Using Google Street View to Audit the Built Environment: Inter-rater Reliability Results

Abstract

Background: Observational field audits are recommended for public health research to collect data on built environment characteristics. A reliable, standardized alternative to field audits that uses publicly available information could provide the ability to efficiently compare results across different study sites and time. Purpose: This study aimed to assess inter-rater reliability of built environment audits conducted using Google Street View imagery. Methods: In 2011, street segments from St. Louis and Indianapolis were geographically stratified to ensure representation of neighborhoods with different land use and socioeconomic characteristics in both cities. Inter-rater reliability was assessed using observed agreement and the prevalence-adjusted bias-adjusted kappa statistic (PABAK). Results: The mean PABAK for all items was 0.84. Ninety-five percent of the items had substantial (PABAK ≥ 0.60) or nearly perfect (PABAK ≥ 0.80) agreement. Conclusions: Using Google Street View imagery to audit the built environment is a reliable method for assessing characteristics of the built environment.