Search Results (98)

China’s rural revitalization strategy has entered a new stage of development, in which optimizing the layout of rural settlements constitutes both a critical component and an urgent task for promoting integrated urban–rural development. Important ecological function areas play a vital role in maintaining ecological security; however, research focusing on the evaluation and optimization of rural settlement suitability within these regions remains limited, thereby constraining their sustainable development. Accordingly, this paper selects Shiyan City, situated within the core water source area of China’s South-to-North Water Diversion Project, as a case study. From an ecological perspective, a suitability evaluation system for rural settlements is developed, specifically tailored to important ecological function areas. This system integrates ecological factors including geological hazards, vegetation coverage, soil and water conservation, and soil erosion. Utilizing GIS spatial analysis and the minimum cumulative resistance model, the study assesses the suitability of rural settlements within these important ecological function areas. Furthermore, it proposes corresponding optimization types and strategies for rural settlements in such areas. The findings indicate the following: (1) The rural settlements in the study area demonstrate a “large dispersed settlements and small clustered settlements” distribution pattern, exhibiting an overall high-density agglomeration, though their internal layout remains fragmented and disordered due to geographical and ecological constraints. (2) The spatial comprehensive resistance values in the study area exhibit significant heterogeneity, with a general pattern of lower values in the north and higher values in the south. The region was categorized into five suitability levels: high yield, highly suitable, generally suitable, less suitable and unsuitable. The highly suitable areas, despite their limited spatial extent, support the highest density of rural settlements. In contrast, unsuitable areas occupy a substantially larger proportion of the territory, reaching 46.83%. These areas are strongly constrained by topographic and ecological factors, limiting their potential for development, and the spatial layout of villages requires further optimization, with emphasis placed on ecological conservation and adaptive sustainability. (3) Rural settlements are categorized into four optimized types: Urban–rural integration settlements, primarily located in high yield areas, are incorporated into urban development plans after optimization. Adjusted and improved settlements, mainly in highly suitable areas, enhance service quality and stimulate economic vitality post-optimization. Relocation and renovation settlements, including those in generally suitable and less suitable areas, achieve concentrated living and improved ecological livability after optimization. Restricted development settlements, predominantly in unsuitable areas, focus on ecological conservation and regional ecological security post-optimization. This study integrates ecological function protection factors with spatial optimization zoning for rural settlements in the study area, providing scientific reference for enhancing residential safety and ecological security for rural residents in important ecological function areas. Full article

Given that the increasing non-agricultural conversion of cultivated land (NACCL) endangers food security, studying the spatial and temporal variation characteristics and driving mechanisms of NACCL in Sichuan Province can offer a scientific foundation for developing local farmland preservation measures and controlling further conversion. Guided by the theoretical framework of land use transition, this study utilizes land use datasets spanning multiple periods between 2000 and 2023. Comprehensively considering population scale factors, natural geographical factors, and socioeconomic factors, the county-level annual NACCL rate is calculated. Following this, the dynamic evolution and underlying driving forces of NACCL across 183 counties in Sichuan Province are examined through temporal and spatial dimensions, utilizing analytical tools including Nonparametric Kernel Density Estimation (KDE) and the Geographical Detector model with Optimal Parameters (OPGD). The study finds that: (1) Overall, NACCL in Sichuan Province exhibits phased temporal fluctuations characterized by “expansion—contraction—re-expansion—strict control,” with cultivated land mainly being converted into urban land, and the differences among counties gradually narrowing. (2) In Sichuan Province, the spatial configuration of NACCL is characterized by the expansion of high-value agglomerations alongside the dispersed and stable distribution of low-value areas. (3) Analysis through the OPGD model indicates that urban construction land dominates the NACCL process in Sichuan Province, and the driving dimension evolves from single to synergistic. The findings of this study offer a systematic examination of the spatiotemporal evolution and underlying drivers of NACCL in Sichuan Province. This analysis provides a scientific basis for formulating region-specific farmland protection policies and supports the optimization of territorial spatial planning systems. The results hold significant practical relevance for promoting the sustainable use of cultivated land resources. Full article

