Describing the functional spatial structure of urban environments

People learn the layout of cities mainly through a series of trips. Wayfinders experience the city structure differently depending on the mode of transport they use. The acquired mental representation then consists of the directly observed, physically accessible parts of the city. In this paper, we propose a computational model to construct images of cities, adapting their content depending on the wayfinder's access constraints. First, we formally study and extend the classification of Lynch's elements of the city form. Second, we propose a simple approach to analyzing local functional relationships between these elements, as experienced by wayfinders. The study of the functional relationships allows for the construction of the most complete image of the city that might be acquired by a wayfinder with given accessibility characteristics. These representations of urban environments can support advanced spatial assistance systems and cognitively efficient spatial interfaces.