One of the keys to creating an urban environment conducive to a healthy lifestyle is to promote active modes of transport, which leads to better air quality and increased physical activity levels.

At local scales, a good public realm design, such as better lighting, benches and cycle lanes, is proven to positively impact levels of walking and cycling. However, it’s often overlooked how the spatial-economic structure of cities influences people’s choice of transport modes in their day-to-day journeys. The majority of those journeys are generated by certain land uses, such as workplaces, grocery stores, GPs and schools. Access to these is supported or restricted by a combination of street and transport networks and land-use distributions, namely the spatial-economic structure of places. Understanding such structures is important to assess the potential of places to promote active travel in relation to those journeys that are made every day.

The study aims to assess such potential using three case studies: Leeds, Milton Keynes and the Royal Borough of Greenwich. Integrated urban models for these places and their wider context were built by combining street network, public transport systems, land use, and demographic data. The models were used to describe spatial-economic structures by calculating the catchment population for key destinations in various transport modes. The quality and capacity of those destinations were also incorporated. The fine-scale catchment analysis uses a street segment between intersections as a unit, allowing a purely spatial analysis, free from administrative boundaries.

The analysis highlights place-specific issues that can be addressed by certain urban planning and design interventions
to promote active travel. For example, in Milton Keynes a large proportion of its population commutes in private vehicles owing to the town’s mono-centric structure, insufficient public transport and relatively low population density. Overall, Greenwich has higher potential for active travel, reflecting higher population, service and street network densities. However, the analysis reveals spatial disparity, highlighting disadvantaged areas in active travel potential. The analysis also described regional inter-dependency in Leeds and its region, identifying needs for infrastructure support to promote active travel in certain areas.