in the north, sparse in the south, more in the east, less in the west” spatial configuration. The primary concentrations appear in north China, northeast China, east China, and northwest China. (2) Spatial agglomeration structure: A “one core, three areas, multiple facets” pattern emerges at the national scale. High-density areas are predominantly concentrated in northeast China (Heilongjiang and Jilin Provinces), north China (Beijing City, Hebei Province), and northwest China (Xinjiang Uygur Autonomous Region, Shaanxi Province). By contrast, central, south china, and southwest China show a sparse distribution of ski resorts. (3) Hierarchical driving factors: The determinants of ski resort spatial differentiation rank as follows: Natural environment>transport capacity>socio-economic development>tourism development level. Significant interaction exists among these factors, primarily through dual-factor enhancement mechanisms, demonstrating that both environmental and socioeconomic variables jointly shape spatial distribution. Based on these findings, we recommend leveraging spatial agglomeration advantages, implementing regionally differentiated development strategies, and strengthening infrastructure to promote high-quality development of China’s winter sports economy.

This research integrates the Flus-Markov model and the equivalent factor method to analyze dynamic changes in the land use patterns in the Tarim River Basin from 2012 to 2032, evaluate the spatiotemporal characteristics of ecosystem service value (ESV), and predict its future trends, based on Landsat remote sensing images and socioeconomic data. The results show that: (1) From 2012 to 2032, the area of unused land and water first decreased and then increased, while the cultivated land area expanded and grassland degraded significantly continuously, resulting in a decrease of 2093.72×10⁸ yuan in the total ESV. The contributions of grassland and water decreased by 2984.17×10⁸ yuan and 38.44×10⁸ yuan, respectively. (2) The spatial distribution of ESV shows a significant gradient, decreasing from high values in the northwest to low values in the southeast. Hydrological regulation, climate regulation, and gas regulation are key service functions. (3) Sensitivity analysis shows that changes in water bodies and grasslands have the greatest impact on ESV. A low value of the elasticity of coefficient correction indicates that the estimation results are robust. Model validation reveals a Kappa coefficient of 0.95, indicating reliable prediction accuracy. (4) Land use and normalized difference vegetation index are the main factors influencing the ESV of the Tarim River Basin. This study reveals the correlation between the degradation of ecological service functions and increased land use in the Tarim River Basin. ESV could be improved by optimizing land use structure, strengthening grassland and water conservation, and providing a scientific basis for ecological security and sustainable development in arid areas.

The primary goal of green development is to improve the overall welfare associated with sustainable practices. The digital economy has a dual effect on regional green development. This study systematically analyzes the theoretical mechanisms through which the digital economy influences green development welfare. An empirical assessment was conducted using panel data from 36 resource cities in the Yellow River Basin for the years 2013 to 2022, employing both the double-fixed effect model and spatial Durbin model. The findings indicate that: (1) Regarding spatial and temporal evolution, the overall level of green development welfare is relatively low, showing a gradual upward trend over time, with a spatial distribution pattern characterized by medium and low levels, supplemented by a few high-level points. (2) The digital economy significantly enhances the level of regional green development welfare among resource cities in the Yellow River Basin, and this effect remains robust under testing. (3) Regarding heterogeneous effects, the digital economy plays a particularly important role in promoting welfare in growing resource cities. (4) Analysis of spatial spillover reveals that the digital economy has a positive spatial spillover effect on green development welfare, with both direct and total effects being significantly positive, although the indirect effect is significantly negative. These results can assist the region in synergizing the digital economy with green development welfare, thereby promoting a form of Chinese-style modernization that fosters harmonious coexistence between human beings and nature.

Evaluating rural development from a resilience perspective is significant for breaking the urban-rural dual structure and promoting comprehensive rural revitalization. This article takes 86 counties in Gansu Province as the research object and constructs a rural resilience evaluation index system based on three dimensions: “resilience, adaptability, and reconstruction capability”. Using spatial autocorrelation analysis and geographic detector models, it reveals the spatiotemporal evolution of rural resilience and its driving mechanisms in counties of Gansu Province from 2010 to 2022. The results indicated that (1) The resilience level of rural areas in Gansu Province has significantly improved, with obvious spatial differentiation characteristics. The resilience of rural areas in central and eastern Gansu is relatively high, while some counties in Hexi, Gannan, and Linxia have lower resilience. The number of high-resilience counties continues to increase, while the number of low-resilience counties continues to decrease. (2) There is a spatial positive correlation in rural resilience, and the correlation is gradually weakening. The degree of spatial agglomeration is declining, with high-agglomeration areas shrinking toward the central Gansu region and low-agglomeration areas concentrated in counties such as Gannan and Linxia. (3) The level of rural social services, economic development, and agricultural production has a significant impact on rural resilience. The explanatory power of rural industrial structure for rural resilience is steadily increasing, and rural resilience is driven by economic development, resource optimization, industrial transformation, and service guarantee mechanisms. This study’s results provide scientific reference for the implementation of rural resilience development in Gansu Province.

