The role of explicit modeling for inferring traffic activity from remote sensing date

Traffic monitoring requires mobile and flexible systems that are able to extract densely sampled spatial and temporal traffic data in large areas in near-real time. Video- based systems mounted on aerial platforms meet these requirements, however, at the expense of a limited field of view. To overcome this limitation of video cameras, we develop a system for automatic derivation of traffic flow data which is designed for commercial medium format cameras with a resolution of 25-40 cm and a rather low frame rate of only 1-3 Hz. In this paper, we emphasize the benefits of utilizing an explicit approach of knowledge-based object modeling. The knowledge necessary for automatic image interpretation is modeled by a multi-layered semantic network, and a specific extraction strategy is applied to use this knowledge during object extraction. We tested the system with data of several flight campaigns to verify its applicability.