The real-time evolution of the direct georeferencing UAV ecosystem BY JOE HUTTON
W
hile mapping using uncrewed aerial vehicles (UAVs or drones) has proven to be a relatively cost-effective method to collect high-accuracy spatial information, there are still a number of bottlenecks that make them tricky to use. These include the complexities and cost of acquiring, setting up and surveying with a global navigation satellite system (GNSS) base station and ground control points (GCPs); dealing with unreliable differential corrections being sent to the drone; mixed datums between base station coordinates and GCPs; the awkward workflow steps of having to retrieve recorded base station data and process that data with the recorded GNSS data in the drone; having to deal with the increased cost of long base to drone separations for Beyond Visual Line of Sight (BVLOS) mapping; and the list goes on. Given these challenges, the ability to fly anywhere, anytime, and to efficiently and quickly deliver high-accuracy, reliable map products literally with a push of a button may seem like a farfetched dream. However, the technology to enable these capabilities is fast emerging. Current advancements are focused on embedding compact direct georeferencing (DG) systems comprised of survey-grade GNSS and inertial hardware that deliver real-time centimeter positioning and highly accurate roll, pitch, and heading measurements using satellite-based GNSS corrections to enable “mapping anywhere” with little or no ground infrastructure. Not only can such DG systems enable mapping to be done with no or at least fewer
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GCPs, they enable the integration of camera, lidar and hyperspectral sensors into single mapping payloads with real-time or in-the-field generation of map products. The combination of these features, with the addition of improved in-field capabilities and licensing, opens the door for smaller, lighter, higher performing solutions and real-time, in-thefield actionable data.
ATTITUDE ADJUSTMENTS
Whether direct or indirect, georeferencing is required to geocode data collected by cameras, lidar, and other sensors to create maps and hence geospatial information. With UAVs, the data can be collected at a higher resolution and more quickly than from