Mapping quality prediction for RTK/PPK-equipped micro-drones operating in complex natural environment
Emmanuel Clédat, Laurent Valentin Jospin, Davide A. Cucci, Jan Škaloud
Abstract
Drone mapping with GNSS-assisted photogrammetry is a highly efficient method for surveying small- or medium-sized areas. However, the mapping quality is not intuitively predictable, particularly in complex environments (with steep and cluttered terrain), in which the quality of the real-time kinematic (RTK) or post-processed kinematic (PPK) positioning varies. We present a method to predict the mapping quality from the information that is available prior to the flight, such as the flight plan, expected flight time, approximate digital terrain model, prevailing surface texture, and embedded sensor characteristics. After detailing the important considerations, we also present the concept of global precision within the context of minimal and efficient ground control point placement in a complex terrain. Finally, we validate the proposed methodology by means of rigorous statistical testing against numerous experiments conducted under different mapping conditions.