Using daily rainfall data from 45 national meteorological observation stations in southern Xinjiang of China from 1961 to 2022, we analyzed the spatiotemporal distribution and variability of rainfall, identified extreme rainfall thresholds, and examined extreme rainfall characteristics. The results show that (1) Over the past 62 years, the region with the highest and most rapidly increasing annual average rainfall in southern Xinjiang has been located in the middle mountain belt at an altitude of 1500-2500 m, with a growth rate of 5.4 mm·(10a)^-1. This increase is mainly reflected in the greater number of rainfall days, particularly large-scale rainfall days, while the increase in heavy-rainstorm-level rainfall and above is especially pronounced. (2) Based on a comparative analysis using the percentile method, the 99^th percentile was identified as the threshold for extreme rainfall in southern Xinjiang, corresponding to 14.1-35.4 mm. Thresholds in the western and mountain-adjacent regions are higher than those in the eastern basin-desert areas, and the extreme rainfall threshold has increased at a rate of 0.7 mm·(10a)^-1. Stations with the most rapid increases are primarily located in the mountainous areas of Kashgar, western Hotan, and northern Bayingol Mongolian Autonomous Prefecture. (3) Over the past 62 years, the number of extreme rainfall events in southern Xinjiang has generally ranged from 10-20 times, while in the Tianshan Mountains, events can persist for more than 20 times. Extreme rainfall events have increased in frequency at a rate of 0.9 events per decade.

In the overall national security concept in the new era, historical blocks are facing dual challenges of disturbances and resilience building. Taking the historical block of Kashi Old City as the research object, this studybuilds a pressure-state-response model comprising six elements: Extreme disaster pressure, climate environment pressure, alley composition capacity, alley component density, infrastructure response, and public service response. It selects 44 key factors closely related to resilience to natural disturbances and uses the entropy weight method and the analytic hierarchy process to establish a multidimensional resilience evaluation system for historical blocks. The evaluation results show that (1) The comprehensive resilience index of the historical block of Kashi Old City is 1.84 (Level II), and the overall coping ability is weak. The resilience of the state layer (38.83%) is significantly higher than that of the response layer (27.45%), indicating its strong self-regulating ability but weak postdisaster management. (2) The key restrictive factors are the flood inundation radius, historical street and alley greening rate, and average summer solar radiation intensity, highlighting the synergistic risks between high-density built environments and climate sensitivity. (3) The wisdom of traditional construction is not linked to modern disaster prevention needs, leading to a contradiction between protection and safety. The results reveal a quantitative framework for integrated multi-hazard defense and living conservation of historic districts in arid zones, thereby promoting the synergistic development of cultural heritage conservation and ecological security.

Rapid urbanization and the attendant spatial expansion of urban regions can alter the structure of ecosystems, degrade habitat quality, and thereby impact sustainable development. Investigating the effects of urban expansion on habitat quality is crucial for the rational allocation of land use and supporting the restoration and reconstruction of ecosystems. This study focuses on the northern Tianshan Mountain economic zone (NTMEZ) in Xinjiang, China, where future urban expansion scenarios from 2024 to 2050 under different socioeconomic pathways are predicted using the Land Use Scenario Dynamic-Urban (LUSD-urban) model. The spatiotemporal changes in habitat quality from 2000 to 2050 in the region are also assessed. The results show that: (1) Between 2000 and 2023, urban land in the NTMEZ rapidly expanded from 551.72 km² to 1756.11 km², with an annual expansion rate of 54.70 km². From 2023 to 2050, under the fossil fuel pathway, urban land expansion is expected to be most significant, whereas under the regional competition pathway, expansion is expected to be least pronounced. The area of urban land is expected to further expand to between 3176.27 km² and 3859.20 km², with an annual expansion rate ranging from 244.03 km² to 369.38 km². (2) From 2000 to 2023, habitat quality in the NTMEZ declined from 0.551 to 0.520, representing a loss rate of 5.574%. From 2023 to 2050, habitat quality is expected to continue to decrease, with an anticipated loss of 0.57×10^-2‒0.82×10^-2, corresponding to a loss rate of 1.10%~1.58%. (3) The main driver of habitat quality loss is the encroachment of urban land on grasslands. In future urban planning and management, greater emphasis should be placed on the restoration of ecological land in the NTMEZ to ensure the region’s sustainable development.

