Retrieval of higher order statistical moments from full-waveform LiDAR data for tree species classification

The SND decomposition is comparable to the Gaussian decomposition regarding the decomposition accuracy (RMSE = 4.45 vs. RMSE = 3.50) and computational cost. Hence, we propose the default use of the SND decomposition, as the SND is a more flexible function, allowing for the modelling of normally distributed echoes, as well as the fitting of skewed echoes, while no limitations regarding the direction of the skewness are introduced. We attribute the difficulties in the tree species classification to the relatively wide ranges of the crown aggregated features within one species, which for some features results in a considerable overlap of the feature ranges across the species.