Search Results (672)

The human–environment interaction on the Qinghai–Xizang Plateau determines the direction of global human sustainable development, making it necessary to propose a refined prediction for this relationship. Currently, there is a lack of a predictive method for human–environment relationships, especially at the grid scale. This study focuses on Qinghai Province and proposes a human–environment relationship simulation method based on cellular automata (CA), utilizing land-use data and a remote sensing-based ecological (RSEI) index. The method enables grid-scale explicit predictions of human–environment relationships. The results show that by 2030, the human–environment relationship in Qinghai Province will become more diverse, with the coordination ratio rising to 11% and the degradation ratio to 7%. The ecological protection scenario serves a defensive role, preventing 3835 km² of land from degradation. In contrast, the urban development scenario plays a revitalizing role, achieving a coordinated area 2% larger than the business-as-usual scenario. By 2030, about 8956 km² of land in Qinghai will be suitable for agricultural revitalization, and 54,340 km² must be reserved for ecological protection. Due to the high-altitude environment, the human–environment relationship aligns only with the right half of the Environmental Kuznets Curve, namely, development brings greater harmony. We further discover the lag in the natural system’s response, for artificially increasing vegetation cover will not quickly improve habitat quality. Likewise, leapfrogging expansion in the urban development scenario may conceal long-term ecological risks behind short-term coordination. For stakeholders and policymakers, this study provides refined and differentiated governance measures at the grid scale, while highlighting the need to focus on underdeveloped regions and remain vigilant about the lag in human–environment relationship responses. Full article

Identifying village functional differentiation within rural territorial systems is essential for differentiated rural revitalization and place-based governance. However, existing approaches still lack effective analytical pathways for translating complex rural territorial relations and sparse planning labels into fine-grained measures of rural functional intensity. To address these gaps, this study develops a Few-Shot Hierarchical Graph Representation Learning (FH-GRL) framework. By integrating a Hierarchical Graph Infomax (HGI) model to capture cross-scale village–township–city relational dependencies and an Evidential Deep Learning (EDL) mechanism to map high-dimensional representations into class-specific evidence and Global Percentile Ranks (GPR), the framework supports fine-grained classification and continuous grading of rural functions. Empirical analysis in Pingdingshan City yields three main findings. First, within the present case study, FH-GRL shows more stable performance than traditional flat clustering and local graph models in identifying complex rural functions under limited labeled samples. Second, hierarchical context serves as a spatial calibration mechanism, reducing locally generated noise and improving the identification of village functional differentiation under spatial heterogeneity. Third, rural functional differentiation reflects the combined effects of place-based conditions and potential flow-related interaction conditions. In particular, Center villages show differentiated trajectories between endogenous production or service centers in agricultural plains and exogenous service centers along urban development axes. Overall, this study provides a planning-oriented quantitative framework for diagnosing rural functional differentiation under label scarcity and spatial heterogeneity. The GPR-based outputs can support the identification of high-intensity functional carriers, transitional villages, and general reserve areas, thereby providing diagnostic evidence for differentiated governance and tiered resource allocation. Rather than replacing formal planning judgment, the framework offers geospatially informed support for classified rural governance and more evidence-informed territorial planning. Full article

Urban–rural integration (URI) is essential for achieving sustainable regional development and addressing the long-standing urban–rural dual-structure divide. This study investigates the impact of factor mobility—specifically labor, capital, and land—on URI across 1712 Chinese counties. By constructing a multidimensional evaluation system for URI and employing a Spatial Durbin Model (SDM), we unpack the direct and indirect effects, as well as the spatial spillover effects of these factors. The results indicate that URI levels in China exhibit significant positive spatial autocorrelation and distinct regional disparities. Labor and capital mobility significantly promote URI, manifesting robust positive direct effects and spatial spillovers that benefit neighboring counties. By contrast, land mobility reveals a “structural mismatch,” whereby inefficient land-use conversion can hinder integration, particularly in less-developed regions. Heterogeneity analysis further shows that the effects of factor mobility are strongest in Eastern China, while Western regions face structural constraints. These findings suggest that sustainable urban–rural transformation requires not only the free flow of production factors but also a coordinated spatial strategy to mitigate regional imbalances. This study provides policy-relevant insights for policymakers aiming to optimize factor allocation and enhance grassroots-level sustainability within the framework of rural revitalization and integrated regional development. Full article

