Search Results (205)

Historic and cultural towns in China are crucial carriers of vernacular heritage, yet many unlisted historic buildings remain highly vulnerable to urbanization and fragmented governance. This study takes Xiangzhu Town in Zhejiang Province as a case study and develops a multidimensional evaluation framework—integrating value, morphology, and risk—to identify conservation priorities and guide adaptive reuse. The results highlight three key findings: (1) a spatial pattern of “core preservation and peripheral renewal,” with historical and artistic values concentrated in the core, scientific value declining outward, and functional diversity emerging at the periphery; (2) a morphological structure characterized by “macro-coherence and micro-diversity,” as revealed by balanced global connectivity and localized hotspots in space syntax analysis; and (3) differentiated building risks, where most assets are low to medium risk, but some high-value ancestral halls show accelerated deterioration requiring urgent action. Based on these insights, a collaborative framework of “graded management–classified guidance–zoned response” is proposed to align systematic restoration with community-driven revitalization. This study demonstrates the effectiveness of the value–morphology–risk approach for small historic towns, offering a replicable tool for differentiated heritage conservation and sustainable urban–rural transition. Full article

Under the accelerating urbanization, the evolution of public spaces in traditional villages increasingly diverges from social needs. The top-down governance model fails to adequately address the actual needs of indigenous residents, highlighting the necessity for structural analysis and optimization from an integrated physical–social perspective. This study, focusing on traditional villages in Beijing’s Fangshan District, constructs a three-tier model (village-street-node) by integrating Social Network Analysis (SNA) and space syntax theory. It analyzes the relationship between the accessibility and traffic potentiality of linear and point-based public spaces across the region and the frequency/scope of villagers’ daily activities. The findings reveal that within the linear belt-like spatial layout of traditional villages in western Beijing, historical spaces situated within the core residential areas demonstrate high stability and integrity, serving as primary venues for villagers’ daily activities. In contrast, historical spaces located at the periphery of settlements suffer from low utilization rates and even exhibit social segregation. Additionally, deficiencies in spatial choice, intermediary nodes, and functionality within settlements are identified as key factors contributing to social segregation in public spaces. Finally, the study proposes targeted policy recommendations for the preservation and sustainable development of traditional villages. Full article

Traditional villages, as forms of significant cultural heritage, have garnered global scholarly attention. This study focuses on the traditional village clusters in Qiandongnan Prefecture, a UNESCO World Heritage site, which includes 415 nationally designated villages. Based on spatial relational analysis and other methods, this study explores the intrinsic relationship between the spatial connectivity of traditional village clusters and their development. The findings are as follows: 1. The spatial distribution of villages exhibits a “dense core, sparse periphery, and localized jumps” pattern. 2. There are five types of development, with over 70% based on agriculture and low industrial differentiation. 3. The spatial connectivity network is clustered, with overall connectivity but a lack of internal coherence, forming a hierarchical network constrained by geography. 4. The spatial connectivity is relatively unstable, highly vulnerable, and exhibits a clear core-periphery structure, where geographical proximity determines basic connections and functional uniqueness drives value-added connections. 5. The overall development potential of these villages is assessed as medium to low. Enhancing network connectivity can foster comprehensive development, and adjusting spatial connectivity could improve its development potential. The study proposes a two-tiered optimization strategy based on the intrinsic connectivity and development characteristics of these villages, providing insights into the development of traditional villages in other regions and cultural heritage areas worldwide. Full article

While core-periphery (CP) structures are a fundamental property of many social networks, their influence on information diffusion remains insufficiently understood, especially for complex contagions that require social reinforcement. To address this research gap, this paper investigates the role of core-periphery (CP) structure on information diffusion using the Maki-Thompson model. Both simple contagion and complex contagion scenarios are analyzed through extensive numerical simulations and theoretical analysis. Our results reveal several key insights. First, a stronger CP structure facilitates broader information dissemination compared to a weaker core-periphery structure. Second, strong CP networks are particularly vulnerable to targeted interventions; immunizing core nodes is highly effective at impeding diffusion, especially for simple and small-k complex contagions. Third, counterintuitively, CP structure significantly hinders the spread of complex contagions, requiring a higher critical threshold for a global outbreak compared to equivalent random networks. These findings can provide valuable insights into the nuanced role of network topology in shaping information propagation, highlighting that CP structure can both facilitate and hinder diffusion depending on contagion type. Full article

