Center for Spatial Studies

Providing recommendations for interesting and engaging leisure walking routes is a complex problem due to the subjective and personal nature of the activity. Existing work has often focused on recommending the quickest or most popular walks. However, these routes often lack detail on the contextual and experiential factors of walks and do not attempt to match the requirements with those of users. This article presents a vision of how more contextual detail can be applied to walking routes. We consider how existing analysis and spatial data mining techniques, including real-time clustering, viewshed analysis, and colocation patterns, could be used to extend a place-based understanding of leisure walking routes. By using spatial methods to extrapolate a rich platial understanding of the locations of a walk, the proposed methods in this article will support an emerging framework for curating engaging leisure walking experiences, recommending routes beyond those of the quickest or the most popular.