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Forest structure is defined as the horizontal and vertical distribution of the vegetation elements (Kükenbrink et al., 2017). Its significance is visible on different factors such as biodiversity and spreading of wildfires. For the latter, fire behavior may be modeled through fire models. To do this, input parameters representing the forest structure and fuel properties are required (García et al., 2011). The use of more recent and detailed 3D fire behavior models based on computational fluid dynamics methods, require more information about the heterogeneity of vegetation fuels in the different vertical strata (Mell et al., 2011). In this sense, discrete airborne laser scanning (ALSD) has been successfully used to characterize forest structure and fuel properties (Hevia et al., 2016). More specifically, full-waveform airborne laser scanning (ALSFW) goes one step further and registers the complete signal response from the different vertical strata (Mallet and Bretar, 2009). Nevertheless, its use has been limited due to three main points: (i) unknowledge of data, (ii) large amount of data, and (iii) lack of processing tools. The main objective of this thesis was the development of processing and analysis methods based on full-waveform airborne laser scanner data to characterize the vertical forest structure, in particular, the understory vegetation. Moreover, six more specific objectives are also described and addressed in the next paragraphs.

Processing and analysis of airborne fullwaveform laser scanning data for the characterization of forest structure and fuel properties