Amid demographic restructuring, analyzing the dynamic interplay between public services and population development is vital for advancing coordinated regional development in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA). This study developed an integrated evaluation framework, applying relative development indices, coupling coordination models, and obstacle analysis to examine the spatiotemporal evolution, coordination dynamics, and key constraints of the public service system and population system development from 2012 to 2023. The findings reveal the following: (1) Coordinated development policies have significantly boosted public service levels in cities near Beijing, whereas growth in Beijing and Tianjin has slowed. (2) Although overall coupling coordination across the BTHUA has improved, a marked core–periphery disparity persists. Beijing maintains high-level coordination, while most Hebei cities remain at marginal coordination levels. (3) The constraints on coordinated development vary substantially: Beijing primarily encounters structural challenges in population dynamics, whereas Tianjin and Hebei face basic infrastructural deficiencies. The study recommends developing a public service delivery system aligned with evolving demographic trends and proposes targeted strategies to optimize regional service structures based on each city’s core challenges. Full article

In the context of China’s “double carbon” goals, examining the spatial–temporal characteristics and influencing factors of the synergistic effect of pollution control and carbon reduction (SEPCR) in the Chengdu–Chongqing region (CCR) is crucial for advancing both air pollution (AP) control and carbon emissions (CE) mitigation. This study uses data on AP and CE from 2007 to 2022 and employs the coupling coordination degree (CCD) model, spatial autocorrelation analysis, and kernel density estimation to investigate the spatial–temporal distribution and dynamic evolution of the CCD between AP and CE in the CCR. Additionally, the Tobit regression model is applied to identify the key factors influencing this synergy. The results indicate that (1) during the study period, the air pollutant equivalents (APE) in the CCR showed a declining trend, while CE continued to increase; (2) the overall level of coupling coordination remained low, exhibiting an evolutionary pattern of initial increase, subsequent decrease, and then recovery, with synergistic effects showing slight improvement but significant fluctuations; (3) the SEPCR in the CCR was generally dispersed, exhibiting no significant spatial autocorrelation. A “core–periphery” structure emerged, with Chongqing and Chengdu as the core and peripheral cities forming low-value zones. Low–low clusters indicative of a “synergy poverty trap” also appeared; (4) economic development (PGDP), openness level (OP), and environmental regulation intensity (ER) are significant positive drivers, while urbanization rate (UR), industrial structure upgrading (IS), and energy consumption intensity (EI) exert significant negative impacts. Full article

Urban commemorative landscapes serve as vital components of a city’s cultural expression. Employing a two-dimensional “physical-perceptual” accessibility evaluation framework, this study conducted a systematic analysis of the spatial distribution characteristics and accessibility of 124 commemorative landscapes in Nanjing, and investigated the factors influencing their accessibility. The analysis revealed four key findings: (1) A pronounced “core-periphery” pattern was identified, characterized by high-density, evenly distributed clusters in central districts that contrast with sparse, scattered layouts in outer suburbs. (2) Weighting analysis via the entropy method indicated that perceived accessibility (53.96%) exerted a slightly greater influence on composite accessibility than spatial accessibility (46.04%). (3) Modern commemorative landscapes in the main urban areas exhibited strong correlations with road network density and high public perception, and their comprehensive accessibility is significantly better than that of the remote suburban areas. Significant disparities in accessibility were observed among different types of modern commemorative landscapes. The comprehensive accessibility of memorial facilities was found to be the highest, attributable to their balanced spatial distribution and the fact that most of them are distributed in the densely populated main urban areas. (4) Key factors influencing accessibility were identified as attraction carrying capacity, regional population density, and elevation. This study aims to provide a reference for the comprehensive quantitative evaluation of urban commemorative landscapes, thereby promoting the coordinated development of historical space preservation and cultural resource utilization. Full article

