Citywide vs. Neighborhood Measures: Understanding the Differences of Safety Perceptions of the Built Environment using GeoAI and Survey - the case of Stockholm, Sweden

Keywords: Safety perception, built environment, street view image, GeoAI, perception bias
Abstract Type: Paper Abstract

Abstract

The safety perception of the built environment, rather than the sheer number of crimes and incivility behavior, is a fundamental driver of public policies intended to improve urban safety. Traditional surveys often capture neighborhood residents’ perceived safety, but may not fully reflect the perceptions of people who are unfamiliar with the area. In this study, focused on the city of Stockholm, Sweden, we develop a geospatial artificial intelligence (GeoAI) approach using street view images to create a measure of citywide residents’ safety perceptions. Our aim is to compare the measures from the localized survey with those from the GeoAI approach to better understand the relationship between these safety measures. We model the two forms of safety perceptions as a function of the city’s land use and its socio-demographics. Results indicate that while the GeoAI-based measures tend more express people’s instant impressions of the built environment across the city, the survey-based measures condense and reflect their overall daily experiences of specific areas. The study concludes by critically assessing the potential ethical issues in the proposed methodology and making suggestions for future practical research.