A citizen science toolkit to collect human perceptions of urban environments using open street view images
Matthew Danish, S.M. Labib, Britta Ricker, Marco Helbich
Abstract
Street View Imagery (SVI) is a valuable data source for studies (e.g., environmental assessments, green space identification or land cover classification). While commercial SVI is available, such providers commonly restrict copying or reuse in ways necessary for research. Open SVI datasets are readily available from less restrictive sources, such as Mapillary, but due to the heterogeneity of the images, these require substantial preprocessing, filtering, and careful quality checks. We present a method for automated downloading, processing, cropping, and filtering open SVI, to be used in a survey of human perceptions of the streets portrayed in these images. We demonstrate our open-source reusable SVI preparation and smartphone-friendly perception-survey software with Amsterdam (Netherlands) as the case study. Using a citizen science approach, we collected from 331 people 22,637 ratings about their perceptions for various criteria. We have published our software in a public repository for future re-use and reproducibility. • Studies using commercial street view imagery have proliferated despite licensing terms. • We built a workflow and webapp to collect perceptions of open street view imagery. • The webapp presents a simple and consistent interface with a swipe-to-rate UI. • Our data preparation methods and mobile-friendly survey are open, FAIR and reusable. • Anyone may easily clone, modify & deploy this perception survey in any desired place.