Google street view image availability in the Bronx and San Diego, 2007-2020: Understanding potential biases in virtual audits of urban built environments.

Google Street View's 'Time Machine' feature holds promise for longitudinal street audits of built and natural environments for urban health research. As images are only available when Google collected data, differential image availability over time and place could bias audit data quality. We assessed image availability at 2000 randomly selected locations within the Bronx and San Diego from which Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants were recruited. In the Bronx, a mean of 7.4 images (95% CI: 7.2,7.5) were available at each location, and 63% of those locations had imagery in 2007 and 2019. In San Diego, fewer images were available (mean 5.4, 95% CI: 5.2,5.6) especially on minor streets (mean 4.4, 95% CI: 4.1,4.6). Image availability was more spatially clustered in San Diego (Moran's I 0.14) than the Bronx (Moran's I 0.04). Differential image availability may affect precision of neighborhood change estimates assessed by longitudinal virtual audit.