Multimodality refers to the phenomenon of using more than one mode of transport in a given period. Encouraging multimodality potentially provides an effective solution to reduce CO₂ emissions and induce modal shifts toward sustainable transport. This research investigates the extent to which the level and correlates of multimodality differ by trip purpose. We used one-week travel diaries of the English National Travel Survey. Our analyses showed that the level of multimodality varied by trip purpose and the associated time-space variability as well as by the number of trip stages. We found that the level of variability in departure time and travel distance was greater for leisure trips than for maintenance trips, which was in turn greater than for work trips. Trips that were more variable in departure time and travel distance showed on average higher levels of individual multimodality, but only if sufficient stages (at least 3) were made. Moreover, we detected cross-purpose disparities in correlates of multimodality in terms of significance and variance explained. This research may provide support to the development of trip purpose-specific policies aiming to increase multimodality.

Urban form plays a critical role in shaping the spatial differentiation of land surface temperature (LST). However, limited research has investigated the underlying driving forces and interactions of multidimensional urban form, specifically considering two-dimensional (2D) urban land use and three-dimensional (3D) buildings, on LST. Furthermore, their multi-scale outcomes remain unclear. Taking the main urban area of Wuhan City as an example, a total of nine indicators—the proportion of administration land (PA), the proportion of commercial land (PB), the proportion of industrial land (PM), the proportion of residential land (PR), the proportion of water area (PE), the building density (BD), the building height (BH), the floor area ratio (FAR), and the sky view factor (SVF)—were selected; this paper used the geographic detector model to investigate the driving force of LST spatial differentiation in winter and summer, as well as the interaction of various influencing factors from a multi-scale perspective. The results showed that (1) the average LST in industrial land was higher than that in commercial land, both in summer and winter. The LST in administration land was higher than that in residential land, while in winter, it is the opposite. (2) The spatial differentiation of summer LST was mainly dominated by 3D buildings, while the spatial differentiation of winter LST was mainly dominated by 2D land use. (3) BD was the leading driving force of LST spatial differentiation in summer, and the interaction between BD and any other indicator showed the most significant explanatory power, which is the same for PM in winter. (4) As scale increased, the explanatory power of 2D urban land use for LST spatial differentiation gradually increased both in winter and summer, while the explanatory power of PE on LST spatial differentiation decreased. The explanatory power of BD, FAR, and SVF on LST spatial differentiation remains basically unchanged. The explanatory power of BH on summer LST spatial differentiation decreases with increasing scale, while the explanatory power of BH on winter LST spatial differentiation remains in a stable state. (5) The interaction among all urban form factors primarily increases as the scale increases, except for the interaction between BH and 2D urban land use in summer, and the interaction between PE and PR in winter. The research can provide scientific decision-making support for the collaborative optimization of multiscale urban forms to improve the urban thermal environment.