Mapping Urban Landscapes Along Streets Using Google Street View

Abstract

City streets are a focal point of human activity in urban centers. Citizens interact with the urban environment through its streetscape and it is imperative to, not only map city streetscapes, but quantify those interactions in terms of human well-being. Researchers now have access to fully digitized representation of streetscapes through Google Street View (GSV), which captures the profile view of streetscapes and, thus, shares equivalent viewing angles with those of the citizen. These two facets—a wealth of streetscape photographs at city-scale and a shared perspective with the end user—underscore the potential of these data in street-level urban landscape mapping. In this study, we introduce two examples that demonstrate GSV as a high-quality data source for mapping street greenery and openness. First, the modified green view index, which estimates the visibility of street greenery, was applied to static GSV images in order to map the spatial distribution of street greenery. Second, GSV panoramas were used to quantify and map the openness of street canyons by applying a geometrical transformation and image classification to the panoramas. The results of these two novel applications of street-level photographic data illustrate its utility for quantifying and mapping key urban environmental features at the same viewpoint in which we, as citizens, experience the urban landscape.