The study of ancient settlements in the traditional waterside towns of Jiangnan is an important part of scientific research on architectural heritage. This study examines ancient settlements in the Nanxi River Basin during various historical periods, such as the Neolithic Age, Eastern Han Dynasty, Tang-Five Dynasty, Song-Yuan Dynasty, Ming Dynasty, and Qing Dynasty. It investigates their temporal and spatial evolution and the factors that influence their distribution, with a particular focus on the role of intangible cultural heritage. This study focuses on the relationship between the spatial evolution of traditional waterside settlements in the Nanxi River Basin and the distribution of intangible heritage and analyzes the driving factors of their development. How settlements changed over time and space was examined with geographic information systems (GIS) software and by using kernel density, elliptical variance, and spatial autocorrelation methods on 204 ancient settlement points. This study also employs buffer and data overlay methods to analyze the factors that affect settlement distribution by elevation, slope, water system distance, and distance to intangible cultural heritage points. The study reveals the following. (1) During the Ming and Qing Dynasties, clans, culture, and the economy drove the expansion of early settlements, which relied on water systems and flat terrain, to form a multicenter distribution. (2) The settlement distribution in the Nanxi River Basin has undergone a transformation from single-point distribution to multipoint aggregation and divergence during the evolution from the Neolithic Age to the Qing Dynasty. The overall center of gravity of the settlements shifts from south to north and east, and the overall distribution of the settlements is in a state of aggregation. (3) The spatial and temporal evolution of settlements is jointly influenced by the natural environment and cultural factors. The natural environment determines the spatial distribution of early settlements, while cultural factors promote the evolution and development of the settlement space. This study further clarifies the key role of intangible cultural heritage in the formation and development of settlements and provides a reference framework for future heritage protection policies.

In the analysis of complex historical layering, studies on how to avoid theoretical analysis and use quantitative methods of display and analysis are scarce. Therefore, we used space syntax to fill this gap in historical layering analysis. We established a spatial digital model by combining the urban historical landscape theory with the space syntax analysis method. Then, we quantitatively analysed the streetscapes in the four historical periods of Macau and the value-related development of the city’s economy, society, and culture. To this end, we used the theory of urban historical landscape to interpret the streetscape of Macau. We reviewed urban development under different spatial scales, which represent different states of historical layering. Changing ideological trends of construction have induced changes in the city, which have led to changes in the city style. The analysis considers the dimensions of space and time, and its results can guide the continued benign growth of the urban landscape and solve protection problems in practice. Meanwhile, the results of this work also indicate that the unique streetscape of Macau bred by the development of the city does not affect the newly constructed roads. The newly reclaimed areas and the streetscape of the new city are on the verge of homogeneity and cannot reflect the unique regional characteristics of Macau. Therefore, we used the historical map of Macau as a carrier, used space syntax to analyse the structure of Macau’s streetscape, and explored the apparent characteristics and value associations carried by the streetscape of Macau under different historical slices. Our results can help retrieve the value of Macau’s historical streetscape and devise a targeted protection strategy that can help pass on the historical streetscape of Macau to posterity.

