Progress on methods for waveform processing and target feature inversion based on full-waveform LiDAR

Full-waveform LiDAR employs detectors with high-speed sampling and storage capabilities, expanding the information dimensions of signals by completely recording the return waveforms. In earth observation, both terrain and vegetation structural parameters (e.g., canopy height, canopy cover, leaf area index (LAI), and foliage height diversity) modulate the laser echoes, endowing this technology with the unique capability to perceive three-dimensional fine-scale surface structures and retrieve key ecological parameters. This technical advantage provides unprecedented opportunities for earth observation, significantly advancing our understanding of ecosystem function and architecture. This review systematically summarizes recent progress in full-waveform LiDAR technology, focusing on processing of echo waveform and retrieval of ecological information. Waveform processing covers waveform simulation, analytical formula, and waveform decomposition and waveform deconvolution. Retrieval methods of ecological information include waveform simulation, analytical formula, waveform decomposition, and waveform metrics. It elaborates on the origins of these methods, and their latest applications in extracting ecological parameters such as forest canopy height, aboveground biomass (AGB), LAI, clumping index, structural complexity, fuel load and canopy bulk density, burn severity, and ecosystem productivity. Finally, this review summarized the advantage and disadvantages of different methods, outline future research directions for full-waveform LiDAR feature retrieval, with particular emphasis on target identification based on waveform attributes and its emerging applications in spatial/spaceborne remote sensing.