Examining the Implementation of Activity-Friendly Zoning and Land Use Policies Through the Use of Google Street View Measures: A Pilot Study

Introduction: Pedestrian-oriented zoning and land use policies are being used by local jurisdictions as tools to implement population-level built environmental changes to create more walkable communities. There is a paucity of evidence examining whether these policies lead to actual changes in the built environment. We used Google Street View (GSV), an established, less expensive, alternative built environment data collection method, to conduct an exploratory pilot study of 19 jurisdictions to examine associations between variations in the presence of these adopted zoning policies and their corresponding specific street-level built environment features. Methods: Samples of 10 large and 9 small jurisdictions (18 municipalities and 1 county) were purposively selected on the basis of the presence of activity-friendly zoning policy provisions (sidewalks, crosswalks, bike-pedestrian connectivity, street connectivity, trails/paths, bike lanes, bike parking, and other items). Corresponding activity-friendly street-level built environment measures were constructed using GSV. Street segments in these jurisdictions were sampled using ArcGIS and stratified by type (residential and arterial) and income (high, medium, and low). Results: A total of 4363 street segments were audited across the 19 sampled jurisdictions. Results show significant differences in the presence of activity-friendly street features when the corresponding zoning policy element was addressed in New Urbanist zones/districts in the site's zoning code (eg, crosswalks, 24.48% vs 16.18%; and bike lanes, 12.60% vs 7.14%). Street segments in the middle- and high-income block groups were less likely to have activity-friendly features than low-income segments, except bike lanes. Conclusions: Results show that having activity-friendly policy provisions embedded in a jurisdiction's (municipality/county) zoning codes was associated with a greater presence of the corresponding built environmental street feature on the ground. Results suggest that the methods tested in this article may be a useful policy tool for local governments to identify high need areas that should be prioritized for built environment improvements.