This study addresses the limitations of traditional nighttime light remote sensing data in ground object feature recognition and carbon emission monitoring by proposing a fusion framework based on Nonsubsampled Contourlet Transform (NSCT) and Intensity-Hue-Saturation (IHS). This framework successfully generates a high-resolution color nighttime light remote sensing imagery (color-NLRSI) dataset. Focusing on Guangzhou, an important city in the Guangdong-Hong Kong-Macao Greater Bay Area, the study systematically analyzes the spatiotemporal coupling mechanism between urban form evolution and carbon footprint by integrating multiple remote sensing data sources and socio-economic statistical information. Key findings include: (i) The color-NLRSI dataset outperforms traditional NPP-VIIRS data in built-up area extraction, providing more accurate spatial information by refining urban boundary recognition logic. (ii) Spatial correlation analysis reveals a remarkably strong positive relationship between built-up area expansion and carbon emissions, with the correlation coefficient for numerous districts exceeding 0.9. High-density built-up areas are strongly associated with a carbon lock-in effect, hindering low-carbon transformation efficiency. (iii) Geographically Weighted Regression analysis demonstrates that in population-polarized regions, the impact coefficient of built-up area expansion on carbon emissions is notably high at 0.961. This factor’s association (22.43%) surpasses economic development (10.34%) and urbanization rate (14.91%). The established “data fusion—dynamic monitoring—mechanism analysis” technical system, which generates a novel high-resolution color-NLRSI dataset and reveals a distinct ‘core-periphery’ heterogeneity pattern in Guangzhou, demonstrating that urban expansion is the dominant driver of carbon emissions. This approach offers a scientific basis for tailored urban low-carbon development strategies, spatial optimization, and enhanced precision in carbon emission monitoring. Full article

Historic districts face persistent challenges balancing heritage preservation and urban vitality due to fragmented governance and static conservation. This study develops a multi-source data-driven evaluation system coupling spatial quality and urban vitality, focusing on China’s Republican-era historic districts with Nanjing’s Yihe Road as a case study. Integrating field surveys and big data (street view imagery, POI data, heatmaps), we quantitatively assess environmental quality and vitality. Key findings reveal a distinct spatial pattern: “high-quality concentration internally” and “high-vitality concentration externally,” where core areas exhibit functional homogenization and low vitality, while peripheries show high pedestrian activity but lack spatial coherence. Clustering analysis categorizes streets into four types based on quality and vitality levels, highlighting contradictions between static conservation and adaptive reuse. The study deepens understanding of spatial differentiation mechanisms and reveals universal patterns for sustainable development strategies. A multi-tiered governance strategy is proposed: urban-level flexible governance harmonizes cross-departmental policies via adaptive planning, district-level differentiated governance activates spatial value through functional reorganization, and street-level fine-grained management prioritizes incremental micro-renewal. The research underscores the critical need to balance heritage preservation with contemporary functional demands during urban renewal, offering a practical framework to resolve spatial conflicts and reconcile conservation with regeneration. Full article

The sustainability of regional development in Europe is deeply influenced by heterogeneous globalization processes, yet the divergent long-term trajectories of these processes remain poorly quantified, hindering the design of targeted policies. This study aims to identify and characterize clusters of European countries with similar patterns of overall globalization development in order to assess implications for sustainable and cohesive growth. A novel clustering algorithm is developed that integrates Dynamic Time Warping with k-means to account for temporal misalignments and capture similarities in development dynamics rather than just static levels. Analysis based on the KOF Globalization Index for 40 countries reveals four distinct clusters: highly globalized and stable Western European economies, converging Central and Eastern European countries, microstates with niche integration models, and a peripheral group of Southeastern European nations facing significant challenges. The results demonstrate a persistent core–periphery divergence in globalization paths across Europe. This divergence presents a major obstacle to achieving territorial cohesion and equitable sustainable development outcomes. Methodologically, this study provides a robust framework for analyzing longitudinal socioeconomic processes. The main conclusion is that a one-size-fits-all EU cohesion policy is insufficient; instead, cluster-specific strategies are necessary in order to mitigate regional inequalities, enhance resilience, and ensure that the benefits of globalization contribute to the goals of sustainable development. The findings offer a quantitative basis for such targeted policy interventions. Full article

