Urban visual intelligence: Uncovering hidden city profiles with street view images.
Ontology highlight
ABSTRACT: A longstanding line of research in urban studies explores how cities can be understood through their appearance. However, what remains unclear is to what extent urban dwellers' everyday life can be explained by the visual clues of the urban environment. In this paper, we address this question by applying a computer vision model to 27 million street view images across 80 counties in the United States. Then, we use the spatial distribution of notable urban features identified through the street view images, such as street furniture, sidewalks, building façades, and vegetation, to predict the socioeconomic profiles of their immediate neighborhood. Our results show that these urban features alone can account for up to 83% of the variance in people's travel behavior, 62% in poverty status, 64%
SUBMITTER: Fan Z
PROVIDER: S-EPMC10319000 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
ACCESS DATA