Bahrehdar, A.R.Adams, B.Purves, R.S.2020-09-012020-09-012020Bahrehdar AR, Adams B, Purves RS (2020). Streets of London: Using Flickr and OpenStreetMap to build an interactive image of the city. Computers, Environment and Urban Systems. 84. 101524-101524.0198-9715https://hdl.handle.net/10092/100978In his classic book “The Image of the City” Kevin Lynch used empirical work to show how different elements of the city were perceived: such as paths, landmarks, districts, edges, and nodes. Streets, by providing paths from which cities can be experienced, were argued to be one of the key elements of cities. Despite this long standing empirical basis, and the importance of Lynch's model in policy associated areas such as planning, work with user generated content has largely ignored these ideas. In this paper, we address this gap, using streets to aggregate filtered user generated content related to more than 1 million images and 60,000 individuals and explore similarity between more than 3000 streets in London across three dimensions: user behaviour, time and semantics. To perform our study we used two different sources of user generated content: (1) a collection of metadata attached to Flickr images and (2) street network of London from OpenStreetMap. We first explore global patterns in the distinctiveness and spatial autocorrelation of similarity using our three dimensions, establishing that the semantic and user dimensions in particular allow us to explore the city in different ways. We then used a Processing tool to interactively explore individual patterns of similarity across these four dimensions simultaneously, presenting results here for four selected and contrasting locations in London. Before drilling into the data to interpret in more detail, the identified patterns demonstrate that streets are natural units capturing perception of cities not only as paths but also through the emergence of other elements of the city proposed by Lynch including districts, landmarks and edges. Our approach also demonstrates how user generated content can be captured, allowing bottom-up perception from citizens to flow into a representation.enAll rights reserved unless otherwise statedStreetsLynchSimilarityUser generated contentPerceptionJournal Article2020-08-060909 Geomatic Engineering1205 Urban and Regional PlanningFields of Research::40 - Engineering::4013 - Geomatic engineering::401302 - Geospatial information systems and geospatial data modellingFields of Research::33 - Built environment and design::3304 - Urban and regional planning::330412 - Urban informaticshttp://doi.org/10.1016/j.compenvurbsys.2020.101524