Search Results (1,172)

This study introduces the Historic Urban Landscape (HUL) approach into a rural setting and conducts a case study of Huaqiu Village. By integrating spatial analysis techniques, unmanned vehicle aerial photography, field surveys, and multitemporal data from 2000 to 2023, this study analyzed the heritage value of traditional villages and explored a rural-adaptable pathway for HUL implementation. Findings showed: 1. Based on the temporal and spatial evaluation analysis logic of landscapes under the HUL framework, spatial patterns of the village, such as vegetation growth and reduced in water bodies, have been quantitatively identified, revealing the interaction patterns of a complex ecosystem. 2. Following HUL’s holistic understanding of heritage value, the three-dimensional value characteristics of the village (landscape, function, and spirit) are clarified. 3. By implementing the community participation mechanism of HUL, through villager-led inheritance of intangible cultural heritage and joint formulation of conservation conventions, the living continuity of heritage has been realized. The HUL approach shows remarkable adaptability, with prominent achievements in dynamic-layered protection and community participation. This study breaks through the urban bias of the HUL approach, enriches understanding of rural heritage, and provides a practical paradigm for promoting sustainable development of similar villages. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

Tourism villages represent a key breakthrough for achieving rural revitalization and integrated urban–rural development. By analyzing the spatial patterns of tourism villages in the Great Mount Huang district and their influencing factors, this study provides a scientific foundation for the high-quality development of rural tourism and for the enhancement and sustainable management of regional leisure tourism systems. Using methods such as the nearest neighbor index, kernel density, geographic detector, and geographically weighted regression analysis, the results reveal: (1) the spatial distribution of tourism villages in the Great Mount Huang district exhibits significant clustering and unevenness, forming a spatial pattern characterized by “one cluster, two cores, and three points”; Anqing City shows the most concentrated and uneven distribution of tourism villages; (2) the number of Grade A tourist attractions and cultural resources are dominant factors; tourism culture and natural environment are the most influential dimensions affecting the spatial distribution of tourism villages in the Great Mount Huang district; the development of rural tourism requires consideration of multiple aspects and factors, emphasizing multidimensional coordination; (3) the average slope and the number of Grade A tourist attractions exhibit the greatest spatial variability, while the average elevation shows the lowest spatial variability; average elevation, average slope, per capita disposable income, the number of Grade A tourist attractions, and cultural resources all show a positive correlation with the distribution of tourism villages. Full article

Exploring the factors and mechanisms influencing farmers’ participation behavior in formal financial markets is of great significance for improving the rural financial service system and comprehensively promoting the development of rural inclusive finance. Based on the data from the 2020 China Rural Revitalization Survey (CRRS), this paper explores the impact and mechanism of digital skills on farmers’ participation in formal financial markets through the theories of feasibility information, social capital, and technology acceptance. The research results show that digital skills significantly promote farmers’ likelihood and extent of participation in formal financial markets, including stocks, bonds, and wealth management products. This is because digital skills enhance farmers’ information acquisition and online transaction capabilities and broaden their social networks. Heterogeneity analysis reveals that digital skills exert a greater influence on both the likelihood and extent of participation of farmers with lower educational level, farmers in the middle-aged and elderly cohorts, and farmers with low income in formal financial markets. Further research reveals that participating in formal financial markets can significantly increase farmers’ annual income. Therefore, training should be strengthened to enhance farmers’ digital skills. Open information platforms should be established to broaden channels, gradually enabling farmers to freely acquire information, reducing the cost of maintaining social networks for farmers, and improving the convenience of farmers’ online transactions. In addition, efforts should be made to promote the development of inclusive finance, focus on the differentiation issues of farmers in information and wealth, and thereby more widely enhance farmers’ participation in formal financial markets. Full article

