Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.

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Floods have become the most prevalent and catastrophic natural hazard that plagues cities worldwide. As an inherent characteristic of an urban system that reflects the degree of effect of flooding and the capacity to cope with it, urban flood vulnerability is of great significance when analyzing and managing flood disasters. To produce a better profile of the current status and the development trend of urban flood vulnerability research, this study conducted a bibliometric analysis using CiteSpace software based on 1134 articles sourced from the Web of Science Core Collection database. The results showed that the annual publication number exhibited an ascending trajectory, which was characterized by three stages: the sprouting stage, the stable development stage and the rapid development stage. The United States, China and England were the most productive countries. Among the top co-cited journals were Natural Hazards, Natural Hazards and Earth System Science, Global Environmental Change and the Journal of Hydrology. In addition, the focus of this research can be succinctly summarized as vulnerability assessments and mapping, the impact of climate change and urbanization on urban flood vulnerability and the integration of urban flood vulnerability with flood risk and urban resilience. This study presents a comprehensive analysis of the current status and development trends of research related to urban flood vulnerability, and it contributes an understanding of the key areas of focus in this field as well as insights into potential prospects for future investigation for researchers and practitioners.

The paper interprets the “shape” and “meaning” of the new courtyard-style building from the two dimensions of architectural culture and architectural technology, as well as three levels of interpretation, construction, and cooperation. At the same time, it takes the building of “Waterside Cube” in Solar Decathlon China Competition as an example, which puts forward the concept of “Re-Traditional” and analyzes the generation logic and possibility of development of the new courtyard-style building which is combined with architectural culture and architectural aesthetics. Meanwhile, it puts forward the application of building technology and coping methods for rapid construction problems and finally summarizes the new ideas for the development of new courtyard-style buildings.

Driven by the emission peak and carbon neutrality targets, traditional cruising taxis are also under pressure to reduce emissions, and reducing taxi vacant time is an effective way to reduce emissions. This paper aims to examine the influence mechanism of built environment characteristics on vacant time of taxi trips from the supply-side perspective. To do so, the study uses a one week of taxi trajectory data of 2019 provided by a taxi company in Chongqing, a megacity in China. We take the divided square grid cell as the study units, calculate the taxi vacant time of 168 (7 × 24) hourly slots for each grid, and then calculate the built environment indicators of the grids with Point of Interest (POI) and vector road network data. A generalized additive model (GAM) based on panel data is constructed to investigate the influence mechanism of built environment on taxi vacant time. The results show that the time-varying trend of taxi vacant time is opposite to the time-varying trend of taxi trips and is similar to taxi trips in spatial distribution with significant spatial dependence. Taxi vacant time is negatively correlated with taxi trips. POI mixture, the number of enterprises, governmental agencies, and shopping services are negatively correlated with vacant time, while the number of sports and leisure services, hotel services, healthcare services, financial and insurance services, and living services are positively correlated with vacant time. An interesting finding is that metro stations significantly increase the vacant taxi time in the region. Average traffic flow speed, road density, the number of bus stops, catering services, residence communities, and motor vehicle services show strong nonlinear relationships with taxi vacant time, and their influence effects are alternately positive and negative. The study provides useful insights for understanding mechanisms of the role of built environment on taxi vacant time and has important implications for driver searching strategy improvement, taxi management measures development, spatial and temporal scheduling of taxi capacity resources, and urban transportation facilities layout planning.

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