The promotion and development of healthy cities are vital for enhancing human habitats and fostering sustainable economic growth. Based on the core databases of Web of Science, PubMed, Google Scholar, and PsycINFO, and the knowledge graph software, this paper presents a quantitative analysis of the literature related to attention recovery abroad. It is found that in recent years, the research on attention recovery has developed rapidly, the number of related studies has been increasing, and the research content presents the characteristics of interdisciplinary integration. By further analyzing the characteristics of the research literature, research context, and knowledge basis, this paper summarizes the empirical research based on the existing quantitative analysis, reviews the research field based on the mechanism of attention recovery, and analyzes the development process and trend based on the research basis of attention recovery. Due to the change in the modern life style, human health problems are becoming more and more prominent. Attention restoration design provides a new research idea and method to balance the relationship between humans and the urban environment.

The promotion and development of healthy cities are vital for enhancing human habitats and fostering sustainable economic growth. Based on the core database of Web of Science and the knowledge graph software, this paper makes a quantitative analysis of the literature related to attention recovery abroad. It is found that in recent years, the research on attention recovery has developed rapidly, the number of related literature has been increasing, and the research content presents the characteristics of interdisciplinary integration. By further analyzing the characteristics of research literature, research context, and knowledge basis, this paper summarizes the empirical research based on the existing quantitative analysis, reviews the research field based on the mechanism of attention recovery, and analyzes the development process and trend based on the research basis of attention recovery. Due to the change of modern life style, human health problems are becoming more and more prominent. Attention restoration design provides a new research idea and method to balance the relationship between humans and the urban environment.

As a concept to describe the characteristics of urban spatial forms, urban grain emphasizes the size of urban parcels. Fine grain and coarse grain are considered essential attributes. Fine grain plays a crucial role in promoting the adaptability of urban development, improving urban vitality, and helping achieve sustainable urban development. Current research on urban grain is scattered and difficult to apply to solve practical urban problems. Therefore, this paper aims to identify the spatial indicators that affect the urban grain, to solve urban problems by adjusting spatial indicators. It contains significant suggestions for improving urban design theory and promoting sustainable urban development. This study primarily uses the comparative method to identify spatial indicators influencing urban grain by comparing coarse- and fine-grain study areas. This study screens relevant spatial indicators (building density, road network density, age of housing structures, building façade width along streets, number of entrances and exits along streets, and function mixture) affecting urban grain through a review and measurements, and it visualizes the representation of spatial indicators using the grid method, determining the correlation between spatial indicators and urban grain. The results show that all six indicators have an impact on urban grain.

The quality of travel for residents has improved in China’s urban renewal development, but there are still barriers to the activities of disadvantaged groups like people with disabilities in the city, including challenges with accessible travel and a lack of accessible design. All urban people should have access to services and be guaranteed equal rights, according to the inclusive development theory. This study examines the travel requirements and behavioural patterns of the barrier-free groups to safeguard the right of underprivileged groups to participate equally in the urban space. It also determines the impact of various types of urban land use and service facilities on the distribution of barrier-free facilities. An evaluation system based on the needs of the disabled group is established to evaluate the degree of barrier-free facilities in the surveyed areas, summarise the problems shown by the evaluation scores, and propose improvement strategies for the shortcomings of accessibility to residential areas and the controversy through web data crawling and a geographically weighted analysis. From the standpoint of inclusive development, the goal is to lessen the travel issues faced by underprivileged groups and to improve their capacity to take advantage of opportunities and have access to resources.

The current design of commercial service spaces in many communities faces issues like incoherence, irrational resource allocation, and low utilization rates. These challenges contribute to increased energy consumption in communities, hindering the overall sustainable development of cities. As a representative community space in the urban environment, the commercial space within the campus requires continuous energy input. Its energy-efficient layout aligns with the principles of sustainable development. This paper uses the university campus as a case study to examine energy-efficient commercial space layout and community practices for environmental protection. Various factors influence the layout of inter-community commercial spaces, and the parameters for measuring the layout structure are diverse, considering the large sample size. Employing machine learning and big data processing to quantify development indicators across various industries and optimize their structure, resource allocation, and energy use has emerged as a viable tool for sustainable urban planning practices. This research seeks to utilize machine learning and data-driven optimization techniques to formulate a comprehensive framework for the sustainable allocation and design of business service spaces within communities. Firstly, we conduct a comprehensive investigation, which includes data collected by applying questionnaire surveys and field research, to assess and model the factors influencing the spatial layout of commercial services on university campuses. Secondly, the AEL machine learning model is constructed by combining the analytic hierarchy process to determine subjective weights, the entropy weight method to calculate objective weights, and the Lagrange algorithm to determine comprehensive weights. Thirdly, we assess and improve the layout of commercial service spaces. Then, by training and testing the Neural Network Model, we apply cases to ensure the accuracy of the machine learning calculation results. Qualitative analysis elucidates the varying factors influencing the sustainable layout of different commercial spaces. Quantitative analysis indicates that, within university campuses, the distance between commercial service spaces and residence halls is a crucial factor in fostering a more sustainable layout. Other significant factors include their location along major student routes and proximity to teaching areas. This study makes contributions not only to the specific field of optimizing commercial service space in communities but also to the broader discourse on sustainable urban development. It advances our understanding of the complex dynamics involved in crafting urban environments that are both efficient and environmentally friendly. Beyond theoretical considerations, the study provides practical solutions and recommendations applicable to implementing tangible improvements in resource allocation. These contributions aim to foster urban environments that are not only environmentally conscious but also economically viable.

The industrial small-town development process in Shandong is influenced by the urban agglomeration strategy and the regional collaborative production, thereby resulting in a challenge of growth boundary planning. How to build a growth forecast decision support system to help small industrial towns maintain sustainable development with limited trial and error costs is an essential topic in the current research of small town-related fields. Empirical analysis reveals that the growth factors of small towns differ from the factors of cities due to the other-organization planning management system and self-organization construction activities that coexist in small towns. Besides, due to the size of small towns, the impact of policy changes in small towns is more significant than in cities. Furthermore, as part of the regional production chain, small industrial towns are most vulnerable to uncertain external disturbances. Therefore, it is necessary to formulate different development scenarios according to possible disturbances and output corresponding development forecasts. The research aims to build a decision-making support system for Shandong’s small-town planning based on an urban modeling approach using geographic information technology and scenario planning. Considering the mutually driving effects of the objective environment and subjective policies of Shandong’s industrial towns, as well as the corresponding dynamic mechanisms and comparing the theoretical basis and limitations of the different modeling approaches, this essay constructs a model system based on a mathematical model and a system dynamics model. It is also an interactive model accompanied by applicable rules and factors so that initial information and relevant development goals can be inputted into the model system to simulate the influence of different policies and identify the small industrial town growth scenarios.