Processing and analysis of airborne full-waveform laser scanning data for the characterization of forest structure and fuel properties

P. Crespo-Peremarch, L. A. Ruiz


This PhD thesis addresses the development of full-waveform airborne laser scanning (ALSFW) processing and analysis methods to characterize the vertical forest structure, in particular the understory vegetation. In this sense, the influence of several factors such as pulse density, voxel parameters (voxel size and assignation value), scan angle at acquisition, radiometric correction and regression methods is analyzed on the extraction of ALSFW metric values and on the estimate of forest attributes. Additionally, a new software tool to process ALSFW data is presented, which includes new metrics related to understory vegetation. On the other hand, occlusion caused by vegetation in the ALSFW, discrete airborne laser scanning (ALSD) and terrestrial laser scanning (TLS) signal is characterized along the vertical structure. Finally, understory vegetation density is detected and determined by ALSFW data, as well as characterized by using the new proposed metrics.


LiDAR; terrestrial laser scanning; forest fuel; understory vegetation; processing tool

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