Against the backdrop of rapid new urbanisation and the ongoing integration of urban and rural areas, the evolving spatial dynamics between public service facilities and population distribution have increasingly garnered scholarly interest. The present study employs a grid-based spatial unit and a coupling coordination model as a foundation. This model integrates POI data, Baidu heat maps, and other sources of spatial and temporal information. The objective is to explore the dynamic matching pattern of public service facilities and population distribution. The study’s findings are as follows: The population within the core urban area displays a strong propensity for agglomeration during the morning and evening peak hours, thereby forming a highly coordinated public service network characterised by high-density and piecemeal distribution of public service facilities. The population residing within the transition zone between urban and rural areas is commuting in a substantial number, and the relationship between the supply of and demand for facilities demonstrates cyclical fluctuations. Local areas are subject to time-periodic pressure on the supply of and demand for facilities. In rural areas, due to the continuous population outflow and dispersed residence, the layout of service facilities is fragmented, exhibiting the island effect. The study reveals a structural contradiction between traditional homogeneous planning and the gradient difference between urban and rural areas, providing a scientific basis for Shandong Province to promote new urbanisation and rural revitalisation strategies in an integrated manner. Full article

Exploring the regional disparities in and spatiotemporal evolution of the new energy vehicle promotion level (NEVPL) is essential for facilitating low-carbon and environmentally sustainable development. This study employs a multidimensional index system to assess the NEVPL across 31 Chinese provinces from 2017 to 2023, utilizing data on NEV ownership, annual NEV sales, the number of public charging piles, and the vehicle-to-pile ratio. The NEVPL scores were estimated using the Entropy-TOPSIS method. Spatial patterns and the mechanisms of regional disparities were examined using a suite of spatial analytical techniques, including the standard deviation ellipse (SDE), gravity center analysis, Dagum Gini coefficient decomposition, and kernel density estimation. The results reveal three principal findings. First, NEVPL exhibited a sustained upward trend nationwide. The eastern region consistently maintained a leading position, the central and western regions demonstrated steady growth, and the northeastern region remained underdeveloped, leading to an expanding regional gap. Second, spatial distribution transitioned from an early dispersed pattern to a structure characterized by both agglomeration and differentiation. The promotional center gradually shifted toward the southeast, and high-value regions became increasingly isolated, forming island-like clusters. Third, spatial inequality was mainly driven by inter-regional differences, which contributed to over 70 percent of the total variance. The rising intra-regional disparity within the eastern region emerged as the predominant factor widening the national gap. These findings offer empirical evidence to support the refinement of new energy vehicle (NEV) policy frameworks and the promotion of balanced regional development. Full article

Amid ongoing societal development, tourists’ travel behavior patterns have been undergoing substantial transformations, and understanding their evolution has emerged as a key area of scholarly interest. Taking Beijing as a case study, this research aims to uncover the spatiotemporal evolution patterns of tourist flows and their underlying driving mechanisms. Based on digital footprint relational data, a dual-perspective analytical framework—“tourist perception–tourist flow network”—is constructed. By integrating the center-of-gravity model, social network analysis, and regression models, the study systematically examines the dynamic spatial structure of tourist flows in Beijing from 2012 to 2024. The findings reveal that in the post-pandemic period, Beijing tourists place greater emphasis on the cultural connotation and experiential aspects of destinations. The gravitational center of tourist flows remains relatively stable, with core historical and cultural blocks retaining strong appeal, though a slight shift has occurred due to policy influences and emerging attractions. The evolution of the spatial network structure reveals that tourism flows have become more dispersed, while the influence of core scenic spots continues to intensify. Government policy orientation, tourism information retrieval, and the agglomeration of tourism resources significantly promote the structure of tourist flows, whereas the general level of tourism resources exerts no notable influence. These findings offer theoretical insights and practical guidance for the sustainable development and regional coordination of tourism in Beijing, and provide a valuable reference for the spatial restructuring of urban tourism in the post-COVID-19 era. Full article

