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The scanning hydrographic operational airborne light detection and ranging (LiDAR) Survey (SHOALS) consists of a bathymetric LiDAR system that provides high-precision measurements of water depth. Although the acquisition is focused on depth accuracy, the return signal, i.e., waveform, contains other relevant information because of integration signatures from the water surface, the water column, and the seabed. This paper highlights the benthic characterization in extracting statistical parameters derived from the bottom backscatter and classifying them. In implementing a specific unsupervised classification, it is significantly proven that the signals derived from habitat, described as statistically homogeneous throughout ground-truth analysis, are similar within an intrahabitat view, whereas they are different between themselves.