From the perspective of social media data, this study investigates the coupling relationship between tourists’ spatial perception and tourism image in traditional old urban areas. Using Nanxun Ancient Town as a case study, this paper reveals the interaction and mutual influence between tourists’ perception of space and tourism image in the development of traditional ancient town tourism. We employed Python 3.13.0 to gather 10,789 valuable comments from tourists from Dianping 11.35.3, Ctrip 8.78.4, and Mafengwo 11.2.6. Mini Tag Cloud software is used to analyze the text data, systematically classify the cognitive image of tourists, and identify negative emotional factors. This paper constructs a four-dimensional landscape spatial perception evaluation system centered on “high-frequency words”, “perceptual dimensions”, “semantic networks”, and “emotional tendencies”. The key findings are as follows: (1) Tourists’ spatial perception exhibits pronounced characteristics of subjective preference and emotional attachment influenced by emotional factors. Overall, tourists exhibited positive emotional perceptions, with 59.51% positive emotions, 21.16% neutral emotions, and 19.33% negative emotions. (2) The perception of Nanxun Ancient Town’s tourism image can be summarized into four dimensions. Here are the dimensions in order of how important they are: historical culture and folk heritage (34.18%), perceptions of natural landscape and architectural style (31.03%), perceptions of tourism services and facilities (18.37%), and psychological identity and emotional interaction (16.42%). (3) Tourism image reciprocally influences tourists’ spatial perception. A positive tourism image is anticipated to encourage tourists to explore the spatial details of the ancient town more deeply, enhancing their positive spatial perception and experience. There exists a coupling relationship between tourists’ spatial perception and tourism image. (4) Key aspects of tourists’ perception of Nanxun Ancient Town include its historical and cultural significance, as well as commercialization. Future studies could focus on tourists’ spatial perception and tourism destination brand image building, and tourism policy makers should pay attention to tourists’ perception of Nanxun Ancient Town’s history, culture and commercialization, and use the coupling of the two to improve development and service policies.

(1) Background: the rapid development of cities and the process of industrialization has improved the level of economic development for all humanity, accompanied by a series of problems, such as the waste of ecological resources and the environmental destruction. Macau has long been one of the regions with the most active economic activities. However, the phenomenon of economic recession, unreasonable land use, and frequent flood disasters have appeared in the past few decades, which violate the concept of sustainable development; (2) Methods: this paper uses the BP neural network model to evaluate the sustainable development of Macau; (3) Results: the weight ranking of sustainable development is: economic > social > ecological environment. A correlation analysis shows that ecology and economy have a significant negative correlation; (4) Conclusions: In Macau, economic growth is given priority while social and ecological environment development lags behind. Macau has problems, such as a unitary economic structure and a high population density. This paper advocates that investment in ecological protection should be increased, environmental resources should be optimized and saved, and the concept of sustainable development should be strengthened in the application of Macau’s urban development.

Rural cultural heritage is a valuable testament to history and culture, with traditional dwelling walls serving as key research objects. However, in Zhejiang Province, humid conditions and weathering have led to damage such as cracks, holes, stains, and yellowing, posing protection challenges. This study employs the YOLOv8 deep learning model, leveraging multi-layer feature extraction and feature fusion to enhance automated damage detection. Field experiments in Hangzhou and Lishui involved data collection, annotation, model training, and testing. Results indicate high accuracy in yellowing (0.8) and stain detection (F1-score 0.71), with improved performance under high-resolution conditions. Additionally, a Raspberry Pi 5-based mobile detection system enables real-time monitoring, providing a cost-effective and efficient solution for cultural heritage protection.

The historic city of Macau is China’s 31st world heritage site, and its residents have actively contributed to preserving its heritage and will continue to reside there for the foreseeable future. Residents’ satisfaction with the current urban environment is closely related to the landscape characteristics of the towns surrounding the historic center of Macau. This study aims to analyze the relationship between landscape characteristics and residents’ satisfaction, determine the key factors affecting their satisfaction and how they are combined, and provide a scientific basis for urban planning. This study used a decision tree machine learning model to analyze 524 questionnaire survey responses that addressed five aspects of the historic town’s landscape: the architectural, Largo Square, street, mountain and sea, and commercial landscapes. The data-driven approach helped find the best decision path. The results indicate that (1) the layout of Largo Square, the commercial colors and materials, the location of the former humanities and religion center, and the commercial signage system are the primary factors influencing residents’ satisfaction. (2) Incorporating decision tree parameters with information entropy as the splitting criterion and a minimum sample split number of two (with no maximum depth) led to the best performance when investigating residents’ satisfaction with Macau’s historic town landscape characteristics. (3) A reasonable layout for Largo Square (satisfaction > 3.50), prominent and harmonious commercial colors and materials (satisfaction > 3.50), rich cultural and religious elements (satisfaction > 4.50), and an excellent commercial signage system (satisfaction > 4.00) can significantly improve residents’ satisfaction. This provides important empirical support and a reference for urban planning and landscape design in Macau and other historical and cultural cities.