Urban systems are the spatial carriers of social and economic relations at the regional level, and their relational and structural resilience are key to regional coordination and sustainable development, attracting widespread attention from scholars. In order to analyze the internal relationships of urban agglomerations in underdeveloped mountainous regions and optimize their spatial resource allocation and resilience, this study takes the urban agglomeration of Qiandongnan in China as an example and researches their internal relationships, development potential, and influencing factors based on quantitative methods such as social network analysis. The results show that the urban cluster in Qiandongnan presents “large dispersion and small aggregation” distribution characteristics, with the karst landscape as the main influencing factor; the spatial network exhibits a scale-free morphology with an obvious core–periphery structure, demonstrating moderate stability but poor completeness, weak equilibrium, and low overall resilience; only 15.61% of nodes demonstrate high competitiveness; urban units with functional roles serve as critical network nodes; urban units’ development potential is divided into three tiers (with 47.31% being medium-high), although overall levels remain low; and the development potential, overall network, individual network, and network resilience of urban units are all positively correlated, with economic and transportation development conditions being the main influencing factors. Based on the abovementioned findings, this study proposes a “multi-level resilience promotion path for network structure optimization”, which provides a theoretical basis and optimization control methods for the reconstruction and synergistic development of urban agglomerations. It also serves as a reference for the development planning of urban systems in other underdeveloped mountainous regions. Full article

This study examined urban vulnerability in the three northeastern provinces of China—Heilongjiang, Jilin, and Liaoning—from 2000 to 2020, addressing challenges such as resource shortages, harsh environments, and inadequate education and healthcare. Using the weighted summation method and geographic detector model, this study analyzes the temporal and spatial evolution of urban vulnerability in 34 prefecture-level cities. The results show that overall vulnerability initially increased and then decreased, while economic vulnerability continued to rise. Spatially, vulnerability shifted from weak agglomeration to dispersion by 2020. Key drivers include new fixed assets, local fiscal revenue, and altitude. The findings highlight the need for tailored, coordinated development strategies to reduce urban vulnerability and promote sustainable regional growth, emphasizing the importance of balancing resources, environment, economy, society, and nature. Full article

Resource-exhausted cities face dual crises of economic stagnation and ecological degradation, which is primarily attributable to the inefficient use of industrial land. The redevelopment of industrial land has emerged as a crucial solution to the “resource depletion-urban decline” dilemma. The issue of inefficient industrial land use in resource-exhausted cities is of great significance as it directly impacts both economic development and ecological protection. Therefore, finding effective ways to redevelop this land is essential for the sustainable development of these cities. This research takes Hegang, a representative resource-exhausted city in China, as a case study. A multi-dimensional evaluation framework and an adaptive redevelopment strategy system are constructed in this research. By integrating data related to land use status, land use efficiency, policy constraints, and development potential, a parcel-scale assessment model is established. This model consists of 4 primary indicators and 13 secondary indicators. Through this model, 11.01 km² of inefficient industrial land in the main urban area of Hegang is identified. Standard deviation ellipse and kernel density analysis are employed to reveal the spatial pattern of inefficient land. The results show that the inefficient industrial land in Hegang exhibits a pattern of “overall dispersion with localized agglomeration”. It is found that idle and abandoned land are the dominant types of inefficient industrial land in Hegang’s main urban area, accounting for 69.7% of the total. This finding provides a clear understanding of the nature of the inefficient land use problem in resource-exhausted cities. A strategic framework is proposed, which incorporates classified governance, dynamic restoration, and multi-stakeholder collaboration. This framework offers a governance toolkit with both theoretical depth and practical value for resource-exhausted cities. Breaking the locked relationship between industrial land and resource dependence promotes the deep integration of spatial restructuring and sustainable transformation. The findings of this research provide significant scientific insights for similar cities worldwide to address the challenges they face and achieve harmony between human activities and land use. Future research could focus on further refining the evaluation framework and redevelopment strategies based on different regional characteristics and resource endowments. Full article

