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.

Amidst the backdrop of rural population decline and the inefficient expansion of construction land, traditional land management models are confronted with the dual challenges of supply–demand mismatch and low efficiency. This paper constructs a three-dimensional analytical framework based on decoupling types, development potential, and driving mechanisms. Initially, using Tapio’s decoupling theory, the study identifies the population–land decoupling types among 224 villages in Yanggao County, Shanxi Province, Northern China. It then evaluates the development potential of rural construction land using a comprehensive index system, and a linkage analysis between the two is conducted. Finally, the study employs the Logarithmic Mean Divisia Index (LMDI) method to conduct an in-depth analysis of the mechanisms driving changes in rural construction land. The results indicate the following: (1) Between 2010 and 2020, the study area exhibited a reverse evolution characterized by rural population loss and the expansion of construction land, with a significant “population–land decoupling” phenomenon. (2) The development potential for rural construction land shows a pattern of being high in the north and south, low in the middle, high in mountainous and hilly areas, low in plains, and high in peripheral areas but low in town centers. (3) Villages in Yanggao County are predominantly of the resource reserve type (49.11%), indicating relatively abundant land resource reserves. (4) In different population migration patterns, the reduction in land-use efficiency represents similar proportions (38% and 36%), with villages experiencing net population inflow performing better in improving land-use efficiency compared to those with net population outflow. Drawing on international governance experiences, the study proposes classification and phased implementation pathways. By revealing the dynamic patterns of rural population–land relationships—construction land potential and change mechanisms—the logic of regulatory path adaptation, the article provides a methodological paradigm for constructing a precise and differentiated land resource allocation system, promoting the transition of rural spatial governance from expansion in scale to an improvement in quality.

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.