Grassland vegetation biomass is a key indicator of grassland ecosystem productivity and carbon storage. Its spatial distribution pattern and driving mechanisms are of great scientific significance for understanding the maintenance of regional grassland ecosystem structure and function and their responses to climate change. Taking the Qinghai Lake Basin as the study area, this research integrates field sampling data (collected in July-August 2023) and remote sensing data to analyze the spatial distribution characteristics of grassland vegetation biomass (including aboveground and belowground components) and to explore its driving pathways using statistical analysis, correlation analysis, and structural equation modeling. The results reveal (1) Significant differences in biomass among different vegetation types, with meadow types demonstrating higher values than steppe types. Aboveground biomass is highest in mountain shrub meadows (311.54 g·m^-2) and lowest in mountain solifluction meadows (64.67 g·m^-2), whereas belowground biomass is highest in dwarf kobresia meadows (3534.05 g·m^-2) and lowest in rhodiola desert (339.12 g·m^-2). (2) High aboveground biomass values are primarily concentrated in the middle and lower reaches of the Shaliu River Basin and the southern region surrounding the lake, whereas the high-value areas for belowground and total biomass are primarily located in the middle reaches of the Buha River, the Quanji River, the Qiadangqu River Basin and middle reaches of the Shaliu River. Lower altitude areas provide more suitable temperatures and fertile soil, thereby promoting the growth of aboveground parts. Conversely, due to colder conditions and poorer soils, higher altitude regions drive plants to enhance root system development and improve resource acquisition capacity. (3) Structural equation modeling revealed that ecosystem carbon use efficiency (total effect: -0.44) and soil bulk density (total effect: -0.59) were direct factors affecting both aboveground and belowground biomass of grassland vegetation. In conclusion, vegetation type, and regional environment collectively affected grassland vegetation in the Qinghai Lake Basin, identifying ecosystem carbon use efficiency and soil bulk density as the primary determinants. This study provides critical data and scientific support for understanding vegetation biomass spatial patterns and for guiding grassland conservation and restoration in the Qinghai Lake Basin.

In the context of an aging population and the “healthy China” strategy, the rational allocation of urban medical facilities is crucial for enhancing the health and well-being of the elderly. This study utilizes multi-source data, including the Seventh National Census, points of interest for medical facilities, and path planning, along with methodologies such as the average nearest neighbor, an improved two-step floating catchment area method, and bivariate local spatial autocorrelation analysis, to investigate the accessibility of medical treatment for the elderly and the alignment of supply and demand in Lanzhou City, Gansu, China in 2020. The results reveal the following. (1) The elderly population in Lanzhou is unevenly distributed, exhibiting a “ual core” structure characterized by varying density and aging rates. (2) The spatial clustering patterns of medical facilities differ by level: city-level facilities exhibit a “single-center” structure, district-level facilities follow a “one main, multiple secondary” distribution pattern, and street-level facilities adopt a “multi-center” distribution pattern. (3) Accessibility to medical facilities varies significantly among different levels, Specifically, the city and district levels show considerable unevenness, street-level facilities have the broadest range of high-accessibility areas, even though some streets remain low-accessibility “blind spots”. (4) The uneven distribution of medical facilities leads to a mismatch between the elderly population and available medical services at the city, district, and street levels. These research results offer valuable insights for the rational allocation of urban medical facilities and the development of healthy cities.

