The use of UAV-based laser scanning systems is increasing due to the rapid development in sensor technology, especially in applications such as topographic surveys or forestry. One advantage of these multi-sensor systems is the possibility of direct georeferencing of the derived 3D point clouds in a global reference frame without additional information from Ground Control Points (GCPs). This paper addresses the quality analysis of direct georeferencing of a UAV-based laser scanning system focusing on the absolute accuracy and precision of the system. The system investigated is based on the RIEGL miniVUX-SYS and the evaluation uses the estimated point clouds compared to a reference point cloud from Terrestrial Laser Scanning (TLS) for two different study areas. The precision is estimated by multiple repetitions of the same measurement and the use of artificial objects, such as targets and tables, resulting in a standard deviation of <1.2 cm for the horizontal and vertical directions. The absolute accuracy is determined using a point-based evaluation, which results in the RMSE being <2 cm for the horizontal direction and <4 cm for the vertical direction, compared to the TLS reference. The results are consistent for the two different study areas with similar evaluation approaches but different flight planning and processing. In addition, the influence of different Global Navigation Satellite System (GNSS) master stations is investigated and no significant difference was found between Virtual Reference Stations (VRS) and a dedicated master station. Furthermore, to control the orientation of the point cloud, a parameter-based analysis using planes in object space was performed, which showed a good agreement with the reference within the noise level of the point cloud. The calculated quality parameters are all smaller than the manufacturer’s specifications and can be transferred to other multi-sensor systems.

Purpose: The use of UAVs (Unmanned Aerial Vehicles) equipped with sensors such as laser scanners offers an alternative to conventional, labor-intensive manual measurements in agriculture, as they enable precise and non-destructive field surveys. Methods: This paper evaluates the use of UAV-based laser scanning (RIEGL miniVUX-SYS) for estimating the crop height and the plant area index (PAI) of winter wheat. (Methods) It further introduces a novel ground classification method, enhancing early growth stage classification through sensor attributes like intensity and pulse shape deviation. Results: The crop height estimation shows a high $$R^2$$ R 2 score with $$99.69~\%$$ 99.69 % but a systematically lower estimate with a mean absolute error of 7.4 cm. The potential of PAI derivation is analyzed with three different estimation strategies and provides an overview and limitations of the approach. Additional weighting based on the scan angle and the adaptation of the extinction coefficient present results with $$R^2$$ R 2 of $$97.66~\%$$ 97.66 % and a mean absolute error of 0.25. Conclusion: The investigation discusses further the impact of the calculated gap fraction, which describes the ratio of laser beams penetrating through the crop canopy in comparison to the total number of measurements.

Assessing the quality of a trajectory is a prerequisite for correctly interpreting and using the trajectory in applications such as kinematic laser scanning. Evaluation is for example done empirically by comparison with a ground-truth trajectory recorded simultaneously. Depending on the measurement and sensor configuration, both trajectories have to be aligned before comparison. Usually, either a similarity transformation or a rigid-body transformation is used for this purpose. We propose an extended spatio-temporal alignment, which additionally supports the estimation of a lever arm and a time offset between both trajectories. Our method can be used to align two trajectories of the same vehicle captured simultaneously by different sensors. We apply the approach on several recorded data sets and evaluate it empirically. We show that although real-world data sets can lead to high correlations between parameters, they can still be successfully aligned and evaluated using the methodology. To enable replication of our research, we publish the code which is available here: https://github.com/gereon-t/trajectopy.

The use of unmanned aerial vehicles (UAV) in monitoring applications is constantly increasing due to the improvement in sensor technology and the associated higher accuracy that can be achieved. As a result, UAV-based laser scanning is already being used in various deformation monitoring applications such as the monitoring of landslides or land deformations. The main challenges, which also limit the accuracy of the resulting georeferenced point cloud are given by the trajectory estimation, the measurement environment and the flight planning. Difficult conditions and high accuracy demands are especially given for the monitoring of a water dam. While the use of area-based measurements such as terrestrial laser scanning (TLS) is an already established approach for such monitoring tasks, the use of a similar technology on a platform such as a UAV is promising and investigated in this study by acquiring a single measurement epoch at a water dam. In addition to the proposal of a flight pattern for the measurements, the trajectory estimation results are evaluated in detail. Due to critical GNSS conditions, positioning errors lead to systematic shifts between single flight strips. Subsequent optimization with known control points allows the point cloud to be compared to a TLS reference. The difference between the two is shown to have a mean difference of 5 mm with a 9.2 mm standard deviation. This can be considered a highly promising result, especially as the potential for further improvement by using additional targets and sensors (e.g. camera) has been identified.

Due to recent improvements in sensor technology, UAV-based laser scanning is nowadays used in more and more applications like topographic surveying or forestry. The quality of the scanning result, a georeferenced 3D point cloud, mainly depends on errors coming from the trajectory estimation, the system calibration and the laser scanner itself. Due to the combined propagation of errors into the point cloud, the individual contribution is difficult to assess. Therefore, we propose an entire investigation of the scan characteristics of a 2D laser scanner without the use of the other sensors included in the system. The derived parameters include the range precision, the rangefinder offset as part of the range accuracy, the angular resolution capability and the multi-target capability of the RIEGL miniVUX-2UAV. The range precision is derived from amplitude values by a stochastic model, with observations fitting a theoretical model very well. The resolution capability in the angular direction is about twice the laser beam footprint size and therefore increases linearly for larger distances. Further, a new approach with the corresponding methodology for the investigation of multi-target capability is presented. The minimum distance between two targets to appear as separated echoes within a single laser beam is about 1.6 m and inliers within the measurement precision occur from 1.9 m separation distance. The scan attributes amplitude and deviation, which are computed during the online waveform processing, show a clear systematic relation to the range precision, also in cases of multiple echoes.