Publications
Temporal and spatial distribution characteristics of the Ming Great Wall
The Ming Great Wall, a monumental engineering achievement and military defense structure, exhibits distinct temporal and spatial distribution patterns shaped by warfare with Mongolia. Research combining historical textual analysis, site surveys, and GIS database analysis identifies five construction phases (1368–1620), revealing that defensive facilities like forts and passes were prioritized before continuous wall construction. The study highlights two major construction climaxes during the Chenghua to Zhengde (1465–1521) and Jiajing (1522–1566) periods, culminating in the completion of the entire wall line by 1620. These findings provide critical insights for preserving the integrity and authenticity of this UNESCO World Heritage Site, contributing to cultural heritage conservation.
Assessment of Sustainable Development Suitability in Linear Cultural Heritage—A Case of Beijing Great Wall Cultural Belt
A comprehensive assessment of sustainable development suitability (SDS) for the Beijing Great Wall Cultural Belt reveals significant regional disparities, with Yanqing, Huairou, Miyun, Pinggu, and Changping districts showing high SDS scores, while Mentougou lags. The study, employing a 15-indicator index system and spatial autocorrelation analysis, identified that 96 out of 169 valley units have practical advantages, with over half exhibiting comprehensive development potential across ecological, socio-economic, and cultural dimensions. Notably, the Badaling Cluster faces sustainability challenges due to its high ecological carrying capacity demands. These findings align with existing planning objectives for the Beijing Great Wall National Cultural Park, underscoring the applicability of this indicator framework and analytical method to similar contexts.
Biocrusts protect the Great Wall of China from erosion
Biocrusts significantly enhance the mechanical stability and reduce erosion of the Great Wall of China, covering 67% of studied sections. These biological soil crusts decrease porosity, water-holding capacity, erodibility, and salinity by 2 to 48%, while increasing compressive strength, penetration resistance, shear strength, and aggregate stability by 37 to 321%. The protective effects depend on biocrust features, climatic conditions, and structure types. This study highlights the critical role of biocrusts as a nature-based solution for preserving this monumental heritage from erosion.
Identifying Landscape Character for Large Linear Heritage: A Case Study of the Ming Great Wall in Ji-Town, China
A comprehensive landscape characterization of the Ming Great Wall (M-GW) in Ji-Town, China, reveals eight distinct landscape character types and 47 sub-areas, spanning approximately 8650.7 km². This study introduces a hierarchical method combining digital and manual approaches to delineate key visual, cultural, and natural attributes of the M-GW, addressing fragmentation issues caused by traditional protection methods and unregulated tourism. The findings provide critical insights for planning the National Cultural Park and offer a sustainable management framework for large linear heritage sites like the Great Wall.
Non-destructive testing research on the surface damage faced by the Shanhaiguan Great Wall based on machine learning
A machine learning approach significantly enhances the detection of surface damage on the Shanhaiguan Great Wall, a UNESCO-listed Ming Dynasty structure. By applying the YOLOv4 model to analyze gray brick surfaces, researchers achieved a 0.17% increase in accuracy over traditional methods, identifying four types of damage—chalking, plants, ubiquinol, and cracking—without manual intervention or destructive testing. This innovation accelerates monitoring, reduces labor costs, and enables timely repairs while preserving the historical integrity of ancient brick walls.
Quantitative evaluation of plants on top surface of the Great Wall in Dazhuangke using the analytical hierarchy process
A quantitative evaluation of plant species on the Dazhuangke section of the Great Wall reveals that 45 species or categories significantly impact the structure, with 'Disruptive Effects' being the most critical factor. Using the Analytic Hierarchy Process and expert Delphi method, researchers identified 13 key indices across three constraint layers to assess plant-induced damage. The study found that 'Impact on the Near Side Wall' is the highest-weighted element in the evaluation model, guiding preservation recommendations categorized into Grade I ('Preservation'), Grade II ('Partial Preservation'), and Grade III ('Removal'). This approach provides a scientific basis for balancing heritage protection with plant management strategies.
Spatial Structure and Corridor Construction of Intangible Cultural Heritage: A Case Study of the Ming Great Wall
Research on the Ming Great Wall reveals that intangible cultural heritage (ICH) forms a distinct spatial pattern of 'three cores and one belt,' with high-density areas concentrated in Beijing, Liaoning, northern Ningxia, and southwestern Inner Mongolia. This distribution is influenced by natural, economic, and social factors. The study also found that ICH, particularly folk art, is predominantly distributed from southwest to northeast along the Great Wall. Suitability analysis indicated higher suitability for heritage corridors in eastern regions like Beijing-Tianjin-Hebei and Liaoning, while western areas such as Gansu, Ningxia, and northern Inner Mongolia showed lower suitability. The research used kernel density estimation, standard deviation ellipse analysis, and minimal cumulative resistance (MCR) method with multifactor spatial superposition to explore these patterns. It concludes with recommendations for the appropriate development of heritage corridors at macro and meso levels.