This study analyzes daily temperature data from 38 meteorological stations in Xizang, China, covering the period from 1981 to 2023. A new method for seasonal division in Xizang was employed to categorize the four seasons, and the regional climate changes, temporal shifts in the start dates of each season, and trends in seasonal changes were examined. The results show the following. (1) Areas with four distinct seasons in Xizang are primarily found along the Yarlung Zangbo River and in Nyingchi City, whereas regions with less distinct seasonal variations (including areas without a summer season) are mainly situated in the western and northern parts of Xizang as well as in the high-altitude regions of the Himalayas. (2) In Xizang, the beginning of spring and summer tends to occur earlier, whereas the onset of autumn and winter tends to be delayed. Notably, the start date of spring was significantly earlier in 2000, whereas the onset of autumn and winter was significantly delayed in 2003 and 1995, respectively. (3) Regarding the timing of seasonal starts, the first empirical orthogonal function (EOF1) for spring and autumn exhibited a pattern of “northwest low and southeast high in spring, and middle high and both sides low in autumn”. In spring, the second EOF (EOF2) presented a contrasting distribution pattern of “northwest positive and southeast negative”, whereas in autumn, EOF2 showed an opposite spatial distribution pattern characterized by “southwest positive and northeast negative”. The EOF1 in winter revealed a “high in the north and low in the southwest” pattern, whereas the EOF2 shared similarities with that of spring’s EOF2. (4) Looking ahead, we anticipate that the start dates of spring and summer will be delayed, whereas those for autumn and winter will be advanced.

This study describes the gradual achievement of common prosperity as a goal and a path of Chinese-style modernization. Using panel data from Ningxia county areas from 2006 to 2022, we develop a comprehensive evaluation index system for assessing common prosperity at the county level, We employ exploratory spatial data analysis, the Thiel index, and baseline regression analysis to investigate the spatiotemporal differentiation patterns and driving factors affecting the common prosperity levels in Ningxia counties. The results show the following. (1) From 2006 to 2022, the level of common prosperity in Ningxia county areas generally exhibited an upward trend; however, the growth rates in northern, central, and southern regions of Ningxia varied significantly across different dimensions of the index. (2) According to the Thiel index, disparities in common prosperity development have regularly existed in Ningxia county areas, but the overall inequality has been gradually decreasing. Notably, the growth rate of the disparity between groups has far exceeded that of the disparity within groups. (3) The level of common prosperity in Ningxia county areas has transformed overall to a higher level, presenting a “patchy distribution” spatial pattern with significant clustering characteristics. (4) The progression toward common prosperity in Ningxia county areas has been relatively slow, driven positively by factors such as economic development, education levels, industrial structure, and infrastructure. By contrast, the urbanization process has shown a stage-inhibitory effect on the advancement of common prosperity in these areas.

This study examines 474 national nature reserves in China from 1956 to 2023, utilizing kernel density estimation to analyze their spatiotemporal distribution patterns. A social network analysis model is then employed to measure the attributes of these reserves and to propose integrated protection strategies. The findings reveal the following. (1) The evolution of China’s national nature reserves can be categorized into four distinct stages: Preliminary exploration, vigorous development, slow development, and consolidation and improvement. This development has resulted in a spatial pattern characterized by large and scattered reserves in the west, and small and clustered reserves in the east. (2) Topological analysis reveals that the nodes within the national nature reserve network exhibit strong cohesion, small-world characteristics, and a prominent “core-periphery” effect. (3) The network’s spatial pattern demonstrates significant heterogeneity among protection clusters, forming a “triangular” framework for reserve aggregation, with key vertices located in the middle and lower reaches of the Yangtze River, the Northeast Plain, the Changbai Mountain area, and the Qinghai-Xizang Plateau. Based on the natural endowments and geographic conditions of these reserve clusters, we propose corresponding integrated protection strategies from the perspective of the association network, aimed at providing guidance for the integration and optimization of nature reserves.

In the summer of 2023, the Hexi Corridor, northwest China experienced its most intense regional high-temperature drought in nearly 60 years, accompanied by frequent wind and dust events. Notably, on September 6—7, Minqin County recorded its most severe sandstorm in almost 40 years. This study investigates two significant sandstorm events (on August 16, on September 6—7) in the Hexi Corridor during the summer and autumn of 2023. The evolution of meteorological elements, synoptic conditions, and boundary layer characteristics preceding the events is analyzed. The sources and transport pathways of dust are determined using the HYSPLIT model’s backward trajectory analysis and Sunflower 8 dust monitoring. The findings are as follows: (1) The regional high temperatures and drought provided ample material conditions for sandstorm development. (2) Synoptic analysis reveals that low-pressure troughs between 65°-85°E and 50°-58°N, combined with a stepped trough pattern from eastern Xinjiang to the Hexi Corridor and mesoscale shear, contributed to the events. At 500 hPa, the cold center intensity was ≤−20 ℃; at 700 hPa, it was ≤0 ℃. The mid-level jet exceeded 20 m·s⁻¹, the low-level jet exceeded 14 m·s⁻¹, and the K index was ≥21 ℃. Convergence occurred below 700 hPa (divergence ≤-0.75×10⁻⁵ s⁻¹), and divergence occurred between 700-650 hPa (divergence ≥0.75×10⁻⁵ s⁻¹). Ascending motion was observed between 800-600 hPa with intensity ≤−0.6 hPa·s⁻¹. Below 700 hPa was a region of positive vorticity with intensity ≥0.75×10⁻⁵ s⁻¹. (3) When the dust source is primarily local, near-surface humidity is the key factor influencing sandstorm intensity. (4) Compared to spring events, sandstorms in summer and autumn require stronger vertical motion, higher wind speeds, and larger 3 h pressure differentials for formation.

