To guarantee that LiDAR data is accurately georeferenced, direct georeferencing is essential, utilizing a precise GNSS receiver and an inertial measurement unit (IMU) that measures the posture (orientation and positioning) of the LiDAR sensor. The LiDAR sensor has a range error; the GNSS has a horizontal and vertical position error; the INS has an angular roll, tilt and heading error; the displacements of the GNSS antennas have a distance error and the LiDAR sensor in relation to the INS has an angular displacement error. The lack of LIDAR information from UAVs in the upper part of the canopy had a much greater impact on the accuracy of estimating the structural and functional traits of grasslands than in the lower part of the canopy. The following table shows the LiDAR point density recommended by the American Society for Photogrammetry and Remote Sensing (ASPRS) for terrain mapping with LiDAR.
Among the five characteristics of grasslands, aerial biomass was the least affected by the loss of LIDAR information from UAVs. With a decrease in information loss in tree crowns, the LIDAR UAV can be used to extract structural and functional features from grasslands with an accuracy comparable to that of TLS. There is an ongoing discussion in the UAV LiDAR community about accuracy, what it means and how significant it really is. However, in grassland ecosystems, it is more likely to be influenced by the loss of LIDAR information from UAVs caused by dense vegetation canopies.
The relative accuracy of LiDAR refers to the internal quality of LiDAR elevation data without using inspected ground control points. It describes UAV LiDAR technology, how it compares to alternative techniques, its advantages, and its best use cases. The average loss of height of the LIDAR of UAVs at the tops of the peaks exceeded 0.30 m, and the average relative height loss exceeded 49%, compared to a value of 0.03 m and 6% at the bottom of the canopies. For instance, accuracy requirements for LiDAR data for detailed design infrastructure such as a dam may be higher compared to LiDAR data for agriculture.