The Promise, Practicalities, and Perils of Virtually Auditing Neighborhoods Using Google Street View

Abstract

In-person audits to collect data on neighborhood characteristics offer opportunities to study the mechanisms that link neighborhood conditions to unequal outcomes for individuals and communities, but the expense and logistical difficulties associated with conducting neighborhood audits have limited their use. The images collected by Google Street View provide a promising alternative for researchers to measure neighborhood environments across cities and to examine how neighborhood conditions vary across a wider geographic scope. We describe the benefits of using “virtual” neighborhood audits and discuss the practicalities of collecting data from virtual audits. We provide an example of individual- and neighborhood-level inequality in the distribution of disorder for older adults across four cities: New York, San Jose, Philadelphia, and Detroit. Despite the promise of virtual audits, they also introduce perils that must be addressed as research progresses; we introduce and discuss those perils here.