Based on continuous observations of PM₁₀ and PM_2.5 at the Akedala regional atmospheric background station from 2011 to 2023, we employed statistical and meteorological correlation analyses, the HYSPLIT-4 model, the potential source contribution function (PSCF), and the concentration-weighted trajectory (CWT) method to investigate the variation trends and source characteristics of PM₁₀ and PM_2.5 mass concentrations. The results showed that: (1) From 2011 to 2023, the annual average mass concentration of PM₁₀ increased from 12.1 μg·m^-3 to 23.2 μg·m^-3, while PM_2.5 increased from 7.3 μg·m^-3 to 10.8 μg·m^-3, with annual growth rates of 0.81 μg·m^-3·a^-1 and 0.31 μg·m^-3·a^-1, respectively, indicating that PM₁₀ increased faster than PM_2.5. (2) PM₁₀ and PM_2.5 exhibited clear seasonal variations, with higher values in spring and winter and lower values in summer and autumn. The PM_2.5/PM₁₀ ratio displayed a bimodal distribution (0.4-0.5 and 0.8-0.9), where lower ratios indicated natural contributions and higher ratios reflected anthropogenic sources. (3) Air mass trajectory analysis suggested that PM₁₀ primarily originated from eastern arid regions of Kazakhstan (PSCF values 0.4-0.7), whereas PM_2.5 mainly came from anthropogenic sources in northern Xinjiang (PSCF values 0.5-0.8). (4) In 2023, four high-concentration PM₁₀ events (peaks 681.1-822.6 μg·m^-3) and five high-concentration PM_2.5 events (peaks 294.2-551.4 μg·m^-3) were observed, with durations typically less than one hour, exhibiting “short-term high-intensity” characteristics. (5) Compared with Lin’an station, PM₁₀ and PM_2.5 at Akedala showed “low baseline, high variability, and short peaks”, with baseline values lower than Lin’an but higher peak concentrations. This study provides a scientific basis for understanding atmospheric background particulate matter in arid regions and analyzing transboundary transport patterns, supporting air quality assessment and regional collaborative governance in northwest China.

Hail is an extreme weather phenomenon caused by intense convective activity, characterized by rapid development and substantial damage, particularly threatening to the Longdong region, eastern Gansu Province, China where agriculture constitutes the economic backbone. In the context of climate change, it is imperative to investigate the climatic characteristics of hail in Longdong and identify its influencing factors. Utilizing hail observation and disaster records from 15 regional meteorological stations spanning from 1978 to 2023, along with ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts, this study employs linear trend estimation, the Mann-Kendall test, and Morlet wavelet analysis to examine the spatial-temporal distribution of hail and its key drivers. The results indicate the following: (1) Hail days exhibit uneven spatial distribution, with higher frequencies in the northwest and southeast, and lower frequencies in the central and southern regions. Hail-prone zones are predominantly situated on downslope terrains, leeward mountain slopes, and the Ziwuling Mountains, while hail-scarce areas are concentrated in the flat loess plateau and southern Liupan Mountains. (2) Over the past 46 years, hail days have declined, with the sharpest decrease observed in spring. Hail predominantly occurs between May and August, accounting for 81.5% of annual hail events. (3) The diurnal variation of hail follows a single-peak pattern, with peak occurrences between 15:00 and 18:00. Hail events of short duration (0-9 minutes) and medium diameter are most frequent. Localized hail occurs more frequently than regional hail, though the incidence of the latter is increasing significantly. (4) A primary oscillation period of 3 years, and secondary cycles of 14 and 35 years, characterize hail frequency. (5) The principal meteorological drivers of hail vary seasonally, with convective available potential energy and the 0 ℃ isotherm height being the most influential. These findings provide a scientific basis for understanding hail occurrence patterns in Longdong and serve as a reference for enhancing forecasting and early warning systems, as well as for guiding artificial hail suppression strategies.

