This paper analyses current active transport usage in a car-dependent metropolis using household travel survey data. A major conclusion emerges: most people and households did not undertake any reportable active transport usage, despite increasing policy support, education and promotion encouraging uptake. Less than a quarter of the population recorded travel on foot and just over 2% by bicycle, although there are differences by gender and age. There are important implications for policy development and urban design interventions aimed at encouraging greater use of the active modes. This research shows we still have some way to go to achieve the levels of active transport uptake necessary for the creation of environmentally sustainable and healthy communities.
With regard to separation of food scraps for composting, this research identified that there are two important aspects often overlooked when the focus is only on behaviour: 1. Policy makers need to ensure that there are socio-technical systems supporting diverse groups of people...Read more
Transportation planners are often looking for efficiency in transportation but this article in Science Advances has also identified that resilience is an important city design feature. Planning for when disruptions occur can help to avoid city gridlock.Read more
Rapid global urbanization and the increase of the Urban Heat Island (UHI) effect make urban cooling a necessity as well as an opportunity to increase the liveability and amenity of cities. This review is a scoping study of the relevant worldwide UHI mitigation/adaptation...Read more
Beyond the benefits of dockless bike sharing for people’s mobility and health, these services are producing an ever more useful byproduct: journey data, which could be a powerful tool for city planners and policymakers
Understanding the flows of people moving through the built environment is a vital source of information for the planners and policy makers who shape our cities. Smart phone applications enable people to trace themselves through the city and these data can potentially be then aggregated and visualised to show hot spots and trajectories of macro urban movement. In this paper we present some preliminary findings using cycle data collected from a smart phone application known as RiderLog.