The burgeoning field of sustainable tourism in historically significant urban districts has derived increasing attention in tandem with broader urban economic development. The perceived image of a tourist destination significantly affects tourist consumption behaviors and destination choices, while negative evaluations provide destination managers with insights for targeted improvements to tourist amenities, thereby contributing to the sustainable development of these historically significant districts. This study leveraged Python 3.12.3 software to collect online textual data from popular tourism websites, specifically Ctrip 8.71.4 and Mafengwo 11.1.7. Then, ROST CM6.0 software facilitated high-frequency word analysis, network semantic analysis, and sentiment analysis to outline the perceived image and characteristics of the Macau Historic District, a UNESCO World Heritage site, from the perspective of tourists. The findings are as follows: (1) The image of the Historic Centre of Macao as a tourist destination comprises four primary dimensions: cultural (16.02%), landscape (30.85%), emotional (16.97%), and local (36.16%). (2) Tourists perceive the Historic Centre of Macao as a blend of dynamism and tranquility, tradition, and modernity. (3) Emotional evaluations of the Historic Centre of Macao as a tourist destination are primarily positive (85.45%), whereas negative sentiments constitute 5.76%, with recurring themes pertaining to overcrowding, high prices, a lack of interactive experiences at attractions, excessive commercialization, and insufficient public rest facilities. These findings offer valuable directives for the future planning and development of tourism in Macau, a city recognized for its World Heritage status. (4) In summary, the thematic image of the Historic Centre of Macao can be considered authentic, romantic, and commercialized.

City image reflects urban culture and communication and influences tourists’ travel behavior. However, based on field investigations, it was found that Macau’s city space currently faces issues such as an imbalance in practical use efficiency, an overload of historical urban areas, and a mismatch between tourist numbers and spatial capacity. To further understand tourists’ travel experiences and influencing factors in Macau, this study uses user-generated content (UGC) textual data and takes the Macau Special Administrative Region in China as a case study. The ROST CM6.0 software and grounded theory analysis method are utilized to analyze the perceptual content and underlying influencing mechanisms of city image from the perspective of tourists. The research results show that: 1. Tourists’ perception of Macau’s city image mainly stays at the intuitive and superficial level, represented by individual landscapes such as the “Ruins of St. Paul’s”, “Grand Lisboa”, and “Galaxy”. 2. Tourists’ perception of Macau’s city image can be summarized into four main dimensions: architectural and landscape image, cultural and historical image, economic and commercial image, and spatial governance and public service image. 3. Negative aspects of tourists’ perception of Macau’s city image include infrastructure perception, tourism service perception, urban experience perception, and urban safety perception, with spatial scale perception being the most influential factor. Finally, this study proposes effective measures to optimize urban spatial resource allocation, improve urban infrastructure, enhance the spatial environment of the old city, strengthen the promotion of historical culture, improve urban transportation convenience, and enhance urban safety to provide references for enriching the theory of city image perception research and the development of urban tourism in Macau.

Introduction: Urban spatial planning is critical for the development of sustainable and livable cities. However, traditional planning methods often face challenges in handling complex planning scenarios and large-scale data.Methods: This paper introduces UrbanGenoGAN, a novel algorithm that integrates generative adversarial networks (GANs), genetic optimization algorithms (GOAs), and geographic information system (GIS) to address these challenges. Leveraging the generative power of GANs, the optimization capabilities of genetic algorithms, and the spatial analysis capabilities of GIS, UrbanGenoGAN is designed to generate optimized urban plans that cater to various urban planning challenges. Our methodology details the algorithm’s design and integration of its components, data collection and preprocessing, and the training and implementation processes.Results: Through rigorous evaluation metrics, comparative analysis with existing methodologies, and case studies, the proposed algorithm demonstrates significant improvement in urban planning outcomes. The research also explores the technical and practical considerations for implementing UrbanGenoGAN, including scalability, computational efficiency, data privacy, and ethical considerations.Discussion: The findings suggest that the integration of advanced machine learning and optimization techniques with spatial analysis offers a promising approach to enhancing decision-making in urban spatial planning. This work contributes to the growing field of AI applications in urban planning and paves the way for more efficient and sustainable urban development.

Drawing upon its regional culture, natural landscapes, and architectural features, Beishan Village in Zhuhai City, Guangdong Province, has forged a distinctive rural development model that combines an industrial park with tourism. While this approach has catalyzed rural progress, it also encounters numerous complex practical challenges. Utilizing the grounded theory method, this study employs participatory observation, in-depth interviews, and network data analysis to investigate the perspectives of three key stakeholder groups: villagers, tourists, and resident merchants. A model is constructed to capture their environmental perceptions of rural tourism. Based on an analysis of network and interview textual data, as well as the influencing factors identified through the theoretical model, this study proposes several optimization strategies. These include enhancing infrastructure development, cultivating a regional brand culture, strengthening the institutional management framework, establishing a rural sharing economy platform, and introducing digital tours. These strategies are designed to refine and enhance Beishan Village's development model, offering insights for similar villages and advancing the integration of beautiful China initiatives with urban and rural development efforts.

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.

This study delves into the profound impact and significance of religious culture on the urban spatial configuration and local cultural essence of Macau amidst contemporary societal transformations. Emphasis is placed on how religious sites undergo functional reshaping and role redefinition within the urban fabric, thereby influencing residents’ quality of life, cityscape, and cultural identity. Adopting a spatial anthropological lens, this research employs a multitude of methodologies including city walking, participatory observation, and historical analysis to investigate the spatial configurations and developmental trajectories of Macau’s diverse religious sites and their immediate environments. The aim is to unearth the historical drivers behind the formation and dissemination of religious culture in Macau and to elucidate its intricate interactions with urban space. The findings reveal that religious sites in Macau not only physically delineate unique urban spatial patterns but also serve as vital hubs for fostering local cultural cohesion and weaving social networks through routine religious practices, community engagements, and a plethora of festive and ritualistic events. The pervasive influence of these sites extends across multiple domains of society, culture, and economy, playing a pivotal role in maintaining regional stability and harmony, enriching cultural diversity, and propelling socioeconomic transformation.