Against the backdrop of rural revitalization, traditional ethnic minority villages in Guizhou face the dual challenges of conservation and development. Existing research has largely focused on macro-scale morphological descriptions, lacking an operational spatial classification method that can directly guide planning and management. To address this gap, this paper takes Fengxi Village in Dejiang County as a case study, integrates Conzenian urban morphology with the concept of “management units”, and proposes a spatial unit classification method for traditional villages based on the overlay analysis of “morphological region + building unit”. First, using Conzenian plan analysis, the study systematically deconstructs land use, road systems, plot combinations, and building types of Fengxi Village to delineate morphological regions. Second, it introduces three evaluation factors—building value, building quality, and building style—and, through quantitative assessment, classifies all 702 buildings in the village into five categories, protection units, repair and improvement units, comprehensive renovation units, demolition and renewal units, and new construction units, with the number and proportion of each category calculated. On this basis, differentiated control guidelines and development strategies are proposed for each unit category. The research shows that this method represents a preliminary attempt to translate “morphological description” into “operational control”, breaking down the relatively macro goal of “integral conservation” into concrete “unit-based control” actions, thereby providing a technical workflow that can be referenced for similar studies on the fine-grained planning and management of traditional villages. The main contribution of this paper is the construction of a systematic technical framework of “morphological analysis–factor evaluation–unit-based control”, and the demonstration of its application at the micro-operational level through the Fengxi Village case study, offering a meaningful complement to the existing research in terms of operationalization. Full article

Against the background of industrial transformation and urban regeneration in old industrial bases, understanding the spatial pattern and driving mechanisms of industrial heritage is essential for its conservation and sustainable use. This study investigates 277 industrial heritage sites in Liaoning Province (including nationally designated sites, potential heritage within cultural relic protection units at all levels, and sites recognized by the China Association for Science and Technology) using kernel density estimation, standard deviation ellipse, and the GeoDetector model. The results reveal a significantly clustered distribution characterized by “dense in central–southern Liaoning, sparse in the periphery,” forming three major agglomerations: the Shenyang core, the Anshan–Benxi–Liaoyang heavy industry triangle, and the Dalian coastal industrial belt. Temporally, the distribution shows distinct phases closely linked to industrial development history and major socio-political events. Land use, GDP, and climatic factors dominate the spatial differentiation, with GDP and annual average temperature exhibiting the strongest combined explanatory power (41.67%). Based on these dominant factors and the identified core agglomeration areas, differentiated protection and utilization strategies should be formulated for core versus peripheral areas, different industrial types, and various historical periods. This provides direct empirical evidence for industrial heritage management and cultural revitalization in old industrial regions. Full article

China is at a critical stage in the coordinated promotion of ecological civilization construction, rural revitalization, and new urbanization strategies. How to scientifically coordinate the transformation of territorial spatial utilization (TSU), such as that of ecology–agriculture–urban spaces, and to build an ecological security pattern (ESP) has emerged as a critical task facing regional sustainability. To address the above problem, this study constructs a research framework to reveal the response characteristics of ESP to TSU transformation by adopting the source–surface–flow continuous field model and geographic grid analysis methods. Taking the Qinba–Dabie convergence area in China, with typical transitional characteristics and regional representativeness, as the study area, this study quantitatively analyzes the spatiotemporal evolution of the comprehensive index of TSU degree, as well as the ecological source, resistance, and flow indices across the whole territory. With the geographic grid method adopted to unify the spatial analysis grain between ESP and TSU transformations, this study further explores the response characteristics of ESP under TSU transformation. The main study findings are presented as follows: With the transformation of TSU, ESP elements such as the ecological source index, resistance index, and flow index exhibited significant spatial differentiation, and a nonlinear relationship could be observed between the TSU degree index and the ESP elements. On this basis, this study further explores and constructs a zoning method system for regional TSU control oriented to ESP, formulates targeted protection and restoration strategies, offering theoretical and practical references for the scientific compilation of territorial spatial planning and the conservation and restoration of ESP. Full article

