Airborne traffic monitoring in large areas using LiDAR data – theory and experiments WEI YAO ∗ †, MENG ZHANG†, STEFAN HINZ‡ and UWE STILLA† † Photogrammetry and Cartography, Technische Universität München, 80333 München, Germany ‡ Remote Sensing and Computer Vision, Universität Karlsruhe, 76131 Karlsruhe, Germany This article investigates the theoretical background for airborne LiDAR (light detection and ranging) and ALS (airborne laser scanning) systems that are used to monitor traffic from airborne platforms. An object moving with a velocity devi- ating from the assumptions incorporated in the scanning process will generally appear both stretched and sheared – motion artefacts. To study the impact of these deformations on the ALS data, the analytic relations between an arbitrarily mov- ing object and its conjugate in the ALS data have been examined and adapted to concrete airborne specifications. Furthermore, a complete scheme is proposed to analyse urban traffic in real-life situations, which combines vehicle detection suc- cessively with the motion classification method, which is the main focus of this article. Finally, the velocity of the moving vehicle can be derived with knowledge about the vehicle shape. The experimental results obtained by using real ALS data were assessed with respect to the reference data concurrently acquired by a video camera to validate the theory. 1. Introduction Transportation represents a major segment of the economic activities of modern soci- eties, which leads to adverse impacts on our environment, so increase in transport safety and efficiency and reduction in air and noise pollution are the main concerns of the future (Hinz et al . 2006, Rosenbaum et al . 2008). The automatic extraction, char- acterization and monitoring of traffic using remote-sensing platforms is an emerging field of research. Approaches rely not only on airborne video but also on nearly the whole range of available sensors (Gierull 2004, Kirchhof and Stilla 2006, Sharma et al . 2006, Jin and Davis 2007, Hinz et al . 2008). The principal argument for the utilization of such sensors is that they complement stationary data collectors in the sense that they not only deliver local data but also observe the traffic situation over a larger region. Finally, the measurements derived from the various sensors could be fused through the assimilation of traffic flow models. Traffic monitoring based on optical satellite systems, however, is only possible dur- ing the day and under cloud-free conditions. Besides SAR systems (Meyer et al . 2006, Suchandt et al . 2010), airborne LiDAR (light detection and ranging) and ALS (air- borne laser scanning) can work during night-time and have the ability to penetrate the clouds. Yet, there are other difficulties inherent in the ALS process that must be