Abstract
This study reports on a low-cost unmanned aerial vehicle (UAV)-borne light detection and ranging (LiDAR) system called LasUAV, from hardware selection and integration to the generation of three-dimensional point clouds, and an assessment of its performance. Measurement uncertainties were estimated in angular static, angular dynamic, and real flight conditions. The results of these experiments indicate that the point cloud elevation accuracy in the case of angular static acquisition was 3.8 cm, and increased to 3.9 cm in angular dynamic acquisition. In-flight data were acquired over a target surveyed by nine single passages in different flight directions and platform orientations. In this case, the uncertainty of elevation ranged between 5.1 cm and 9.8 cm for each single passage. The combined elevation uncertainty in the case of multiple passages (i.e., the combination of one to nine passages from the set of nine passages) ranged between 5 cm (one passage) and 16 cm (nine passages). The study demonstrates that the positioning device, i.e., the Global Navigation Satellite System real-time kinematic (GNSS RTK) receiver, is the sensor that mostly influences the system performance, followed by the attitude measurement device and the laser sensor. Consequently, strong efforts and greater economic investment should be devoted to GNSS RTK receivers in low-cost custom integrated systems.
Highlights
Laser scanning (LS), referred to as light detection and ranging (LiDAR), is a well-established and consolidated technology used extensively for environmental sciences
As an airborne laser scanning (ALS) system, the principle of measurement of unmanned aerial vehicle (UAV)-borne laser scanning is based on laser-ranging measurements supported by position and orientation information derived with the use of a Global Navigation Satellite System (GNSS) device and an inertial navigation system (INS) mounted on a drone (Figure 1)
This paper describes the development of a UAV laser scanner system, including the process for generating 3D point clouds based on the precise UAV position and orientation
Summary
Laser scanning (LS), referred to as light detection and ranging (LiDAR), is a well-established and consolidated technology used extensively for environmental sciences. ALS provides data for research and operational applications related to the management of forest ecosystems, data for forestry applications are often not acquired by dedicated flights, but are generated as a byproduct of the above-mentioned campaigns (i.e., land planning and monitoring). They are frequently characterized by a low point density and, above all, are usually acquired in winter to minimize the disturbance of vegetation [4], leading to a systematic, significant tree height underestimation [5]. ALS in forestry is only affordable for large-scale continuous forest cover (e.g., Canada, USA, Scandinavian countries) and is less convenient where the forest cover is fragmented, as in most European countries
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