Topic Modeling for Hiking Trail Online Reviews: Analysis of the Mutianyu Great Wall
Chinese and non-Chinese hikers share common concerns about hiking challenges, scenery, tour services, and crowding at the Mutianyu Great Wall, but differ in their perceptions of cultural resources. This insight emerges from a topic modeling analysis using latent Dirichlet allocation (LDA) on a large dataset of online reviews. The study highlights key attributes influencing hikers' experiences, offering valuable implications for tailoring domestic and international market strategies at UNESCO World Heritage Sites.
Types of lime binders in mortars used for the construction of the Ming Great Wall of China and their importance for the development of a conservation strategy
Research on the Ming Great Wall reveals that dolomitic lime, a high-strength binder with low porosity, was predominantly used in its construction around Beijing and Hebei provinces. This finding challenges the current conservation principle of preserving the wall as a ruin, suggesting instead that calcium-rich lime binders should be employed for conservation or restoration to mitigate damage caused by reactions between dolomitic lime mortars and air pollutants. The study analyzed chemical and mineralogical compositions of original mortars, identifying aggregate-free textures in both dolomitic and calcium-rich lime mortars. Additionally, it proposes natural hydraulic lime and pozzolana-gauged binders as more compatible alternatives for structural consolidation.
Visualized Failure Prediction for the Masonry Great Wall
A novel hybrid approach combining architectural visualization with structural collapse simulation successfully predicts failure mechanisms in the Ming Great Wall (1368–1644 AD). Using Blender and a physics engine, researchers modeled four damage types—stone layer collapse, step collapse, parapet wall inward tilting, and stone layer bulge—based on brick dimensions, friction coefficients, and adhesive strength. The method accurately visualizes failure processes and assesses structural stability, offering preliminary engineering insights. This study demonstrates the potential of digital tools to analyze and preserve the Great Wall’s integrity under natural and artificial threats.
A comparative case study of MTInSAR approaches for deformation monitoring of the cultural landscape of the Shanhaiguan section of the Great Wall
A comparative analysis of two MTInSAR techniques, PSInSAR and SBAS, reveals the structural stability of the Shanhaiguan section of the Great Wall while identifying localized deformation risks. Using high-resolution TerraSAR-X data from 2015–2017, researchers found that while the site remained largely stable, rock falls in mountainous areas posed potential hazards. The study highlights the need for more adaptable MTInSAR methods to effectively monitor linear heritage structures like the Great Wall, offering valuable insights for conservation efforts.
Distribution and Integration of Military Settlements’ Cultural Heritage in the Large Pass City of the Great Wall in the Ming Dynasty: A Case Study of Juyong Pass Defense Area
Research reveals that the Juyong Pass defense area, a key Ming Dynasty stronghold near Beijing, had its military resources disproportionately concentrated in the western part of the Great Wall, forming a secondary core alongside the pass city. This finding challenges current conservation efforts, which focus solely on Juyong Pass, thereby undermining the heritage's integrity. The study applied spatial analysis to a military settlements database, identifying that over half of the defense area's resources were allocated to the western region. By mapping the distribution of cultural heritage, the research aims to guide sustainable preservation practices that respect historical spheres of control and integrate resources along the Great Wall's significant cultural routes.
Ecological Risk Assessment and Protection Zone Identification for Linear Cultural Heritage: A Case Study of the Ming Great Wall
A significant portion (63.49%) of the Ming Great Wall Heritage (MGWH) faces low to medium ecological risk, with the highest risk areas (16.61%) concentrated at lower and medium elevations (200–1000 m). The study identified four protection zones—Protection-Restricted, Restoration-Moderate exploited, Restoration-Restricted, and Protection-Moderate exploited—based on preservation status and risk analysis using GeoDetector, principal component analysis, and bivariate autocorrelation. Ecological risks transition from human-dominated at lower elevations to natural factors at higher elevations, with a trend of increasing then decreasing risk as elevation rises. The research emphasizes the need for 'cultural heritage protection first' policies, restricting development while prioritizing ecological restoration and environmental management. This approach provides a scalable model for assessing and mitigating risks in large linear cultural heritage sites.
