The use of UAV photogrammetry compared to LiDAR for forest reconstruction; A comparison of different UAV photogrammetry protocols

Abstract
With the increasing pressure of climate change and human activity on forest areas, the need to monitor them increases. Therefore, the possibility of using UAV photogrammetry instead of LiDAR to monitor forest areas in a more accessible way is researched. This is done by comparing different UAV photogrammetry protocols to a forest reconstruction made with LiDAR. The influence of flight height (60m and 100m), flight path (longitudinal and transversal), sideway overlap (60% and 80%) and camera angle (nadir and smart-oblique) of the UAV flight on the resulting photogrammetry point cloud is determined by calculating cloud to cloud distances. Also the optimal flight protocol for the photogrammetry is determined, based on the cloud to cloud distances between the LiDAR and the photogrammetry point clouds, the measured canopy height and the canopy cover. From these measurement it was determined that a flight at 100 meters height, with a sideway overlap of 80%, a nadir camera angle and a longitudinal flight path was most accurate compared to the LiDAR. When a high point density and completeness of the resulting point cloud is required however, the flight with a combination of a longitudinal and transversal flight path and a combination of the two flight heights or the smart-oblique camera angle is optimal. Lastly, it was studied whether forest density influences the accuracy of the photogrammetry point cloud. This was done by comparing forest areas with low, medium and high forest density within the research area to the LiDAR point cloud. It was concluded that the forest density does influence the accuracy of the point cloud, but differently for each measurement. Overall, it is concluded that photogrammetry can be used instead of LiDAR to make a forest reconstruction, but that the influence of the flight parameters on the output should be taken into consideration, as these can largely influence the results.