Investigating influence of UAV flight patterns in multi-stereo view DSM accuracy

Abstract

Current advancements on photogrammetric software along with affordability and wide spreading of Autonomous Unmanned Aerial Vehicles (AUAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance of flight patterns and large overlaps in aerial triangulation and Digital Surface Model (DSM) production from large format aerial cameras is well documented in literature, this is not the case for AUAV photography. This paper assess DSM accuracy of models created using different flight patterns and compares them against check points and Lidar data. Three UAV flights took place, with 70%-65% forward and side overlaps, with West-East (W-E), North-South (N-S) and Northwest-Southeast (NW-SE) directions. Blocks with different flight patterns were created and processed to create raster DSM with 0.25m ground pixel size using Multi View Stereo (MVS). Using Lidar data as reference, difference maps and statistics were calculated for each block, in order to evaluate their overall accuracy. The combined scenario performed slightly better that the rest. Because of their lower spatial resolution, Lidar data prove to be an inadequate reference data set, although according to their internal vertical precision they are superior to UAV DSM. Point cloud noise from MVS, is considerable in contrast to Lidar data. A Lidar data set from a lower flying platform such as helicopter might have been a better match to low flying UAV data.