Full-waveform is becoming increasingly available in today's LiDAR systems and the analysis of the full return signal can provide additional information on the reflecting surfaces. In this paper we present the results of an assessment on full-waveform analysis, as opposed to the more classic discrete return analysis, for discerning vegetation cover classes related to post-fire renovation. In the spring of 2011 an OPTECH ALTM sensor was used to survey an Alpine area of almost 20 km2 in the north of Italy. A forest fire event several years ago burned large patches of vegetation for a total of about 1.5 km2 . The renovation process in the area is varied because of the different interventions ranging from no intervention to the application of re-forestation techniques to accelerate the process of re-establishing protection forest. The LiDAR data was used to divide the study site into areas with different conditions in terms of re-establishment of the natural vegetation condition. The LiDAR survey provided both the full-waveform data in Optech's CSD+DGT (corrected sensor data) and NDF+IDX (digitizer data with index file) formats, and the discrete return in the LAS format. The method applied to the full-waveform uses canopy volume profiles obtained by modelling, whereas the method applied to discrete return uses point geometry and density indexes. The results of these two methods are assessed by ground truth obtained from sampling and comparison shows that the added information from the full-waveform does give a significant better discrimination of the vegetation cover classes.
Waveform analysis for the extraction of post-fire vegetation characteristics
PIROTTI, FRANCESCO;GUARNIERI, ALBERTO;VETTORE, ANTONIO
2012
Abstract
Full-waveform is becoming increasingly available in today's LiDAR systems and the analysis of the full return signal can provide additional information on the reflecting surfaces. In this paper we present the results of an assessment on full-waveform analysis, as opposed to the more classic discrete return analysis, for discerning vegetation cover classes related to post-fire renovation. In the spring of 2011 an OPTECH ALTM sensor was used to survey an Alpine area of almost 20 km2 in the north of Italy. A forest fire event several years ago burned large patches of vegetation for a total of about 1.5 km2 . The renovation process in the area is varied because of the different interventions ranging from no intervention to the application of re-forestation techniques to accelerate the process of re-establishing protection forest. The LiDAR data was used to divide the study site into areas with different conditions in terms of re-establishment of the natural vegetation condition. The LiDAR survey provided both the full-waveform data in Optech's CSD+DGT (corrected sensor data) and NDF+IDX (digitizer data with index file) formats, and the discrete return in the LAS format. The method applied to the full-waveform uses canopy volume profiles obtained by modelling, whereas the method applied to discrete return uses point geometry and density indexes. The results of these two methods are assessed by ground truth obtained from sampling and comparison shows that the added information from the full-waveform does give a significant better discrimination of the vegetation cover classes.File | Dimensione | Formato | |
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