The last decade has witnessed very active development in two broad, but separate fields,
both involving understanding and modeling of how individuals move in time and space …

Abstract Machine Learning (ML) approaches are increasingly being investigated as an
alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These …

Influential research on the negative effects of living in a disadvantaged neighborhood
assumes that its residents are socially isolated from nonpoor or “mainstream” …

Human mobility is differentiated by time scales. While the mechanism for long time scales
has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we …

Understanding urban vibrancy aids policy-making to foster urban space and therefore has
long been a goal of urban studies. Recently, the emerging urban big data and urban analytic …

It is increasingly recognized that mental disorders are affected by both personal
characteristics and environmental exposures. The built, natural, and social environments …

In the twenty-first century, more than ever, everything and everybody seems to be on the
move. Global flows of people, goods, food, money, information, services and media images …

Location-based check-in services enable individuals to share their activity-related choices
providing a new source of human activity data for researchers. In this paper urban human …

A considerable body of literature has investigated how environmental exposures affect
health through various pathways. These studies have generally adopted a common …

In Rhythmanalysis, Henri Lefebvre put forward his ideas on the relationship between time
and space, particularly how rhythms characterize space. Here, leading geographers …