This longitudinal study applies decade-spanning socioeconomic indicators (2013–2022) from the Beijing–Tianjin–Hebei urban agglomeration. An integrated analytical framework was developed, merging the super-efficiency slack-based measurement (SBM) methodology with entropic weighting techniques to quantify tourism efficiency and economic development. Subsequent phases employed a multi-method analytical cascade: coupling coordination assessment modeling for system interaction analysis, standard deviation ellipses for spatial dispersion characterization, and Markovian transition matrices for temporal pattern identification. The investigation concludes with evolutionary trajectory projections using gray system forecasting GM(1,1) modeling. The analytical findings reveal the following patterns: (1) Within the Beijing–Tianjin–Hebei metropolitan cluster, tourism efficiency demonstrates a consistent upward trajectory, manifesting spatial differentiation characteristics characterized by a dual-core structure centered on Tianjin and Baoding, with higher values observed in northwestern areas compared to southeastern regions. Concurrently, regional disparities exhibit progressive convergence over temporal progression. (2) The level of economic development in the Beijing–Tianjin–Hebei city cluster has been rising steadily, demonstrating a geospatial distribution of ‘central concentration with peripheral attenuation, with the north-east being better than the southwest’, and the gap between the regional differences has become broader over time. (3) The coupling between tourism efficiency and the level of economic development in the Beijing–Tianjin–Hebei city cluster has generally improved, with Beijing and Tianjin predominantly in a coordinated regime, and some cities in Hebei Province about to shift from dysfunctional to coordinated, and, spatially, the coupling and coordination in northern sectors demonstrate superior performance compared to southern counterparts nationally. (4) The coupling coordination degree of the Beijing–Tianjin–Hebei city cluster in the next eight years is predicted by the gray GM(1,1) prediction model and the overall continuation of the growth trend of the Beijing–Tianjin–Hebei city cluster over the past ten years, thus verifying the importance of the regional integrated policy frameworks in the system integration of the Beijing–Tianjin–Hebei metropolitan system. Full article

Land use change significantly influences landscape pattern adjustments, thereby altering ecosystem functions and service flows, ultimately impacting ecosystem service value (ESV). However, previous studies have often examined the impacts of land use change and landscape patterns on ecosystem services from a one-dimensional perspective, overlooking the complex interactions among these factors. This study proposes a “process–structure–value” response framework and applies it to a case study of the western Sichuan urban agglomeration. Its aim is to identify the spatial and temporal characteristics of land use and landscape pattern evolution. Additionally, it quantitatively evaluates the synergistic effects of these changes on ESV evolution from 2000 to 2020 using a correlation analysis. The results show that, over the past 20 years, the study area experienced a significant expansion of construction land by 184,729.41 hm², leading to the dispersion and fragmentation of arable land, grassland, and waters, resulting in an overall trend of fragmentation and diversification in landscape patterns. The ESV increased by CNY 2.619 billion, primarily due to the increased ESV associated with forest land and waters. This study found that the synergistic effects of land use processes and landscape pattern structures significantly enhanced ESV. The transition from construction land and arable land to forest land and waters notably improved the ESV. Meanwhile, increased landscape diversity and patch connectivity further enhanced the ecosystem service function. Furthermore, the ecological environment of the study area remained vulnerable despite the increased ESV. Overall, the results highlight the significant correlation between changes in land use processes, landscape patterns, and ESV, emphasizing the necessity of integrating the “process–structure–value” framework in future research to comprehensively assess the responses of land use and landscape patterns to ESV, providing a more comprehensive reference for land use planning and policy development. Full article