This study aims to investigate the multifaceted effects of e-commerce-led digital chain engagement on the income of Chinese crop farmers, distinguishing between participation status and participation depth. The analysis uses data from the China Rural Revitalization Survey (CRRS) conducted in 2020, with 1815 crop-farming households as the sample. To estimate causal effects, treatment effect models and instrumental variable strategies are employed. Results show that e-commerce-led digital chain participation significantly enhances household income, and deeper digital chain engagement amplifies this effect. Mechanism analyses reveal that deep engagement promotes income through multiple channels, including improved digital preparedness, enhanced product sales performance, and increased participation in digital financial services. Heterogeneity analysis indicates that the income gains mainly stem from agricultural revenue, and are more pronounced among cooperative members, though marginal benefits from deeper engagement appear limited. Quantile regressions uncover a pronounced Matthew effect: higher-income households benefit more from digital chain embedding, thereby widening the income gap. Moreover, e-commerce-led digital chain participation also improves farmers’ income satisfaction and their expectations of income sustainability. These findings suggest that policymakers should not only promote basic e-commerce participation but also implement targeted support for deep digital chain embedding to foster inclusive growth while mitigating the Matthew effect. By shifting the focus from binary participation to embedded intensity, this study provides new insights into how e-commerce-led digital transformation shapes rural income structures, offering theoretical and empirical contributions to the literature on agricultural modernization and digital inclusion. Full article

Open-pit mining often induces geological hazards such as slope instability, surface subsidence, and ground fissures. To support sustainable mine operations and safety, high-resolution monitoring and mechanism-based interpretation are essential tools for early warning, risk management, and compliant reclamation. This study focuses on the Baorixile open-pit coal mine in Inner Mongolia, China, where 48 Sentinel-1 images acquired between 3 March 2017 and 23 April 2021 were processed using the Small-Baseline Subset and Distributed-Scatterer Interferometric Synthetic Aperture Radar (SBAS-DS-InSAR) technique to obtain dense and reliable time-series deformation. Furthermore, a Trend–Periodic–Residual Subspace-Constrained Regression (TPRSCR) method was developed to decompose the deformation signals into long-term trends, seasonal and annual components, and residual anomalies. By introducing Distributed-Scatterer (DS) phase optimization, the monitoring density in low-coherence regions increased from 1055 to 338,555 points (approximately 321-fold increase). Deformation measurements at common points showed high consistency ($R^2$ = 0.97, regression slope = 0.88; mean rate difference = −0.093 mm/yr, standard deviation = 3.28 mm/yr), confirming the reliability of the results. Two major deformation zones were identified: one linked to ground compaction caused by transportation activities, and the other associated with minor subsidence from pre-mining site preparation. In addition, the deformation field exhibits a superimposed pattern of persistent subsidence and pronounced seasonality. TPRSCR results indicate that long-term trend rates range from −14.03 to 14.22 mm/yr, with a maximum periodic amplitude of 40 mm. Compared with the Seasonal-Trend decomposition using LOESS (STL), TPRSCR effectively suppressed “periodic leakage into trend” and reduced RMSEs of total, trend, and periodic components by 48.96%, 93.33%, and 89.71%, respectively. Correlation analysis with meteorological data revealed that periodic deformation is strongly controlled by precipitation and temperature, with an approximately 34-day lag relative to the temperature cycle. The proposed “monitoring–decomposition–interpretation” framework turns InSAR-derived deformation into sustainability indicators that enhance deformation characterization and guide early warning, targeted upkeep, climate-aware drainage, and reclamation. These metrics reduce downtime and resource-intensive repairs and inform integrated risk management in open-pit mining. Full article

With the rise in rural tourism, public space use has become more complex, causing significant weekday-weekend vitality imbalances. However, the factors shaping these dynamics in traditional villages remain unclear. This study uses Wi-Fi sensing method to analyze vitality variations across weekdays and weekends, and it develops a 13-metric evaluation framework to examine how built environment factors, from both internal and external dimensions, differentially influence the vitality of public spaces in traditional villages across various time periods. Using 17 public spaces in Yantou Village, Lishui, China, as a case, it finds: (1) Historical Element Proximity consistently and significantly drives public space vitality across all periods; (2) Leisure Facility Count and Decorative Element Count demonstrate strong positive effects during weekend morning peaks. (3) Retail Facility Count significantly reduces vitality during weekend morning peak but enhances it during midday off-peak, whereas Street Vendor Count shows the opposite pattern—increasing vitality in morning peak and decreasing it in midday off-peak. Using Wi-Fi sensing’s high-resolution, real-time, and non-invasive capabilities, this study provides a scientific method to accurately assess the variations in public space vitality and their impact factors between weekdays and weekends in traditional villages, offering technical support for enhancing public space vitality and sustainably revitalizing rural heritage. Full article

