In the last three decades, relevant research has rapidly increased in tandem with the global popularity of TOD (transit-oriented development) initiatives. It is vital to thoroughly summarize this research and investigate its development trends for sustainable cities. The advent of bibliometrics has given rise to a new method of conducting systematic reviews. We wish to illustrate the evolution of the TOD field by applying scientometrics, with the aim of revealing trends in this field and establishing a scientific classification system. We employ visualization software such as VOSviewer and CiteSpace to conduct bibliometric analyses on TOD-related publications from the WOS database from 1994 to 2021. Potential TOD-related research hotspots and cutting-edge research trends are thoroughly examined. The results indicate that TOD research topics are diverse, with hot topics related to land use, built environment, travel behavior, etc. The regions studied in TOD research are mostly metropolitan areas. Based on a modest number of starting keywords, this strategy can be used to build a more relevant and deeper research network. Through expanding the research content and improving research methods, this paper can provide insights into identifying the evolution of TOD research in different locations of the world, as well as provide a reference for the application and implementation of TOD strategies.

Skylights are an efficient means of daylighting in exhibition spaces, but their design presents significant challenges. Considering that daylight utilization profoundly impacts both the visual and thermal environments while affecting energy consumption, the early application of multi-objective optimization strategies becomes imperative. However, many optimization studies provide numerical references only, without delving into the characteristics of opening distribution. This study introduces an optimized exploration approach for openings based on grid subdivision and material parameter selection, targeting Useful Daylight Illuminance (UDI), Energy Use Intensity (EUI), and Predicted Percentage of Dissatisfied (PPD). Simulations and optimizations were performed using Honeybee and Octopus, focusing on the optimal configurations of four typical skylights in Fukuoka, Japan’s climate. The results demonstrate that this novel optimization approach improves metrics for each case and challenges traditional perceptions of daylight systems. Flexible and diverse opening configurations, formed through irregular layouts and material combinations, help achieve more ideal holistic environmental effects under different climatic conditions. Thus, we should provide these research findings as design guidelines for similar scenarios.

Previous studies have identified that environmental awareness correlates with the choice of bicycle travel. However, few studies have considered the relationships with different types of healthy behaviors and environmental behaviors. This study examined the relationships between several healthy and environmental behaviors and the choice of bicycle commute using survey data. A total of 803 residents participated in this questionnaire survey. Using factor analysis, we constructed latent factors of healthy behaviors and environmental behaviors. Using a binary logistic regression model, we examined the relationship between latent factors and cycling usage, controlling for demographic characteristics. Factor analysis revealed three latent factors of healthy behaviors: “healthy diet”, “avoiding tobacco or overdrinking”, and “physical activity”. The latent factors of environmental behaviors were as follows: “household behavior” and “purchasing behavior”. The results showed that “avoiding tobacco or overdrinking”, “physical activity” and “purchasing behavior” correlated positively with bicycle commuting. Differences were also observed in relation to demographic characteristics.

Buses are one of the most essential parts of the urban transportation system since they can cater to residents’ daily transit demands. This study investigates the spatio-temporal patterns of urban bus traveler activities using a one-month bus trajectory dataset in Kumamoto City based on smart card data. Based on the idea of a compact city, the ordinary least squares (OLS) regression model is implemented to explore the factors that affect the bus ridership at the bus stop level in the 17 essential core districts in Kumamoto City. Then using the geographically weighted regression (GWR) model, we can get the spatial heterogeneity of the bus ridership and visualize the spatial distributions of parameter estimations. By comparing the results of the two models, we find that the two models performed similarly both in global fit and explanatory accuracy. These results can provide valuable suggestions for estimating bus demand, which may exert important implications for bus route optimization. They can also provide a basis for policy formulation by city and transportation planning and management authorities. The results of the study demonstrate the effectiveness of compact urban development in Kumamoto City from the perspective of bus ridership in each core district.