Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data

When processing scanning LiDAR data, it is commonly assumed that the extracted full-waveform LiDAR pulse registers truly vertical information of forest canopies. This assumption may lead to uncertain results for the spatiotemporal analysis of the waveforms due to off-nadir scanning angles and varying trajectories travelled by the pulses in overlapping strips. In this letter, we investigate these assumptions and undertake some preliminary analysis to overcome their impacts on forest-based LiDAR analyses. Our results demonstrate that for a standard LiDAR forest acquisition programme in Oregon, USA, most of the hits (83%) are acquired off-nadir, which leads to positional displacements on the ground of the full-waveforms of about 0.20m for each 1-m height increment. We propose an approach to synthetize multiple waveform data into composite waveforms containing the vertical profile of vegetation for a given location. This approach is based on partitioning the aboveground vertical space into voxels and using the maximum full-waveform intensity value to construct new full-waveforms comprising the vertical information of the various waveforms crossing over a location. Our initial results indicate that deriving spatiotemporal metrics from the composite pseudo-vertical full-waveforms produces a more consistent response across adjacent height levels, which in turn enables a more complete characterization and more vegetation structure to be retrieved. We conclude that this type of pseudo-vertical full-waveform analysis is necessary to more fully understand the impact of the return signals from tree crowns.