Accuracy Assessment of Different Unmanned Aerial Vehicles (UAV) and its Application Compared with RTK GNSS Network
Nowadays UAVs are a rapidly evоlving technоlоgy with pоtential fоr different surveying and measurement purpоses. The broad definition covers balloons, kites, gliders, airships, rotary and fixed wing UAVs with the capability for photogrammetric data acquisition in manual, semi-automated and automated flight mode. With assorted embedded sensоrs, UAVs can prоvide data frоm their surrоundings with a capability tо easily reach places that can оtherwise be difficult tо measure and generate sub-meter level, timely and cloud free remote sensing products.
In this work, an evaluating accuracy of unmanned aerial vehicles was introduced. A raw uncalibrated aerial image acquired from a non-metric digital camera which carried by an UAV normally has lens and perspective distortions and could not be used directly without undergoing image rectification. The most important approach for non- parametric aerial image rectification were used Ground control points (GCPs) features. University of Sopron established a test field for UAVs. This test field enables us to assess the flight performance of various UAV systems and the same time around 50 high accurate grid Ground Control Point (GCP) that allow us to evaluate the accuracy of our non-metric camera.The results demonstrate that accurate initial positions and the number and distribution of ground control points become the main influencing parameters in reducing the deformation in the block adjustment processes.
The research showed that a drone-based measurement system for outdoor material fields is a feasible and practically working concept. The system can produce very accurate and timely results, being capable of replacing more traditional measurement methods. The system is limited by being dependent on good weather conditions and by having lack of automation in some parts of its workflow. The research as a whole was limited by its approach of pilot testing, which could make some of the results not generalizable.
Keywords: UAV, photogrammetry, structure from motion, accuracy assessment, block adjustment, RTK GNSS, empirical error measurement, IMU.