Rural homestays have emerged as pivotal drivers of rural socioeconomic revitalization, particularly in metropolitan peripheries characterized by intensified urban–rural dynamics. However, their spatiotemporal distribution patterns and underlying mechanisms remain underexplored. This study employs Geodetector and related analytical methods to examine rural homestays in Beijing, aiming to decipher spatial heterogeneity and driving factors. The results reveal a distinct “large-scale dispersion with small-scale clustering” pattern marked by pronounced agglomeration in northern mountainous areas and sparse distributions in southern suburban regions. Temporally, the sector currently exhibits a notable expansion–contraction phase influenced by external factors, alongside spatial centroid migration toward resource-rich zones. Geodetector quantification identifies the proximity to transportation nodes and vegetation coverage as primary spatial determinants, while socioeconomic factors demonstrate comparatively limited influence—contrasting sharply with urban contexts. Rural homestay concentration zones are classified into high-, medium-, and low-intensity categories based on the homestay density, with high-intensity zones leveraging apex advantages of scenic resources, cultural heritage, and infrastructure. These findings underscore the interplay of natural environmental factors, tourism resources, transportation accessibility, and socioeconomic conditions in shaping agglomeration dynamics, providing actionable insights for optimizing spatial planning and promoting sustainable development in rural regions adjacent to megacities. Full article

Rural tourism has become a key driver of rural revitalization in China, contributing to poverty alleviation while also irreversibly altering the spatial evolution of rural settlements. In the ecologically fragile regions of northwest China, the rapid expansion of rural tourism destinations has raised ecological concerns, particularly regarding land resource utilization. Therefore, it is crucial to examine the phenomenon of industrial agglomeration in the evolution of rural tourism within the context of tourism-driven poverty alleviation. This study uses Lanzhou City as a case study and employs nearest neighbor analysis and kernel density estimation to analyze the spatial agglomeration patterns of rural tourism destinations, focusing on agglomeration forms, scales, and patterns. Additionally, it explores the spatial coupling distribution between agglomeration levels and influencing factors. The results show that from 1987 to 2022, the development of rural tourism destinations in Lanzhou City has progressed through several stages, from initial emergence to rapid growth. The form of industrial agglomeration has shifted from a dispersed to a clustered distribution, gradually expanding from urban centers to peripheral areas. The spatial agglomeration follows a multi-core hierarchical point-axial diffusion model, forming multiple core and sub-core agglomeration zones of varying scales. This transformation is primarily driven by geographical factors, transportation accessibility, and the presence of high-quality tourist attractions. However, a comparison of land use changes and ecological vulnerability indices over multiple periods indicates that the industrial agglomeration of rural tourism has led to irregular land use patterns and ecosystem instability. Finally, based on the complex relationship between rural tourism development, industrial agglomeration, and ecological sustainability, this study proposes strategies for the development of rural tourism in Lanzhou City, with the aim of providing valuable insights for the development of rural tourism in ecologically fragile regions of China. Full article

Existing studies on eco-efficiency evaluation often neglect the social and ecological benefits of land use, as well as the spatial heterogeneity in the effects of natural factors. This study aims to establish a systematic eco-efficiency evaluation framework and examine the dynamic impacts of various factors on land use eco-efficiency at the county scale. An evaluation framework integrating economic, ecological, and social outputs was constructed using multi-source remote sensing data. The super-efficiency Slack-Based Measure model and exploratory spatial data analysis method were employed to analyze the land use eco-efficiency and its spatiotemporal characteristics in the Huaihai Economic Zone from 2000 to 2022. Furthermore, the enhanced Geographically and Temporally Weighted Regression model was applied to examine the spatiotemporal heterogeneity of industrial structure, ecological background, land use, and other factors influencing land use eco-efficiency. The results indicated the following: (1) The average land use eco-efficiency in the Huaihai Economic Zone followed a pronounced “U-shaped” pattern, initially decreasing before increasing. At the county level, efficiency values generally showed an upward trend, with municipal districts or county-level cities accounting for more than half of the areas. (2) A weak positive spatial agglomeration of land use eco-efficiency was observed at the county level. High-efficiency areas shifted from a dispersed pattern to a “T-shaped” spatial distribution, while low-efficiency areas gradually converged toward the southern regions, evolving from an “H-shaped” cluster. (3) The influence of industrial structure, urbanization, environmental regulation, ecological factors, and land use on ecological efficiency exhibited clear spatial and temporal heterogeneity. The multi-dimensional land use eco-efficiency evaluation offers an effective tool for comprehensively assessing ecological conservation, environmental sustainability, and socio-economic development. It also provides valuable insights for improving land use eco-efficiency at the county level. Full article

