Introduction:Various built environment factors might influence certain health behaviors and outcomes. Reliable, resource-efficient methods that are feasible for assessing built environment characteristics across large geographies are needed for larger, more-robust studies. This paper reports the item response prevalence, reliability, and rating time of a new virtual neighborhood audit protocol, drop-and-spin auditing, developed for assessment of walkability and physical disorder characteristics across large geographic areas.Methods: Drop-and-spin auditing, a method where a Google Street View (GSV) scene was rated by spinning 360° around a point location, was developed using a modified version of the virtual audit tool CANVAS. Approximately 8,000 locations within Essex County, New Jersey were assessed by 11 trained auditors. Thirty-two built environment items per a location within GSV were audited using a standardized protocol. Test-retest and inter-rater κ statistics were from a 5% subsample of locations. Data were collected in 2017-2018 and analyzed in 2018.Results: Roughly 70% of GSV scenes had sidewalks. Among those, two thirds were in good condition. At least five obvious items of garbage or litter were present in 41% of GSV scenes.