The COVID-19 pandemic has prompted a reassessment of urban space, including planning and architecture. This study employs a conditional generative adversarial network (CGAN) to derive the distribution of urban texture based on COVID-19 hotspots. It establishes a link between urban form and the pandemic, enabling the machine to predict high-risk urban forms. The study focuses on Macau, conducting model training, image generation, and comparing results for different assumed epidemic distribution degrees. The implications for urban planning are as follows: 1) Urban forms exhibit a correlation with epidemic distribution, allowing CGAN to predict high-risk urban forms; 2) Large-scale and high-density buildings promote COVID-19 transmission; 3) Green public open spaces and squares inhibit COVID-19 spread; and 4) Reducing building volume and density while increasing green public spaces can help mitigate COVID-19 distribution. This research offers valuable insights and potential applications in planning and design.

This study examines the relationship between folk religious place-making and urban public spaces, focusing on Macau’s Shi Gandang Temple. The research utilizes on-site visits, historical evidence, and interviews to analyze place-making processes, social functions, management mechanisms, and folk culture. The findings emphasize the significant influence of folk beliefs on Macau’s urban spaces and social management system. They contribute to the development of local communities and geopolitical relations. The study highlights the participation of folk religious places as key nodes and emotional hubs, facilitating conflict resolution among diverse communities. It also promotes positive interactions, cooperation, and integration of regional development with management mechanisms, governance models, and cultural orientations.

This research addresses the challenge of achieving a unified planning of architectural styles in urban expansion and preserving traditional buildings in villages and towns. It uses a conditional generative adversarial network (CGAN) to develop a technique for designing building facades in villages and cities. The results serve as design references, enhancing efficiency. The CGAN-Assisted model is applied to rehabilitate building facades and in visual design for rural tourism products, demonstrating practical usefulness and design potential. Using villages and towns in China’s Wuyishan area as an example, the study involves model training, image generation, and comparing results for different assumed buildings.