Maps power so many applications and services in sectors ranging from transportation to agriculture to social media. However, there are few well-documented approaches for evaluating map quality. How can developers determine if a map is well-suited for their use case? In this post, Clare Corthell and Mark Huberty discuss how Lyft assessed OpenStreetMap (OSM) through a methodology that combines remote sensing with cluster-sampled ground truth data collection. Their findings indicate the OSM has a high-quality road network in major North American cities, although discrepancies with ground truth arise due to recent changes (in the real world) and turn restriction and lane data may be less accurate.