Damage Assessment of Earthen Sites of the Ming Great Wall in Qinghai Province
Support Vector Machine (SVM) emerges as a superior model for assessing damage to earthen sites of the Ming Great Wall in Qinghai Province, outperforming traditional back-propagation Neural Networks. This study demonstrates that SVM can accurately predict damage levels, providing a robust tool for conservation efforts. Researchers trained and tested two machine learning algorithms using data from 18 earthen sites, with SVM showing significantly better predictive performance. Validated through the case study of Liutun Great Wall, this approach offers a practical solution for preserving these historically significant structures, which have endured environmental threats for centuries.
Space Technology Facilitates the Preventive Monitoring and Preservation of the Great Wall of the Ming Dynasty: A Comparative Study of the Qingtongxia and Zhangjiakou Sections in China
A comparative analysis of two sections of the Great Wall—Qingtongxia and Zhangjiakou—reveals distinct degradation patterns driven by environmental factors. Using synthetic aperture radar interferometry, researchers found that surface deformation rates decreased from 2015 to 2018 along the observed corridor. In Qingtongxia, high winds and surface runoff significantly correlated with wall degradation (correlation coefficients: 0.582 for wind speed and 0.524 for elevation), while in Zhangjiakou, natural processes had negligible effects (coefficients near 0). This study underscores the potential of space technologies to enhance preventive monitoring and risk assessment for large-scale heritage sites like the Great Wall.
The Great Wall 3D Documentation and Application Based on Multi-source Data Fusion – A Case Study of No.15 Enemy Tower of the New Guangwu Great Wall
A novel approach combining terrestrial laser scanning and UAV photogrammetry successfully generated complete, high-quality 3D digital documentation of the No.15 enemy tower of the New Guangwu Great Wall. This method overcame challenges posed by harsh geographical conditions, such as steep cliffs and inaccessible interiors, which hinder traditional scaffolding-based techniques. By integrating internal structure data from laser scanning with external data captured via UAV photogrammetry—facilitated by RTK-UAV technology for efficient image control point layout—the study achieved comprehensive 3D modeling using an ICP algorithm. The resulting digital documentation supports heritage restoration efforts and demonstrates the potential of multi-source data fusion for preserving cultural heritage sites under difficult environmental conditions.
Cultivated land quality improvement to promote revitalization of sandy rural areas along the Great Wall in northern Shaanxi Province, China
Research identifies critical factors limiting agricultural land quality along the Great Wall in northern Shaanxi Province, China. The study reveals both single-factor (e.g., soil thickness, organic content) and combined-factor limitations (e.g., irrigation challenges, salinization), which vary spatially across the region. Using a potential index model, scientists pinpointed these constraints to propose targeted land quality improvement measures. These interventions aim to revitalize sandy rural areas, addressing practical challenges posed by harsh natural conditions in this transitional zone between the Maowusu Desert and loess hills.
Identifying Linear Traces of the Han Dynasty Great Wall in Dunhuang Using Gaofen-1 Satellite Remote Sensing Imagery and the Hough Transform
Researchers have developed an automated method to identify linear traces of the Han Dynasty Great Wall using high-resolution Gaofen-1 satellite imagery, achieving 80% accuracy. This approach combines image processing techniques with the Linear Hough Transform (LHT) and an improved Otsu segmentation algorithm. The study demonstrates that computer-based identification can effectively map and assess the preservation state of ancient structures like the Great Wall in Dunhuang, China. Additionally, the method shows potential for broader application across different dynasties and regions, offering a scalable solution for archaeological research and conservation efforts.
Study on Damage Assessment of Earthen Sites of the Ming Great Wall in Qinghai Province Based on Fuzzy-AHP and AHP-TOPSIS
AHP-TOPSIS emerges as the more accurate method for assessing damage to earthen sites of the Ming Great Wall in Qinghai Province, offering a closer alignment with real-world conditions compared to Fuzzy-AHP. This study evaluates 18 earthen sites by integrating their environmental context, material properties, deterioration patterns, and construction techniques. The findings highlight AHP-TOPSIS's potential for broader application in assessing similar heritage sites across Northwest China, providing a robust framework for targeted conservation efforts.
Efficient space and resource planning strategies: treelike fractal traffic networks of the Ming Great Wall Military Defence System
The Ming Great Wall (1368–1644) is more than a linear barrier—it is part of a sophisticated, treelike fractal traffic network that integrates with the wall to form an efficient military defense system. This study reveals how the Ming Great Wall Military Defence System (M-GWMDS) optimizes space and resource allocation through its fractal structure, merging military and civil settlements into a double-fractal system. Using Geographic Information System (GIS) analysis and fractal theory, researchers uncovered that this network allows for highly effective defense strategies in border regions, adapting to the unique man-land relationship of the era.
