Profiling and visualizing activity spaces of urban utility cyclists

Recent literature concludes that there is a likelihood of activity-space approach to physicalactivity analysis receiving much attention in the developed world (Schonfelder and Axhausen, 2010). Recent call for further research in detection and representation of activity spaces from portable GPS trackers, within the context of mobility pattern research is therefore timely (Thierry et al, 2013). However, little is known about the analysis of movement data in an explicit context and even less on the visualisation of actual urban cycling behaviours in available literature (Andrienko and Andrienko, 2013); particularly, when it comes to our understanding of individual level cycling behaviours in the British geographical context (Goodman, 2014). This is partly due to the lack of spatio-temporal information needed as input, but also due to the limited diffusion of innovative approaches for producing visualisation that add to the existing body of knowledge. Context is a vague and even versatile term in Visual Analytics (VA) since VA itself is quite broad. This paper therefore follows a view on conceptualization of context which makes the assumption that context is based on a fixed set of pre-determined descriptively well-defined terms used for processing and integrating information (Tomaszewski and A. M. Maceachren, 2010). This paper analyses, visualizes and explains activity spaces of actual movement behaviours of urban cyclists using a new dataset collected around Newcastle upon Tyne which is the urban core of the Tyneside conurbation in North East England. Analytical frameworks are drawn from visual analytics and Local Moran I spatial statistics in understanding urban cycling behaviour together with stationary and motile activity spaces concepts are used to understand urban cycling behaviours in both space and time. These concepts were operationalised using already established and publicly available area boundaries from the UK electoral Ward and the Census Output Areas (OA) geographies.