Automated Tool for Geographic Information Systems That Supports Transit Network Design by Identifying Urban Activity Centers

Public transit is central to sustainable multimodal transportation systems; however, designing an effective transit network remains an analytically challenging and complex task. Given the spatial nature of the problem, geographic information systems (GISs) can support transit network design by identifying subsections of urban areas within and between which very high travel demand exists. Once these corridors are identified, local knowledge and expertise may be used to develop routings that satisfy these demands. This paper presents a spatial approach to assist in designing transit networks and describes the development and application of an automated, spatial multicriteria aggregation algorithm implemented as a user-friendly GIS tool coded by using the Python scripting library (ArcPy). Using population and employment densities, spatial adjacency, and geographic and administrative boundaries, the GIS tool leverages readily available demographic data to classify and merge traffic analysis zones into larger urban activity centers. The tool then aggregates regional origin–destination matrices to visualize only the flows associated with the activity centers. The results show that this approach significantly reduces the number of origins and destinations to be considered in designing the network but retains a large proportion of regional trips. This paper demonstrates how the tool can be applied through an example from the region of Waterloo, Ontario, Canada, where the local transit agency is developing a transit network to support a central light-rail transit line.