Promoting the coordinated development of different elderly care models is an effective way to optimize the allocation of elderly care service resources in our country. Based on panel data from 2018 to 2022, this study empirically analyzes spatiotemporal coupling coordination and influencing factors of home community elderly care and institutional elderly care in China using a coupling coordination model, a geographic detector, and other methods. The results indicate that (1) The coupling coordination degree and relative development degree between home community elderly care and institutional elderly care are generally on the rise. The coupling coordination degree has shown a continuous improvement trend over time. The relative development degree of home community elderly care is gradually becoming clear with the trend of “synchronous development>advanced development>lagging development”. (2) The number of provinces entering the coordination stage (III and IV) continues to increase and shows an evolutionary pattern of gradually spreading from the central and eastern regions to the western and northeastern regions in space. The phenomenon of stage transition in relative development is more pronounced, and the western region has significantly more provinces in transition than the central and eastern regions. (3) The coupling coordination degree has a positive spatial correlation and a fluctuating upward trend. The correlation strength shows a spatial pattern of “western>eastern>central>northeast”, with mostly HH-type and LL-type clustering. (4) Organizational strength, elderly care demand, and technological level are the main influencing factors of the coupling coordination degree. This study’s findings can provide a theoretical basis and policy recommendations for addressing structural contradictions in China’s elderly care service supply and for innovating the development of the elderly care policy system.

Quantitative assessment of the long-term variations in cropland water use efficiency (WUEc) is crucial for optimizing water resource utilization and achieving high yields as well aseffective water-saving in irrigated agriculture in arid regions. This research integrates gross primary productivity of crops (GPPc), grop evapotranspiration (ETc), WUEc, and meteorological as well as vegetation data in the Aksu River Basin from 2002 to 2022, a typical arid region, and systematically identifies the spatiotemporal patterns of WUEc and the synergistic effects of multiple driving factorsby applying Sen’s slope, the Mann-Kendall trend test, seasonal and trend decomposition using loess, partial correlation analysis, and path analysis. The results indicate the following: (1) Temporal characteristics: GPPc and ETc in the basin increased significantly at rates of 0.6 g C·m^-2·a^-1 and 0.3 mm·a^-1, respectively, while WUEc declined at a rate of 0.02 g C·mm^-1·m^-2·a^-1. Intraannual dynamics showed a unimodal pattern for GPPc and ETc (peaking in August), and a bimodal pattern for WUEc (with peaks in April and October). (2) Spatial patterns: Regions with declining WUEc accounted for 60.3% of the area under consideration, while those with increasing GPPc and ETc covered 97.1% and 94.8%, respectively, highlighting a widespread phenomenon of “increased production without efficiency gains” in the basin. (3) Driving factor analysis: WUEc was significantly negatively correlated with temperature (T), vapor pressure deficit, and leaf area index (LAI), with the negatively correlated areas corresponding to 77%-89%, and positively correlated with precipitation (Pre), corresponding to 87% of the total area. (4) Path analysis: T and Pre primarily influenced WUEc by regulating GPPc, whereas LAI affected WUEc via ETc. Normalized difference vegetation index and enhanced vegetation index impacted WUEc through the combined regulation of both ETc and GPPc. T and LAI were identified as dominant drivers, suggesting a dual-stress mechanism acting on agroecosystems in arid regions. This study elucidates the multi-scale evolution patterns of WUEc in arid regions and its nonlinear driving mechanisms, providing a scientific basis for optimizing agricultural water resource management under climate change.

Using remote sensing and GIS methods, this study reconstructs the spatiotemporal patterns of glacier changes and hazards along the China-Tajikistan Pamir highway from 2000 to 2021. We conducted a glacier hazard exposure assessment using both the range transformation and entropy weight methods. The results reveal the following. (1) Since 2000, the glacier area shrinkage rate along the China-Tajikistan Pamir highway has been 0.20%·a^-1±0.06%·a^-1, with a mass balance of -0.25±0.04 m w.e.·a^-1. In addition, the glacial lake area has expanded at a rate of 0.45%·a^-1 since 1992, all of which are several times greater than the overall levels observed in the entire Pamirs. (2) The increasing instability of glaciers has directly contributed to a widespread risk of glacier disasters along the China-Tajikistan Pamir highway, with medium and high-risk areas primarily concentrated in the western section of the highway. (3) The spatial pattern of glacier disaster exposure along the China-Tajikistan Pamir highway is largely influenced by factors such as the distribution density of disaster-causing elements and disaster-bearing bodies, the complexity of the terrain and geological environment, as well as spatial variations in climate change. This study elucidates the overarching pattern of glacier hazard exposure in the areas along the China-Tajikistan Pamir highway, offering valuable insights for research on hazard vulnerability, impact, and prediction.

