Commercial feasibility of traffic data collection using satellite imagery

Requests to market remote sensing data at fine spatial resolutions have been proposed. We evaluated the potential of complementing traffic data collection programs with such data. One of the most fundamental issues is the imaging resolution required to identify vehicles on a highway. We simulated the performance of three spatial resolutions (1.0 m, 2.1 m and 4.2 m) by processing aerial photography (0.4–0.7 μm) of the Columbus, Ohio, area. The imagery was used to count and classify two groups of vehicles—large trucks and smaller vehicles—on several highway segments. We found that the 1.0 m resolution performed significantly better than the coarser resolutions for correctly identifying vehicles. We also investigated the coverage of an orbiting satellite for imaging highways. We find that a 1‐m resolution satellite would cover approximately 1% of the highways in the continental U.S. per day.