3D Digitisation of Large-Scale Unstructured Great Wall Heritage Sites by a Small Unmanned Helicopter
A hierarchical optimization framework enables precise 3D digitization of large, unstructured segments of the Great Wall using a small, low-cost unmanned helicopter equipped with a laser scanner and digital camera. The system addresses challenges posed by unpredictable pose uncertainties during fly-hover-scan and flying-scan modes, which can lead to mismatches in point cloud data. By tailoring optimization methodologies to each scan mode, the framework ensures accurate reconstruction of the Wall's complex terrain. A WebGL-based interface facilitates 3D model visualization and comparison, demonstrating the approach's feasibility for heritage conservation efforts.
Architectural Forms and Distribution Characteristics of Beacon Towers of the Ming Great Wall in Qinghai Province
Research on the Ming Great Wall's beacon towers in Qinghai Province reveals that their elevations typically decrease along military intelligence routes, with sudden changes at strategic corners. The study classified 116 beacon towers into six architectural types based on their relationship to surrounding structures and found a radial distribution pattern around the Xining Guarding Post, often following river systems and ancient roads. By analyzing 'beacon tower links,' the authors demonstrated how these towers facilitated intelligence transmission during the Ming Dynasty, showcasing the sophisticated design of ancient Chinese military architecture.
Conflicting Images of the Great Wall in Cultural Heritage Tourism
A striking disparity emerges between domestic tourists' admiration for modern facilities over heritage value and the government's emphasis on preservation, while business operators prioritize commercialization. This study, analyzing 7,466 online reviews and official documents, reveals how conflicting objectives among stakeholders shape cultural heritage tourism experiences at Mutianyu Great Wall. Using quantitative word frequency analysis and qualitative discourse semantics, researchers expose a tension where tourists' focus on amenities overshadows historical significance, while regulators advocate for protection. The findings underscore the need for balanced approaches in managing China's iconic World Heritage Site to reconcile commercial interests with conservation goals.
A History of the Great Wall of China
The Great Wall of China stands as the world's largest military defense structure, its enduring legacy rooted in over 2,000 years of architectural brilliance and historical significance. This comprehensive work traces its evolution through four key periods: initial construction of defensive walls, overall transformation, partial expansion, and maintenance. The Great Wall's value lies not only in its physical components—walls, gates, towns, garrisons, and signal towers—but also in the rich cultural heritage it embodies, inspiring countless classical works across poetry, literature, theater, and storytelling. Published by SCPG Publishing Corporation and distributed globally (except China) by World Scientific, this book offers a systematic and accessible exploration of the Great Wall's history, providing readers with a clear and thorough understanding of its development and impact on imperial China.
Community involvement at Great Wall World Heritage sites, Beijing, China
Local communities adjacent to UNESCO World Heritage Sites, such as the Great Wall in Beijing, China, primarily benefit from heritage tourism without significant involvement in decision-making or management. A study comparing two sites revealed that while communities receive economic and social benefits, their participation in planning remains minimal. Researchers developed a two-dimensional framework assessing community involvement based on decision-making and benefit acquisition, highlighting disparities between these dimensions. The findings suggest opportunities for improvement in engaging local communities more effectively in heritage tourism governance.
Community Participation in Tourism at a World Heritage Site: Mutianyu Great Wall, Beijing, China
Local communities near the Mutianyu Great Wall generally view tourism positively, but their opinions vary based on the extent of their involvement and exposure to its impacts. While community members benefit from tourism with minimal input in decision-making processes, this study highlights significant differences in perceptions among groups, suggesting that deeper participation could enhance both heritage conservation and local development outcomes. The research employs qualitative methods to analyze these dynamics, offering insights into how community engagement can be better structured in Chinese heritage management contexts.
Global–local relationships and governance issues at the Great Wall World Heritage Site, China
At the Badaling section of China's Great Wall tourism and heritage preservation coexist with both benefits and tensions. Research reveals that while local businesses strongly support tourism—prioritizing economic gains—they also show high awareness for heritage conservation, albeit with some tolerance for environmental impacts. The study highlights conflicts between global UNESCO standards and local development needs, noting weak international linkages at the site. Using interviews with officials and surveys of local operators, it maps a complex, hierarchical management structure that shapes preservation efforts and tourism policies.
Place Attachment and Heritage Tourism at the Great Wall
Heritage tourism at the Great Wall of China, particularly at Badaling and Mutianyu sections, significantly enhances local residents' place attachment. This study found that tourism development boosts their pride in their community, strengthens emotional and functional ties to their hometown, and increases willingness to stay while providing employment opportunities. Questionnaire surveys conducted in 2008 revealed that residents experienced heightened recognition of the Great Wall's value and attractiveness, suggesting that heritage tourism can foster positive sociocultural impacts. The findings offer practical insights for planning and managing sustainable heritage tourism.
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