Unpacking the weather-transit ridership relationship using big data in Brisbane and beyond

The emergence of passenger tracking technologies and big data have heralded a new generation of transport studies. In this chapter, we align to this new generation by overviewing the research that has applied transit smart card data, followed by an empirical case developed to provide a better understanding how weather affects people’s travel patterns in cities. Set against a backdrop of climate change and rapid urbanisation, understanding the travel behaviours of individuals across entire urban transit networks in response to shifts in weather conditions are critical in order to inform the smart design of resilient transit infrastructure. (Re)designing such infrastructure in a way that embeds weather resiliency (to account for both current and future predicted weather patterns) is important to ensure public transit poses an attractive alternative to the private vehicles for urban residents to fulfil their daily mobility needs. We draw on the results of a modelling exercise in conjunction with research in this domain to reveal that adult ridership is affected most by precipitation, and that this effect persists across multiple modes as well as for off-peak and weekends. However, more mixed effects for the combinations of weather phenomena show that wet and windy, hot and rainy, and hot and windy conditions are also important predictors of transit ridership.