Historical villages bear historical, cultural, architectural, aesthetic, and landscape values, but they are facing a series of dangers and problems during the process of urbanization. Digital survey for traditional villages plays a crucial role in the preservation, planning, and development of this kind of heritage. The introduction of the terrestrial laser scanning technique is essential for heritage surveying, mapping, and modeling due to its advantages of noncontact measurement, accurate sensing of complex objects, and efficient operation. In recent years, TLS and related processing software (“SCENE”) have been widely presented as effective techniques for dealing with the management and protection of historical buildings in Fenghuang village. Thus, this paper highlights the process of using laser scanning to obtain architectural data, process point clouds, and compare the characteristics of historical buildings in Fenghuang village. The cloud-to-cloud registration technique is applied to build point clouds. As a result of model construction, some architectural patterns are summarized in this village, such as the spatial sequence of ancestral halls, the dominant position of memorial halls, and the character of building decorations and roof slopes. Furthermore, a BIM model is also explained to fulfill the statistical function for architectural components. In the future, more research can be fulfilled based on the built point cloud model, which will be beneficial for the development of the whole village.
The visual aesthetics of villages are remarkably affected by the exterior quality of traditional residences, influencing the impression and assessment of local culture. A proper scientific assessment of exterior quality can protect traditional cultures and improve the development of villages. This research was conducted in a village consisting of 115 residences (Mengjinglai village, which is on the border between China and Myanmar). The backpropagation (BP) neural network model with genetic algorithm (GA) was applied to evaluate the quality of the dwellings. All the evaluation values of the dwellings were defined by scores. Meanwhile, the score of each residence was affected by three main factors: architectural spatial elements, architectural construction elements, and historical and cultural elements. The results show that the village’s dwellings are well preserved and clearly express the traditional Dai style. Moreover, the GA–BP approach is more suitable than the traditional BP method for the assessment of the exterior quality. The quantitative machine learning model would be useful for other aspects of the assessment of similar villages in the future.
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