PROCESSING OF UAV BASED RANGE IMAGING DATA TO GENERATE DETAILED ELEVATION MODELS OF COMPLEX NATURAL STRUCTURES

Abstract. Unmanned Aerial Vehicles (UAVs) are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters) UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps.

In this paper we will describe a UAV platform, which can carry a range imaging (RIM) camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies) carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre level. The RIM data indicated a high noise level in the measured distance image, due to the vibrations caused by the flight system. Multi-image processing reduced the noise level of the distance image. The produced elevation models from a test area show the high potential of the proposed method for complex structures such as riverbeds.