Abstract
Abstract. Surveying an area with small, unoccupied aerial systems (UAS) equipped with a lidar mapping payload—absent permanent, stable, geometrical reference surfaces—demands accurate, repeatable data collection procedures. While relative error within a single UAS lidar dataset may reveal itself in strip misalignment, absolute error (particularly horizontal error) can prove more difficult to detect, casting doubt upon the quality of both individual surveys and time change analyses of multiple surveys of the area. To gain insight on the UAS lidar error budget, this study presents an analysis of multiple UAS lidar surveys over a set of accurately surveyed geometric checkpoints. Each flight’s trajectory was processed multiple times using multiple static GNSS base observations, both autonomous and set over surveyed monuments, at varying distances from the study site. Custom algorithms were used to mensurate the geometric targets detected in each UAS lidar survey's point cloud, allowing for precise comparison of both absolute horizontal and vertical accuracy of each survey against the rigorous ground survey. The results of the analysis suggest that high horizontal accuracy can be achieved under a variety of conditions, whereas vertical accuracy is sensitive to the quality of ground control. and a discussion of the results explores the ultimate goal of isolating and understanding the sources and magnitudes of error in the UAS lidar error budget.
Highlights
The popularity of unoccupied aerial systems (UAS) lidar mapping continues to grow, implying a growing reliance upon the method in both research and industry
The primary objective of this study is to present a method of analysing the absolute accuracy of a UAS lidar point cloud which accounts for the issues mentioned above, and to apply the method to the UAS lidar mapping system on hand (Section 2.2)
The site was chosen for safety of operations, ease of access, open skies for quality of GNSS observations, and the large available area. (One of the study objectives was to ascertain the absolute accuracy of a typical UAS lidar survey; the flights were designed to have flight lines of reasonable length.)
Summary
The popularity of UAS lidar mapping continues to grow, implying a growing reliance upon the method in both research and industry. For many UAS lidar surveys, two of the main components used are considered survey-grade (i.e highly accurate, tactical-grade IMUs and geodetic-grade GNSS receivers); some of the commonly used lidar sensors, such as the Velodyne family of rotating multibeam sensors, are relatively inexpensive and known to researchers as noisy and unstable to a degree which may preclude one from asserting that a UAS lidar mapping product is survey grade. While the main source of error may be the sensor, ascertaining the absolute accuracy of a UAS lidar system must be approached holistically, examining the effects of the static GNSS base station, the trajectory solution, and the resulting point cloud characteristics. Analyzing the accuracy of a lidar point cloud typically relies upon flat, rigid surfaces visible in the study area, such as roofs or paved surfaces. As the method gains popularity in forestry, geomorphology, and ecology, to name a few, the likelihood decreased of human-made reference structures existing in the scene
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