International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
that the differences between samples in different sectors is
significant over sector 1 (forest) and the other sectors. Sector 3 is
also significantly different from the other sectors except sector
2. This can be explained on the fact that the area in sector 3 has
stems of deadwood standing, thus the height distribution is
different from the other sectors, where all stems were cut down.
The method was not able to discriminate between sectors 2, 4
and 5. The low vegetation present and the sample area size do
not bring enough height variance between them for
discrimination. A solution could be to use smaller sample plots
over more representative spots, avoiding the inclusion of a large
percent of bare ground in the plot. A stratified sampling
procedure using image interpretation could be used to segment
an image masking the ground area.
SI S2 S3 S4 S5
S1 | - 0;56* 046% 043* 0:32*
S2 - 0.36 0.19 0.12
S3 - 0.41* 0.47*
S4 - 0.11
S5 -
*Indicates a significant difference in distributions at a — 0.05
Table 3. Characteristics of the four test sectors.
Figure 4. Top — 3D view of plot without ground returns — the
scale reports the intensity in 8 bit scale. Bottom - four slices
from the voxel grid reporting digitizer counts of waveform.
526
Another factor to consider is that the sampling of the waveform
occured with a nominal threshold which was chosen according
to the observed values. This was possible because we worked on
a single survey and thus the survey characteristics which
influence the outgoing energy for every pulse — thus the return
energy loss — where relatively constant (relative flying height,
pulse frequency). A more objective method would be to
calculate only the segment with Full Width at Half Maximum
(FWHM) criteria.
4. CONCLUSIONS
The results are part of a more in-depth investigation for
evaluating methods for discriminating low vegetation
distribution over land for defining the effect of re-forestation
methods in a broader ongoing project which investigates
vegetation dynamics in areas which have been part of a severe
fire event. A positive result over the sampled areas will enable
to apply the method and evaluate results over larger areas to test
for robustness. The proposed modifications mentioned in the
discussion will be applied to test for improved results. The final
objective is to provide a method to segment 3D space into
significant information using waveform data.
5. ACKNOWLEDGEMENTS
This work is part of the CPDA097420 project funded by the
University of Padua: "Disturbi naturali in foreste alpine:
approccio multiscala e applicazioni LiDAR", scientific
coordinator prof. Emanuele Lingua.
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