Public data is a foundational resource and new production factor in the digital economy era. Scientific assessment of its economic effects on urban–rural integration is of great significance for promoting the revitalization of rural areas and achieving common prosperity. This study employs a double machine learning (DML) model for causal inference, using the establishment of “data trading platforms” as an exogenous policy shock to measure public data openness (Opendata). The level of urban–rural integration (Uri) is assessed through a comprehensive index system encompassing economic, population, social, spatial, and ecological dimensions, with weights assigned using the CRITIC method. Based on panel data from 259 prefecture-level cities in China (2012–2024), the analysis is conducted using machine learning algorithms such as Lasso regression, supplemented by a series of robustness and endogeneity tests. Research has found that public data openness can significantly promote urban–rural integration, and this conclusion still holds true after a series of robustness tests. Mechanism analysis indicates that public data openness promotes urban–rural integration by facilitating the flow of factors between urban and rural areas and enhancing technological innovation. Heterogeneity analysis shows that the enhancing effect of public data openness on urban–rural integration is more significant in eastern cities and non-resource-based cities. Based on these conclusions, it is recommended to further accelerate the cultivation of a standardized and unified data element market and enrich the “digital soil”, solve the problems of unsmooth flows of factors and resource constraints, strengthen data empowerment in urban–rural information sharing, and promote common prosperity in urban and rural areas. Full article

Historic and cultural districts are key carriers of urban historical continuity, and the historic buildings within them form the material basis for cultural inheritance and living conservation. Balancing heritage preservation with vitality enhancement has become a central issue in their sustainable renewal. This study examines three historic districts in Changsha—Chaozong Street, Taiping Street, and Xiwenmiaoping—using complex network analysis and multi-source data integration at the building scale to investigate building network structure, vitality distribution, and their spatial association. The results reveal distinct spatial patterns. Chaozong Street shows relatively good overall connectivity and a balanced, multi-nodal distribution of population activity and functional density. Taiping Street exhibits a strong main-street orientation, with both building connections and vitality concentrated along the main street and adjacent buildings. Xiwenmiaoping is characterized by strong local connections but weaker overall connectivity, greater reliance on a few key buildings, and vitality concentrated more at the edges than in the interior. Correlation analysis indicates a certain correspondence between building network structure and building vitality, although relationships vary across indicators; direct building connections show the clearest association with population activity intensity and functional density. The study suggests that vitality in historic districts is shaped jointly by network structure, spatial organization, and functional layout, and proposes targeted strategies for conservation and revitalization. Full article

Peri-urban village renewal in China has increasingly improved infrastructure and environmental conditions, but its effects on residents’ subjective well-being remain insufficiently understood. Taking Siqing Village in Chanba District, Xi’an, as a case study, this research examines how spatial restructuring is associated with residents’ perceptions of livability, place attachment, and well-being. A mixed-methods approach was adopted, combining field observation, spatial classification, questionnaire survey, semi-structured interviews, reliability and validity testing, Spearman correlation analysis, and hierarchical regression. The results show that recent renewal improved roads, lighting, sanitation, drainage, waste management, and housing interfaces. Questionnaire responses indicated generally positive evaluations of spatial restructuring and living environment satisfaction, although the highly positive distribution suggested a ceiling effect. Correlation analysis showed significant positive relationships among spatial restructuring perception, living environment satisfaction, place attachment, and subjective well-being. Regression results further indicated that place attachment had the strongest association with subjective well-being after spatial restructuring perception and living environment satisfaction were included. Interview findings revealed that physical improvements increased convenience and safety, but also raised concerns about reduced informal social interaction, weakened local character, and insufficient public space adaptability. The study concludes that peri-urban village renewal should not be evaluated only by visible environmental improvement, but also by its capacity to sustain everyday use, local familiarity, and residents’ emotional attachment to place. Full article

