As an essential material carrier of cultural heritage, the accurate identification and effective monitoring of buildings in traditional Chinese villages are of great significance to the sustainable development of villages. However, along with rapid urbanization in recent years, many towns have experienced problems such as private construction, hollowing out, and land abuse, destroying the traditional appearance of villages. This study combines deep learning technology and UAV remote sensing to propose a high-precision extraction method for conventional village architecture. Firstly, this study constructs the first sample database of traditional village architecture based on UAV remote sensing orthophotos of eight representative villages in Beijing, combined with fine classification; secondly, in the face of the diversity and complexity of the built environment in traditional villages, we use the Mask R-CNN instance segmentation model as the basis and Path Aggregate Feature Pyramid Network (PAFPN) and Atlas Space Pyramid Pool (ASPP) as the main strategies to enhance the backbone model for multi-scale feature extraction and fusion, using data increment and migration learning as auxiliary means to overcome the shortage of labeled data. The results showed that some categories could achieve more than 91% accuracy, with average precision, recall, F1-score, and Intersection over Union (IoU) values reaching 71.3% (+7.8%), 81.9% (+4.6%), 75.7% (+6.0%), and 69.4% (+8.5%), respectively. The application practice in Hexi village shows that the method has good generalization ability and robustness, and has good application prospects for future traditional village conservation.

The Great Wall is an example of linear cultural Heritage (LCH) subjected to a fragile ecological environment and unbalanced economic development. However, no studies have been conducted to assess the sustainable development suitability (SDS) of the Great Wall region. Heritage area development assessments can increase public and government knowledge of the state of heritage areas and aid decision makers in formulating sensible policies or plans to protect and develop heritage areas. The valley is the spatial model of mountain economic development proposed on the basis of a basin combined with the ecological protection, rural development, and cultural inheritance present in mountainous areas. This study chose 169 valley units in the Beijing Great Wall Cultural Belt as research objects. A 15-indicator assessment index system was established based on the ecological, socio-economic, and cultural dimensions. The assessment procedure was enhanced by employing the triangle graphical method, and spatial autocorrelation was used to study the geographical distribution features of the development suitability scores derived from the research region. The results show the following facts: (1) Yanqing, Huairou, Miyun, Pinggu, and Changping have high development suitability results, whereas Mentougou and Changping have low scores. (2) In total, 96 valley units have practical advantages, and 51.5% are comprehensive development types (with advantages in at least two aspects). (3) Valley development suitability scores spatially cluster into seven high- and low-value groups. The ecological carrying capacity of the Badaling Cluster cannot maintain its overheated development. The results match up well with the objective condition of planning in the Beijing Great Wall National Cultural Park. We conclude that the proposed indicator framework and analytical method can be transferred to cases with similar contexts.

The Great Wall, as a globally important large-scale linear cultural heritage asset, is an example of the integration of architecture and landscape, demonstrating the interaction and feedback between heritage and the environment. In the context of advocating the holistic protection of cultural heritage and surroundings, this study utilizes landscape character assessment (LCA) to identify the landscape character of the Great Wall heritage area. Taking the heritage area of the Great Wall in Beijing, China, as an example, principal component analysis (PCA), two-step clustering, and the eCognition software were used to identify and describe the landscape character types, and the interaction mechanism between heritage and the environment was further explored through the reclassification process. A total of 20 landscape character types and 201 landscape character areas were identified in the study area, and a deep coupling relationship between heritage and the environment and cultural landscape spatial patterns were found in the core heritage area. The heritage and environmental character of linear heritage areas should be integrated so as to protect, manage, and plan cultural heritage areas at the landscape level. This study identifies and describes the character of the coupling of heritage and the environment in the Great Wall area for the first time, expands the types and methods of landscape character assessment, and carries out the exploration to combine natural and cultural elements of large-scale linear cultural heritage areas.

Livelihood diversification for traditional villages is essential to reducing poverty, addressing rural hollowing, and achieving the Sustainable Development Goals (SDGs). Shanxi Province—with its wealth of ancient villages, diverse cultural heritage, and unique landscapes—serves as a critical case for analyzing livelihood strategies. This research proposes a framework for livelihood diversification in Shanxi Province’s 619 traditional villages. Firstly, we constructed an indicator system to measure livelihood assets, including ecological stability, economic feasibility, land productivity, cultural inheritance, and social service capacity. Then, the trade-offs and synergies between each pair of assets are explored based on the correlation tests and the Geographically Weighted Regression (GWR) model. Finally, the Self-Organizing Map (SOM) model is employed to cluster the dominant livelihood assets of the sample villages. The results indicated that (1) the current sustainable livelihood levels of traditional villages in Shanxi Province exhibit spatial differentiation and imbalance. (2) The analysis confirms significant synergy between cultural inheritance, social service capacity, and economic feasibility, suggesting that appropriate protection and enhancement of local culture positively correlates with sustainable economic and social development in the villages. (3) Utilizing the SOM clustering model, six distinct types of sustainable livelihood strategies for traditional villages in Shanxi Province were successfully identified. Furthermore, a county-scale “multi-livelihood zoning” strategy has been proposed. The findings of this research can serve as a valuable reference for strategic planning and the implementation of rural revitalization.

Military settlements are an integral part of the military defense system of the Ming Great Wall, and the spatial layout of their constituent elements embodies the wisdom of ancient military geography. However, existing studies have predominantly focused on the macro-scale distribution of military settlements, with insufficient exploration of the spatial differentiation mechanisms of their micro-level constituent elements. Therefore, this study examines 61 military settlements in Miyun District, Beijing. Based on documentary research and field surveys, the types of constituent elements were systematically identified. This study employs kernel density analysis and the Optimal Parameters-based Geographical Detector (OPGD) model to explore their spatial patterns and driving mechanisms. The results show that (1) the constituent elements of military settlements collectively exhibit a spatial pattern of “one belt and three cores”, with pronounced spatial heterogeneity; (2) Fortress level, Military strength, and Distance to the Lu Fort are the core factors influencing the spatial differentiation of elements; and (3) when multiple factors interact, the interaction between Military strength and Distance to the Lu Fort demonstrates a significant nonlinear enhancement effect. This study reveals the spatial organizational logic of the Ming Great Wall military settlements at the micro-element level, providing a scientific basis for the graded protection and adaptive reuse of military settlements in Miyun District. Furthermore, the proposed analytical framework can also offer methodological insights for studies in other regions along the Great Wall.