LAUSR

Abstract In The Image of the City Lynch describes how individuals perceive and recall features in urban spaces. The most distinctive elements in the urban landscape - categorised in paths, nodes, edges, districts and landmarks - give shape to individuals' mental representation of the city. Lynch’s approach has stimulated research into spatial cognition, urban design and artificial intelligence, and it still represents an essential pillar in the analysis of urban dynamics. Nevertheless, an explicit link between The Image of the City and GIScience has not been completely explored yet. In this paper, a computational approach to The Image of the City is proposed. Different perspectives in spatial cognition and GIS research are integrated to obtain a complete Image of the City, in which the most salient elements are shared by a large part of citizens. Nodes, paths and districts were identified through network science techniques. Methods drawn from the information approach to The Image of the City are used to detect landmarks, integrating the complexity of points of reference in their visual, structural and semantic components, as conceptualised by Lynch and successive research. The methods were applied to the central area of Boston and built using freely available spatial datasets. Results were compared to Lynch’s maps to evaluate the methodology: besides a considerable discrepancy with regard to landmarks, a good correspondence for paths, nodes, edges and districts was found.