Preservation and revitalization of historic districts are critical for quality urban development and renewal. Accurately assessing what drives district vitality is essential for sustainable historic area development. Current research often uses cross-sectional data and single models, limiting understanding. This study uses Xigong District, Luoyang, and integrates multi-source data—street view imagery, points of interest, road networks, and nighttime lighting—from 2014 to 2021. MGWR and XGBoost models create a dynamic framework for analyzing how the built environment affects street vitality over time. Results: (1) Spatial effects: Physically, green exposure, functional mix, and road network access are highly spatially sensitive. Morphological indicators—commercial frontage, street continuity, complexity, and building texture—show reduced local variation over time. Perceptually, the influence of abstract color narrows each year, and subjective preference broadens. (2) Nonlinear effects: Green exposure and openness dominate but show negative inhibition and diminishing returns. Morphological, functional, and road network indicators have moderate explanatory power with clear thresholds. Perceptual importance shifts from abstract color to architectural texture, which now rises while color influence steadies. Renewal should go beyond basic greening and surface color. Instead, focus on refined, threshold-based control of form and function, and preserve authentic historic texture. This approach enables scientific, sustainable vitality. Full article

The rapid expansion of e-commerce has transformed market access in developing economies, yet its impact on the spatial structure of market participation remains insufficiently understood. While existing studies primarily examine welfare outcomes such as income growth and consumption smoothing, few investigate how digital platforms reshape the balance of market entry between urban and rural areas. Drawing on New Economic Geography and platform economics theory, this study proposes that e-commerce development rebalances urban–rural market vitality through three associative pathways: alleviating rural capital constraints, improving rural innovation environments, and promoting agricultural-industry agglomeration. Using county-level panel data covering 2725 Chinese counties from 2011 to 2022, we employ a Double Machine Learning (DML) framework to examine the association between designation as an “E-commerce into Rural Comprehensive Demonstration County” and changes in the urban–rural market vitality balance (URMAR). The results indicate that demonstration county designation is associated with a statistically significant reduction in urban–rural market disparity, as measured by both the Theil index and the absolute difference in new enterprise registrations. The directional URMAR indicator further reveals that this convergence is driven primarily by accelerated rural enterprise formation. Subsample analysis confirms that the rebalancing interpretation holds across counties with different baseline market structures. Mechanism analysis provides suggestive evidence consistent with all three proposed associative pathways. Heterogeneity analysis further reveals that these effects are stronger in economically developed eastern regions, in counties linked to higher-tier cities, and in secondary and tertiary industries. These findings advance a market-structure perspective on digital development that complements existing welfare-based approaches and offer policy insights for fostering balanced regional development through targeted digital and complementary investments. Full article

Based on the UN SDGs global agenda and China’s national urban renewal strategy, this study highlights the key role of historic architectural decorative patterns in supporting cultural continuity in urban renewal and facilitating heritage building-informed regeneration. Focusing on the sustainable development of urban renewal and heritage building-informed design and regeneration of historic buildings, this study explores the quantification of the cultural memory value of decorative patterns. It integrates a quantitative indicator system into the Gaussian Strategy Enhanced Whale Optimization Algorithm-Back Propagation Neural Network (GSWOA-BP) to enable intelligent pattern generation. First, cultural genes are extracted from architectural heritage, followed by digital quantification and analysis, to generate context-appropriate pattern designs. These are then applied to urban renewal scenarios, ultimately promoting the transmission and revitalization of architectural heritage through digital means. This study provides theoretical support and a technical pathway for the intelligent design of historic architectural decorative patterns, facilitates cultural continuity in heritage building-informed design for urban renewal, and presents a heritage building-informed generative design framework. Full article

