A citizen science toolkit to collect human perceptions of urban environments using open street view images

TL;DR

This paper introduces an open-source toolkit for processing open street view images and conducting citizen science surveys to gather human perceptions of urban environments, demonstrated through a case study in Amsterdam.

Contribution

It provides an efficient, automated method for preparing open street view imagery and a smartphone-friendly survey tool, enabling scalable perception studies.

Findings

Collected 22,637 perception ratings from 331 participants

Published software for image processing and surveys for future research

Demonstrated feasibility in a real urban environment (Amsterdam)

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 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.