Voxelization of full waveform LiDAR data for fusion with Hyperspectral Imagery

Abstract

Current research into the fusion of Hyperspectral Imagery (HI) and full waveform LiDAR (Light detection and ranging) has relied on first processing the full waveform LiDAR (FWL) data to a set of discrete returns before combining. However, more information about target properties can potentially be recovered if the raw waveform is preserved in the fusion with HI. This paper proposes a voxelization method to fuse raw FWL data with HI by dividing the waveform data into voxels, and then synthesizing all waveforms which intersect a voxel into one 3D superposition waveform. The efficacy of this method is evaluated by comparing the synthesized waveform with an actual nadir LiDAR waveform from the voxel of interest. Results show that this method of voxelizing and fusion of FWL data can preserve raw waveform characteristics while effectively representing the FWL data on a 3D raster basis that can be directly co-registered with the HI.