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

Egg yolk IgY antibody has significant application potential in aquaculture as a form of passive immunotherapy against various bacterial infections owing to its capacity for large-scale and cost-effective production. In this research, laying hens were immunized with live or inactivated Aeromonas hydrophila to produce IgY antibodies. Following this, experiments were carried out to assess the passive immune protection rates of the two types of IgY antibodies when used to immunize goldfish (Carassius auratus), which were then infected with A. hydrophila or Aeromonas veronii. ELISA experiments were conducted to demonstrate the interaction between the IgY antibodies and the bacteria. The kidneys of C. auratus were coated on a Luria–Bertani (LB) medium to evaluate bacterial content. The leukocyte phagocytosis was detected by a cell phagocytosis assay. The serum of C. auratus was used to assess the expression of antioxidant factors, and a qRT-PCR was conducted to evaluate the mRNA expression of inflammatory factors in visceral tissue. Furthermore, histopathology and immunofluorescence analysis were performed to evaluate the structural integrity, apoptosis, and DNA damage of visceral tissues. The results indicated that the live or inactivated A. hydrophila IgY antibodies exhibited passive immune protection rates against A. hydrophila and A. veronii and could recognize these two bacteria in vitro. Additionally, these two IgY improved the phagocytic ability of leukocytes, diminished renal bacterial concentration, and decreased the levels of antioxidant factors and mRNA expression of inflammatory factors. Meanwhile, the two IgY antibodies did not cause any pathology of the kidney, spleen, and intestine, and decreased the levels of DNA damage factor (γH2A.X) and cell apoptosis factor (p53) in renal tissue. Therefore, live and inactivated A. hydrophila IgY antibodies can resist bacterial infections, with live bacteria IgY providing greater protection than inactivated bacteria IgY. Further, A. hydrophila is an aquatic pathogen that causes minimal damage to laying hens, and the immunity of live A. hydrophila conforms to animal welfare. Altogether, live A. hydrophila IgY antibody can serve as a polyvalent passive immune vaccine candidate in aquaculture. Full article

In recent years, China’s economic and social development has faced challenges such as urban-rural imbalance and ecological pressure. Digital inclusive finance and ecological resilience have become key concerns in academia and policymaking. This study empirically examines whether digital inclusive finance can enhance ecological resilience and its underlying mechanisms, drawing on quantitative evidence from provincial panel data covering 2011–2020. By providing robust empirical results, it contributes to understanding the role of digital finance in supporting high-quality growth and ecological civilization. While the findings align with national strategies such as the “dual carbon” goal and rural revitalization, the study’s primary contribution lies in advancing interdisciplinary exploration through rigorous evidence rather than solely at the policy level. By constructing a double fixed effects model and panel data from 30 Chinese provinces (2011–2020), the study finds that digital inclusive finance significantly enhances ecological resilience, both directly and indirectly through channels such as environmental regulation, artificial intelligence development, and green credit. Moreover, its ecological impact is moderated by regional economic levels and digital infrastructure, with stronger effects observed in eastern and digitally advanced regions. In summary, this study reveals the mechanisms through which digital inclusive finance promotes ecological resilience, offering a theoretical foundation and practical guidance for policy formulation. Its key contribution lies in systematically analyzing the link between digital inclusive finance and ecological resilience, enriching the theoretical framework and providing data support for policy optimization and financial institutions’ strategic adjustments. Future efforts should focus on strengthening policy coordination to enhance the ecological role of digital finance, promoting financial innovation to support resilience, and advancing regional coordination to narrow the digital divide and achieve shared ecological protection. Full article

China and Italy, both ancient civilizations, have numerous traditional villages that bear witness to history and support the transmission of cultural heritage. However, these villages face challenges such as homogenized development, population outflow, and disruptions in cultural continuity. While both Chinese and Italian traditional villages have received considerable scholarly attention, their comparative study remains relatively limited, leaving the transferability of respective solutions across different legal, heritage and planning contexts to be fully explored. This study aims to adapt and transfer Italy’s contiguous protection, integrated operation, national park designation, and community partnership policies to China in order to establish a comprehensive mechanism for preservation and revitalization of traditional villages. A cross-case study of Cinque Terre (Italy) and Jiande (China), incorporating on-site mapping, governance analysis, and interviews, reveals that Italy’s integrated community-based approach markedly outperforms China’s fragmented state-led model in sustaining population, culture and tourism quality. These findings provide a globally replicable paradigm for traditional village preservation. Full article