Numerous well-preserved ancestral halls dating back to the Ming and Qing dynasties are found throughout Southern Anhui, China. Among the architectural elements in these ancestral halls, the “Xuan” plays a significant decorative role. Nevertheless, scholarly research on the “Xuan” in this region remains limited, particularly in the context of the temporal and regional evolution of its decorative art. This study examines the decorative characteristics and spatiotemporal evolution of the front Xuan of 115 ancestral halls across Southern Anhui belonging to the Ming and Qing periods. Using field surveys, a combination of qualitative and quantitative analyses, and ArcGIS kernel density analysis, this study identifies key trends in Xuan evolution. Specifically, the findings indicate that the Chuanpeng Xuan emerged as the predominant style, replacing the earlier Renzi Xuan after the mid-Ming period. By the late Qing period, the primary structural components of the Xuan showed increasing standardization, while accessory elements showed notable diversification. During the commercial boom of the mid-Qing era, flood-dragon carvings and S-shaped short beams became especially prevalent. Spatially, kernel density analysis demonstrated a core-periphery distribution pattern: mainstream styles were concentrated in central counties, whereas a greater variety of stylistic combinations and niche forms emerged in border regions. These evolutionary patterns reflect the broader sociohistorical dynamics of this period, including ritual reforms during the Ming dynasty, the patronage of Huizhou merchants, innovations in carving tools, and wartime resource constraints. These findings provide diagnostic criteria for dating unidentified ancestral halls and offer a practical reference for the conservation of architectural heritage. Full article

When considering an urban agglomeration as a unit, promoting the coupling and coordination of the land price gradient and industrial gradient is crucial for achieving regional integrated development. We selected the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) as a case study; constructed a three-dimensional analytical framework involving static coupling, dynamic coupling, and spatial matching; theoretically clarified the coupling mechanism between the land price gradient and industrial gradient; and systematically assessed their spatial-temporal patterns and coupling characteristics. The results indicate that from 2012 to 2022, both the land price gradient and industrial gradient within the BTHUA exhibited a “core-periphery” spatial distribution, gradually forming an over-all pattern of “one core, multiple nodes, and multi-level rings.” For the Beijing–Tianjin–Hebei urban agglomeration, overall static coupling and spatial matching exhibit an evolutionary trajectory of “first rising, then declining.” By contrast, dynamic coupling remains relatively weak, exhibiting a corridor-shaped distribution along core and sub-core cities. All three indicators consistently show that core cities outperform peripheral cities. Nonlinear mechanism analysis based on the gradient boosting decision tree method showed that “second-nature” factors like economic development and public utilities significantly promote multidimensional coupling. Conversely, “first-nature” factors, such as geographic conditions, have limited impacts with threshold effects; surpassing these thresholds results in inhibitory effects. Based on the research findings, this study proposes that regional integration should serve as the guiding principle, emphasizing the cultivation of regional development corridors, the implementation of flexible and functionally aligned land supply policies, the strengthening of land use performance audits, and the reorientation of fiscal and financial policies toward structural and qualitative improvements. These measures can provide valuable references for promoting coordinated industrial development and balanced land allocation in urban agglomerations. Full article