Cropland abandonment is increasing in the upper and middle Yangtze River Basin due to complex terrain, urbanization, and labor migration. This threatens regional food security. To address the challenge of monitoring abandonment in fragmented hilly areas, we developed a framework. We integrated machine learning with time-series analysis. We mapped cropland probability using multi-source remote sensing data, random forest, and kernel density estimation, then applied LandTrendr to detect land-use changes and track the spatiotemporal evolution of abandonment from 2000 to 2022. Next, we combined Geodetector and linear regression to identify driving factors. The results show that abandoned cropland exhibited an increasing trend from 2000 to 2010, with an average annual growth rate of 20.4%. From 2010 to 2013, the area of abandoned cropland declined rapidly, decreasing by 44.6%. Between 2013 and 2022, abandoned cropland decreased steadily, with an average annual reduction rate of 24.7%. Spatially, abandonment was clustered in the central mountains and southern hills. Key drivers included distance to towns (DtT), total grain output (GTO), and GDP. Our approach supports cropland management and rural revitalization in regions with complex terrain. Full article

The rural collective property rights system reform (RCPRSR) is a pivotal institutional innovation for revitalizing rural resources, optimizing factor allocation, and advancing urban–rural integration—a core goal of sustainable land use planning. This study evaluates the reform’s impact on county-level urban–rural integration using panel data from 1106 Chinese county-level administrative units during 2013–2020. Treating the staggered rollout of reform pilots as a quasi-natural experiment, we employ a multi-period difference-in-differences approach. The results show that the RCPRSR significantly promotes urban–rural integration, a finding robust to a series of sensitivity checks. The policy effects exhibit marked heterogeneity: the dividends of narrowing the urban–rural development gap are more pronounced in poverty-stricken counties and areas with lower baseline integration levels. Mechanism analysis reveals two pathways—population agglomeration and industrial structure optimization—through which the reform operates, specifically manifested as enhanced county population carrying capacity, accelerated tertiary industry development, and deepened secondary–tertiary industrial integration. These findings provide empirical evidence for optimizing rural property rights reform and advancing sustainable urban–rural development. Full article

Coordinated development between new-type urbanization and rural revitalization is important for sustainable urban–rural transformation and balanced regional development in China. Using panel data for 30 provincial-level units from 2014 to 2023, this study examines the spatiotemporal evolution, dynamic transitions, and external drivers of the coupling coordination degree between the two systems. Spatial Markov chains and an interpretable machine-learning framework are used to identify neighborhood effects, nonlinear relationships, and interaction patterns. The results show four main findings. First, the coupling coordination degree increased over the study period, but clear spatial differences and clustering remained. This suggests that coordinated urban–rural development did not advance evenly across regions. Second, the evolution of coordination shows strong state dependence, and neighborhood context is closely related to transition probabilities. Provinces located in high-coordination neighborhoods were more likely to move to higher levels, while provinces in low-coordination neighborhoods were more likely to remain trapped at lower levels. Third, digital inclusive finance and fiscal self-sufficiency were the most important external factors. Both showed clear nonlinear patterns. Per capita electricity consumption and aging rate also showed heterogeneous relationships at different value ranges. Fourth, the interaction results suggest that higher coordination is more likely to emerge when digital finance, fiscal capacity, openness, human capital, and infrastructure improve together, rather than when only one factor expands on its own. The findings indicate that sustainable urban–rural transformation is shaped by spatial dependence, nonlinear changes, and context-specific factor combinations. Beyond their relevance for more targeted urban–rural coordination and place-based sustainability governance in China, these findings also provide a useful reference for other developing countries seeking to address similar urban–rural development challenges. Full article