The escalating consequences of human activities and global warming have markedly increased the frequency and intensity of geological disasters worldwide, posing a formidable threat to human life and property. In the southern mountainous region of Ningxia, China—an area characterized by complex topography, interlaced ravines, and pronounced ecological fragility—recurrent geological disasters have substantially constrained rural revitalization and development. This study introduces the integration of the Information Value (IV) method with Random Forest (RF) and XGBoost models, identifying IV + XGBoost as the optimal model through rigorous ROC-curve validation. The results reveal that low- and lower-risk areas account for 58.63% of the total area (7644.20 km² and 4038.08 km²), medium-risk areas cover 29.24% (5825.76 km²), and high-risk regions constitute 12.13% (2417.28 km²). The latter are predominantly in river valleys with high population density and intensive economic activities. These findings provide practical recommendations for scientifically informed disaster management and decision-making by relevant authorities. Furthermore, the proposed methodology offers valuable insights for disaster risk assessment in other regions with similar complex terrains and ecological vulnerabilities, contributing to developing more effective and sustainable disaster mitigation strategies. Full article

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

Rural transformation is crucial to alleviating development pressure on traditional agricultural areas and stimulating rural vitality. This study aims to comprehensively analyze the spatio-temporal patterns, identify the key influencing factors, and propose targeted development strategies for rural transformation specifically within Northern Anhui, a quintessential traditional agricultural area in China. Utilizing the entropy method, exploratory spatial analysis, and geographic detector, we systematically evaluated the level of rural transformation and its spatial distribution characteristics across 35 counties and districts in Northern Anhui from 2011 to 2023. The results demonstrate a significant 35.93% increase in the average rural transformation level over the past decade, evolving from an initially low-level pattern to one characterized by “Central high, peripheral low”, with significantly narrowing disparities between counties and districts. Significant global positive spatial autocorrelation was consistently observed, alongside distinct localized clustering, including high-value clusters (H-H) and low-value clusters (L-L). A driver analysis identified investment efficiency, economic development level, industrialization, transportation accessibility, and fiscal revenue level as the predominant factors driving the spatial differentiation of rural transformation, with interaction detection revealing crucial synergistic effects among these factors. These findings provide valuable empirical insights and a scientific basis for formulating differentiated rural development strategies tailored to specific county types within traditional agricultural areas like Northern Anhui, thereby facilitating the rural transformation process in developing countries. Full article

Timely and reliable surface deformation monitoring is critical for hazard prevention and resource management in mining areas. However, traditional Time-Series Interferometric (TSI) Synthetic Aperture Radar techniques often suffer from low coherent point density in mining environments, limiting their effectiveness. To overcome this limitation, we propose an adaptive Polarimetric TSI (PolTSI) method that exploits dual-polarization Sentinel-1 data to achieve more reliable deformation monitoring in complex mining terrains. The method employs a dual-strategy optimization: amplitude dispersion–based optimization for Permanent Scatterer (PS) pixels and minimum mean square error (MMSE)-based polarimetric filtering followed by coherence maximization for Distributed Scatterer (DS) pixels. Experimental results from an open-pit mining area demonstrate that the proposed approach significantly improves phase quality and spatial coverage. In particular, the number of coherent monitoring points increased from 31,183 with conventional TSI to 465,328 using the proposed approach, corresponding to a 1392% improvement. This substantial enhancement confirms the method’s robustness in extracting deformation signals from low-coherence, heterogeneous mining surfaces. As one of the few studies to apply Polarimetric InSAR (Pol-InSAR) in active mining regions, our work demonstrates the underexplored potential of dual-pol SAR data for improving both the spatial density and reliability of time-series deformation mapping. The results provide a solid technical foundation for large-scale, high-precision surface monitoring in complex mining environments. Full article