A citizen science toolkit to collect human perceptions of urban environments using open street view images
This provides a reusable toolkit for researchers to efficiently gather human perceptions of urban environments using open data, though it is incremental as it builds on existing methods for data processing and citizen science.
The authors tackled the challenge of using open street view imagery for research by developing an automated method for downloading, processing, and filtering these images, and applied it in a citizen science survey in Amsterdam to collect 22,637 perception ratings from 331 people.
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 an efficient 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.