Xinjiang, an ecologically fragile region in China that is prone to aeolian desertification, has a surface-soil particle composition that plays a critical role in regional ecosystem stability. This study analyzed the particle composition of surface soils collected from 180 sampling points across 60 plots in Xinjiang, China. Using the aridity index, sampling sites were classified into semi-arid, arid, and hyper-arid plots to examine the fractal characteristics of soil particle-size distributions across drought gradients and to assess how environmental factors influence these fractal properties in surface soils. The results demonstrated that (1) With increasing aridity, the surface-soil particle-size distribution became progressively coarser and showed clear transitional features. Semi-arid and arid plots were dominated by silt, whereas hyper-arid plots were dominated by sand, with very fine and fine sand together accounting for 53.48%. (2) Overall, the soils exhibited poor sorting. Particle dispersion decreased with increasing aridity, resulting in progressively narrower size distributions, and the fractal dimensions ranged from 1.98 to 2.47. (3) The fractal dimension was strongly influenced by clay content, showing positive correlations with clay and silt and a significant negative correlation with sand. Furthermore, the model-fitting performance of the fractal dimension in plots under different aridity gradients followed the order: hyper-arid>arid>semi-arid. (4) The factor detector results indicated that mean annual precipitation (MAP), mean annual temperature (MAT), soil type, and parent material had strong explanatory power for the soil fractal dimension. Structural equation modeling further showed that, among the continuous variables examined, climatic factors had a significant influence on the surface-soil fractal dimension in Xinjiang. Specifically, MAP and wind speed exerted positive effects, whereas MAT had a negative effect. This research provides a scientific basis for regional soil use and ecological management, supporting soil and water conservation, vegetation restoration, and ecosystem stability in Xinjiang.

The Zhundong region in Xinjiang, a typical arid and semi-arid area, is a vital national energy base with abundant coal resources. However, intensive coal mining and related industrial activities have caused severe ecological issues, including land desertification, salinization, and PM_2.5 pollution, intensifying the conflict between resource exploitation and ecological preservation. To accurately evaluate the ecological environment quality (EEQ) of this region, an arid modified remote sensing ecological index (ARSEI) is proposed herein. The ARSEI improves upon the traditional remote sensing ecological index by incorporating indicators for salinity, desertification, and air pollution, besides greenness, wetness, and heat. Using the Google Earth Engine platform, Landsat 5/8 images from 2000 to 2023 were processed to generate the ARSEI. The first principal component derived via principal component analysis was used to construct the ARSEI, with the direction of the wetness component applied to resolve the eigenvector ambiguity. Temporal trends were analyzed using Sen’s slope estimator and Mann-Kendall trend test, and ecological vulnerability was assessed based on the sensitivity and adaptability of the ARSEI. The optimal parameter-based geographical detector was employed to identify key driving factors and their interactions. Results indicated that the ARSEI of the Zhundong region showed a trend of initial decline followed by a partial recovery from 2000 to 2023, with its mean value decreasing from 0.368 in 2000 to 0.225 in 2018, before increasing to 0.289 in 2023. Spatially, the EEQ was generally poor, with over 60% of the area classified as “poor” or “relatively poor”, exhibiting a clear north-south gradient where the southern part exhibited better ecological conditions. Trend analysis revealed that 83.5% of the region experienced significant ecological degradation, whereas only 4.6% showed improvement, mainly in the southern agricultural and urban areas with low ecological vulnerability. Single-factor detection identified human activity intensity (q>0.6) and evapotranspiration (q>0.35) as the primary drivers. The interaction between temperature and human activity intensity had the strongest explanatory power (q>0.7), indicating nonlinear enhancement effects. In summary, large-scale resource development has exerted considerable pressure on the already fragile ecosystem. Although ecological restoration measures since 2019 have led to a partial recovery, the northern mining areas remain highly vulnerable due to water scarcity and soil degradation. The ARSEI model demonstrates enhanced applicability in arid resource-based regions and offers a scientific basis for ecological protection and sustainable development strategies.