In the contemporary economic landscape shaped by globalization and digital transformation, patent-intensive industries have emerged as critical engines for enhancing national competitiveness. This study analyzed 98,464 collaborative patent application records (2012–2023) from listed companies in patent-intensive sectors, sourced from the China National Intellectual Property Administration (CNIPA) database. Through kernel density estimation, social network analysis, and community detection techniques, we examined the evolutionary trajectories of innovation networks and spatial patterns within these industrial clusters. Our findings indicate a notable spatial agglomeration trend in patent-intensive industries, exhibiting a prominent “core-periphery” structural feature. The core nodes of this cluster network closely align with economically developed regions, and the network structure has gradually shifted from a triangular framework supported by Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta to a diversified multilateral framework. Moreover, the community structure of the collaborative network within China’s patent-intensive industrial clusters exhibits distinct characteristics driven by technological relevance and strategic synergy, rather than strictly adhering to the principle of geographical proximity. These discoveries not only enrich the application of innovation network theory in the specific context of China, but also provide valuable guidance for cluster enterprises in selecting partners and achieving collaborative innovation. Full article

Harmonizing economic growth and carbon emissions is key to reaching the “dual carbon” targets. This research centers on the seven key urban agglomerations within the Yellow River Basin (YRB) and establishes an integrated research framework of decoupling effect quantification–spatial association recognition–driving factor analysis. By combining the Tapio decoupling model, a modified gravity model, social network analysis (SNA), and the Logarithmic Mean Divisia Index (LMDI) method, the study systematically evaluates the decoupling states, spatial association structure, and driving mechanisms between regional carbon emissions and economic growth from 2001 to 2020. The results show that: (1) All seven urban agglomerations exhibit a simultaneous upward trend in both carbon emissions and GDP, but significant regional disparities exist, with some agglomerations demonstrating a green growth pattern where economic growth outpaces carbon emissions. (2) Weak decoupling is the predominant type among urban agglomerations and their constituent cities in the YRB. Notably, some regions have regressed to growing connection or growing negative decoupling during 2016–2020. (3) The spatial network of carbon emission decoupling effects exhibits a core-periphery structure characterized by stronger eastern regions and weaker western regions, with the Shandong Peninsula and Guanzhong Plain urban agglomerations serving as core nodes for regional linkage. (4) Per capita GDP and technological level play a dominant role in promoting decoupling, while energy intensity and the population carrying intensity of the real economy are the primary inhibiting factors; the impact of industrial structure shows an unstable direction. Grounded in these findings, this study formulates differentiated carbon reduction pathways tailored to regional heterogeneity, providing theoretical insights and actionable guidance to facilitate the low-carbon transition and coordinated governance of urban agglomerations. Full article

Climate change has emerged as a critical global issue. Land-use/cover change (LUCC) plays a pivotal role in influencing terrestrial ecosystem carbon cycles and further regulates carbon emission intensity by reshaping the spatial characteristics of landscape patterns. Taking 300 Chinese cities as the study area, an analytical framework encompassing carbon emission accounting, regional land-use landscape pattern analysis, spatiotemporal correlation between landscape patterns and carbon emissions, and economic “core-periphery” disparities was presented. The land-use carbon emissions and landscape pattern indices of each city from 2005 to 2020 were calculated, and the geographically weighted regression (GWR) model was employed to examine the impact of land-use landscape pattern changes on carbon emissions from an urban perspective. Furthermore, the cities were categorized into developed and underdeveloped groups based on the median per capita GDP to compare how economic development levels moderate this impact mechanism. The results indicate that the relationship between landscape patterns and carbon emissions exhibits significant spatial heterogeneity, highlighting the complexity of the influence of land-use morphology on carbon emissions. Sustainable land-use strategies must account for regional disparities in economic levels, planning capacity, and administrative characteristics rather than pursuing a uniform urban form. Economic development significantly moderates the carbon mitigation effects of landscape patterns through its influence on spatial governance capacity, leading to pronounced differences between cities at varying development levels. Moving forward, regionally tailored approaches that integrate landscape optimization with industrial transformation and ecological conservation should be prioritized to provide spatial solutions for achieving the carbon peaking and carbon neutrality goals. Full article