With the expansion of urbanization in China, ecological environments are becoming more and more prominent. Uncovering driving factors and ways of regulating ecosystem health has become a hot topic for regional sustainable development. This paper adopted the improved vigor–organization–resilience service (VORS) model to diagnose the regional ecosystem health status in Guangxi from 2000 to 2020 and verify the main factors affecting ecosystem health. Considering the influencing factors (including vegetation, terrain, climate and human activities), the mechanism of driving factors associated with regional ecosystem health was analyzed by using a geographic detector (GD), a multiscale geographically weighted regression model (MGWR), and the XGBOOTS-SHAP model. The results show that the spatial distribution of ecosystem health is characterized by low values in the central region and high values in the northern and eastern regions with higher elevations from 2000 to 2020. The spatial agglomeration evolution changes from agglomeration to dispersion, and the regional urbanization distribution and evolution are consistent. The interaction of driving factors for ecosystem health and vegetation is enhanced significantly, while the interaction of climate factors is relatively weak. And most of the impacts of human activities on the ecological environment are negative. The vegetation factor has a dominant positive effect on ecosystem health, while human activity elements have a weak negative effect on ecosystem health. Meanwhile, climate factors are complex and changeable, and their impacts on ecosystem health are changeable, leading to corresponding changes in other factors. This study provides scientific reference for the harmonious and sustainable development of humans and nature in southern China. Full article

The identification of the multifunctional combination of production–living–ecological spaces (PLES) in urban agglomerations, particularly in urban cores and peri–urban areas, is a critical issue in the urbanization process. This study, using the Hohhot–Baotou–Ordos–Yulin (HBOY) urban agglomeration, a key node in China’s “Two Horizontals and Three Verticals” urbanization strategy, proposes a hexagonal grid–based PLES quantification framework using POI data. A three–level POI classification system was developed, with functional element weights determined via the Analytic Hierarchy Process and public perception surveys. The framework quantifies PLES within hexagonal grids and analyzes its patterns and functional coupling mechanisms using spatial overlay, Average Nearest Neighbor Index (ANNI), kernel density analysis, and spatial autocorrelation analysis. The following results were obtained. (1) PLES classification accuracy reached 90.83%, confirming the reliability of the method. (2) The HBOY urban agglomeration exhibits a dominant production space (40.84%), balanced living and ecological spaces (29.37% and 29.36%, respectively), and a severe shortage of mixed spaces (0.43%). (3) Production and living spaces show significant clustering ($ANNI$ ≤ 0.581), mixed spaces follow ($ANNI$ = 0.660), and ecological spaces are relatively evenly distributed ($ANNI$ = 0.870). (4) The spatial distribution patterns show that production and living spaces exhibit “core concentration with peripheral dispersion”, ecological spaces show “block concentration with point–like distribution”, and mixed spaces show “point–like dispersion”. (5) Production and living spaces exhibit strong spatial autocorrelation ($Moran’s I$ > 0.7) and the highest spatial correlation ($Bivariate Moran’s I$ = 0.692), while the spatial correlation with ecological spaces is weakest ($Bivariate Moran’s I$ = 0.150). The proposed PLES identification framework, with its efficiency and dynamic updating potential, provides an innovative approach to urban spatial governance under the global Sustainable Development Goals. The findings offer integrated decision–making support for spatial diagnosis and functional regulation in the ecologically vulnerable areas of northwest China’s new urbanization. Full article