Food security is fundamental to national development and social stability. The analysis of the spatiotemporal evolution of crop planting structures provides a theoretical basis for ensuring regional food security and promoting the sustainable development of agriculture. This study examines the crop planting structure across 117 counties (cities/districts) in the Fenwei Plain, Shanxi Province and Shaanxi Province, China based on agricultural statistical data for the period of 2000—2022. Employing methods such as the standard deviation ellipse model and spatial autocorrelation analysis, the spatial and temporal dynamics of major crop planting structures over this period are explored. The results indicate the following. (1) Over the study period, 88 distinct crop planting structure types were identified, with wheat, corn, and their combinations (wheat type, corn type, wheat-corn type, and corn-wheat type) being the dominant types. Moreover, spatially and temporally, the number of wheat-type counties gradually declined, while the number of corn-type counties steadily increased. Wheat-corn-type counties expanded from the southwest to the northeast of the Fenwei Plain, while corn and wheat varieties were dispersed throughout the region. Crop planting structure diversity peaked in 2005, whereas the richness index was lowest in 2015. (2) For the period of 2000—2022, the planting patterns of wheat, corn, and vegetables exhibited a distribution trend along the northeast-southwest axis. The center of gravity for wheat remained stable, whereas that of corn shifted progressively northeastward. Meanwhile, the center of gravity for vegetables moved from Heyang County to Chengcheng County in a southwestward direction. Thus, the spatial distribution of major crops in the Fenwei Plain demonstrates a differentiated development trend, with a decline in wheat cultivation and expansion in corn and vegetable cultivation. To ensure food security, future adjustments to the crop planting structure of the Fenwei Plain should be made based on an analysis of these spatiotemporal trends and supported by macroeconomic regulatory measures.

Improving economic resilience is an important part of achieving high-quality development. This paper empirically explores the influence of spatial distribution mode of provincial innovation agglomeration on urban economic resilience using the panel data of 275 cities in China from 2004 to 2021. The conclusions are as follows: (1) The monocentric pattern of innovative agglomeration inhibits the urban economy resilience, while the polycentric pattern promotes the urban economy resilience, and with the increase of the degree of multi-center, its effect on improving the urban economy resilience is enhanced. (2) Compared with cities with strong economic resilience, the polycentric pattern of innovation agglomeration has a more prominent empowerment effect on cities with weak economic resilience. (3) The polycentric pattern of innovation agglomeration has the strongest effect on improving the urban economic resilience in the eastern region of China, followed by the central region, while the effect on improving the urban economic resilience in the western region is not significant. (4) The mechanism identification test shows that the polycentric pattern of innovation agglomeration can enhance the resilience of urban economy through independent intermediary channels to promote the flow of innovation factors and improve the return on capital, and chain intermediary channels of “innovation factors flow-improve the return on capital”. The research conclusion provides beneficial practical enlightenment for optimizing the spatial distribution structure of innovation to enhance the urban economic resilience.

Accurately quantifying the accessibility of kindergarten education is essential for evaluating the spatial allocation efficiency of resources, particularly in underrepresented areas of the education system. This study focuses on the main urban area of Lanzhou City, Gansu Province, China, utilizing data on kindergarten points of interest, school-age children, available places, and road grades. Using kernel density analysis and a multi-level-multi-travel mode Gaussian accessibility algorithm, we examine the agglomeration characteristics and accessibility of kindergartens at various levels. We also employ a spatial regression model and bivariate spatial autocorrelation to investigate the factors affecting accessibility distribution. The findings reveal that: (1) Kindergartens are distributed in “one core” and “four center” patterns, with density decreasing from east to west. Notably, densely populated areas in Xigu District are independently clustered. The classifications of provincial-level, municipal-level, district-level standard kindergartens, and general kindergartens predominantly exhibit the spatial distribution characteristics of a “single core”. (2) The accessibility of all kindergartens displays a spatial bias trending eastward, and “south-to-north”, and high accessibility areas are concentrated in Chengguan District and Qilihe District. The accessibility of kindergartens, based on their grades and quality, shows a “multi-center” structure, with general kindergartens reflecting the highest accessibility values, indicating their significant role in serving local enrollment. (3) Factors such as school-age population, family economic status, and kindergarten enrollment quotas influence school accessibility. By contrast, road network density and bus stop availability negatively affect accessibility, although this correlation is not significant. Kindergarten education fees also have a negative effect on accessibility.