Historic sites are important components of every city’s cultural history because they preserve rich historical knowledge and distinctive values passed down from previous generations to the present. Due to the progress of urbanization and modernization, many historic sites face pressure from damage and transformation. In this paper, a method for assessing cultural heritage damage was developed to measure the extent of spatial damage in historic sites. Using sample data obtained in Xiyang, Qi, and Xiaoyi, all historic cities in Shanxi Province, Mainland China, and combined weights were estimated using the Delphi technique and the CRITIC weight method. Following this, the Spatial Damage Degree Model (SDDM) based on K-means cluster analysis and K-nearest neighbor (KNN) classification was developed. The findings show that the model efficiently solves the problem of assessing spatial damage levels in historic sites. Through multiple linear regression analysis, it was shown that the damage to historic sites was predominantly caused by three factors: natural erosion, construction damage, and planning and policy. SDDM was used to calculate the spatial damage levels of historic sites, allowing conservators to fully comprehend the features and concerns related to historic sites. As a result, more scientific and rational preservation approaches can be developed, improving the efficiency of historic site restoration and conservation, and encouraging the sustainable development of urban and rural heritage.

The Great Wall of China is a cultural monument of profound historical significance and a testament to the evolution of various historical periods. As a living heritage, it holds exceptional value. However, due to inadequate protection measures in recent years, numerous sections of the Great Wall have been subject to continuous degradation. While damage to its main structural components and explicit heritage elements has been widely acknowledged, the more critical issue lies in the ambiguous recognition and insufficient safeguarding of its implicit heritage elements. This study explores the composition and classification of protective elements associated with the Great Wall, proposing a framework that emphasizes the dual safeguarding of both its tangible structures and intangible cultural significance. Employing big data collection through search engine optimization (SEO) techniques and questionnaire surveys, this research analyzes recent trends in the prioritization of heritage conservation efforts related to the Great Wall. Furthermore, by constructing a mathematical model based on the “grey relational analysis” method, the study classifies and stratifies various heritage elements to highlight the Wall’s core values and propose targeted protection strategies. The findings reveal that (1) certain regions possess considerable development potential and can be restored and planned as cultural tourism destinations; (2) conservation efforts should prioritize material restoration while preserving the intrinsic spiritual and cultural values; (3) a living heritage transmission strategy should underpin the overall protection framework. Ultimately, the study establishes a classification and grading system for conservation elements centered on the sustainable development of the Great Wall heritage. By concretely mapping the concept of living heritage protection onto the various protective elements of the Great Wall, this research offers valuable insights and recommendations for enhancing conservation practices.

The Great Wall of China, one of the nation’s most remarkable military defense structures, possesses a history spanning several millennia and is associated with numerous heritage sites. Today, it stands as a world-renowned cultural heritage asset. Vegetation growing on the ruins of the Great Wall can exert both detrimental and protective effects on the structure. Indiscriminate removal of such vegetation may lead to unintended damage to the heritage site. Drawing on the theory of “evaluative conservation”, this study integrates the analytic hierarchy process (AHP) and the Delphi method to develop a resistance assessment system for vegetation removal. A case study was conducted on 40 plant species or categories located along the Ming-era Guangwu section of the Great Wall, with spatial zoning analysis applied to inform removal strategies. The results reveal the structure, key factors, and classification criteria of the resistance evaluation system. Corresponding management recommendations are proposed, including strategies such as “preservation”, “partial preservation”, “removal”, and “subsequent removal and management”. This research provides a foundational reference for the conservation and restoration of the Great Wall heritage, and for the management of associated vegetation.

This study investigated the Yongning Fortress ruins in Taiyuan through a comprehensive analytical approach employing scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), laser particle size analysis, X-ray diffraction (XRD), X-ray fluorescence spectroscopy (XRF), and ion chromatography (IC). The research focused on elucidating the disturbance mechanisms and environmental impacts induced by the root systems of five representative herbaceous species on rammed earth structures. The results demonstrated distinct, species-specific disturbance patterns. Melica roots created three-dimensional network damage, Artemisia capillaris primarily caused deep root penetration, Fallopia aubertii exhibited coupled physical–chemical effects, Convolvulus arvensis induced shallow horizontal expansion damage, while Cirsium formed a heterogeneous structure characterized by dense taproots and loose lateral roots. Environmental conditions, particularly moisture content, significantly influenced disturbance intensity. All root activities led to common deterioration processes, including particle rounding, gradation degradation, and formation of organic–mineral composites. Notably, vegetation markedly altered soluble salt distribution patterns, with Cirsium increasing total salt content to 3.7 times that of undisturbed rammed earth (0.48%), while sulfate ion concentration (1.16 × 10⁻³) approached hazardous thresholds. The study established a theoretical framework linking plant traits, disturbance mechanisms, and environmental response, and proposed risk-based zoning strategies for preservation. These outcomes provide significant theoretical foundations and practical guidance for the scientific conservation of rammed earth heritage sites.

Visitor access in linear defensive built heritage landscapes needs to balance historical interpretation, route accessibility, and current protection constraints. This issue is evident in the Laoniuwan section of the Ming Great Wall in Shanxi Province, China, where heritage nodes lie within a scenic area but access infrastructure and interpretive route organization remain underdeveloped. This study proposes a conservation-oriented trail planning method for Great Wall scenic areas by combining MaxEnt-based historical defensive landscape modeling with GIS-based contemporary resistance analysis. MaxEnt was used to model terrain- and visibility-related suitability for defensive node locations, including watchtowers, beacon towers, forts, and mamian. The output was treated as a historical landscape interpretation layer, not as a prediction of tourist movement or final route location. Contemporary resistance was built from terrain ruggedness, road and village disturbance, the Great Wall protection buffer, permanent basic farmland, and the ecological conservation redline. Three historical–contemporary weighting scenarios were compared using least-cost path analysis. A Conservation–Interpretation Balance Index (CIBI) was then used to support scenario selection. The 4:6 scenario achieved the highest CIBI score (0.606). It maintained connectivity among defensive nodes while reducing ecological and farmland conflicts. The recommended loop trail was further translated into a four-tier conservation management zoning scheme. The results offer a spatial decision support approach for organizing fragmented built heritage resources into controlled-access interpretation routes with reduced disturbance to heritage fabric and protected land.

Historic sites are important components of every city's cultural history because they preserve rich historical knowledge and distinctive values passed down from previous generations to the present. Due to the progress of urbanization and modernization, many historic sites face pressure from damage and transformation. In this paper, a method for assessing cultural heritage damage was developed to measure the extent of spatial damage in historic sites. Using sample data obtained in Xiyang, Qixian, and Xiaoyi, all historic cities in Shanxi Province, Mainland China, and combined weights were estimated using the Delphi technique and the CRITIC weight method. Following this, the Spatial Damage Degree Model (SDDM) based on K-means cluster analysis and K-nearest neighbor (KNN) classification was developed. The findings show that the model efficiently solves the problem of assessing spatial damage levels in historic sites. Through multiple linear regression analysis, it was shown that the damage to historic sites was predominantly caused by three factors: natural erosion, construction damage, and planning and policy. SDDM was used to calculate the spatial damage levels of historic sites, allowing conservators to fully comprehend the features and concerns related to historic sites. As a result, more scientific and rational preservation approaches may be developed, improving the efficiency of historic site restoration and conservation and encouraging the sustainable development of urban and rural heritage.