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Technical Commission VII

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

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Across Track Distance (m)
Figure 7. a) Top view and b) profile plot of a strip of a point
cloud demonstrating the shadowing effect which increases as
scan angle increases.
flying height is a significant attenuation of the number of returns
received from the upper part of the canopy. It is evident that in-
creased above ground flying heights result in a decreased return
intensity from the top of the canopy which becomes insufficient
to trigger a return at flying heights greater than 50 m. As the Ibeo
LUX scanner has a working range of 200 m, the signal attenua-
tion is most likely due to a combination of the canopy structure
(i.e. small surface areas to trigger a return), the reflectance prop-
erties of the vegetation, the footprint size as well as the triggering
mechanism of the Ibeo LUX laser scanner. Artefacts of this at-
tenuation are still evident at flying heights below 50 m . To deter-
mine if this small amount of attenuation effects the measurement
of forest metrics, or if attenuation is occurring in all point clouds,
comparison with field measurements of tree height and canopy
properties (width and volume) is required.
Previous studies that have focused on the effect of point density
on the measurement of forest structure have suggested that in-
creased point densities result in an improved accuracy at the tree
level (Disney et al., 2010; Lovell et al., 2005). It has also been
shown that increased point density has no significant effect on
metrics derived at the stand or plot level (Tesfamichael et al.,
2010). In this study we found that decreased point density re-
duced the number of returns from the upper part of tree crowns.
This is in line with the findings of Disney et al. (2010) and Lovell
et al. (2005). However, it is also highly evident that a reduction
in point density is not contributing to the attenuation of crown
returns in the point clouds generated at higher flying heights. For
point densities between 30 and 70 point per m at the plot level
all statistics were reliably derived. Furthermore, the collection of
high density data, from a UAV platform, over a plot sized area
does not incur a significantly higher cost. As such point density
should not be a controlling factor in the design of a survey for
multi-temporal studies.
The poor quality data collected from the higher altitudes (higher
than 50 m), limited the ability to resolve the effects of scan angle
and footprint size within this study. Morsdorf et al. (2006) high-
lighted that increases in scan angle result in a reduction in canopy
penetration due the distance the beam has to travel through the
canopy and a reduction. This was also observed in the UAV gen-
erated point clouds as the shadowing effect shown in Figure 7
resulted in parts of the plot not being observed. These areas pri-
marily consisted of the lower parts of canopy and some ground
areas. This suggests that narrow scan angle ranges should be used
where possible. No effect due to footprint size was observed in
the data analysed. However, as previously discussed, it is highly
likely that large footprint sizes are contributing to the attenuation
of canopy returns with flying height.
Based on these results several recommendations for this specific
UAV- LiDAR system and for UAV-borne LiDAR systems in gen-
eral can be made. Primarily, this study shows that both flying
heights above 50 m and the use of high scan angles should be
avoided where possible. Although a different miniaturised laser
scanner may perform better at higher altitudes, the potential for
the use of UAVS is seen to be most beneficial at the plot level.
As individual plots can be surveyed at flying heights below 50
m within a single flight, this recommendation holds for all UAV
surveys at this scale. Furthermore, the spatial accuracy of the
generated point clouds suggests the fusion of forward and back-
ward transects is a feasible option to further restrict the scan an-
gles used within lower altitude flights. In the case of this study,
a 12.62 m radius circular plot is the primary area of interest. To
completely cover this area a flying height of 20 mabove the tree
height, would theoretically allow the entire plot to be covered
with a maximum scan angle of 17.5 °. Whereas this could be
reduced to 12 °if the point clouds collected from forward and re-
verse transects were used to generate a single point cloud, while
insuring 50% overlap.
This study has shown that with correctly chosen flying condi-
tions, statistics which have been shown to be related to key for-
est metrics can be derived with high repeatability from UAV-
borne LiDAR systems. This suggests that any changes in for-
est structure, such as a loss of biomass due to disease or prun-
ing, should be observable from multi-temporal surveys. One of
the primary advantages of a UAV-system is an ability to fly on-
demand. Therefore, the UAV can be used to assess a number of
the dynamics which are important in modern forestry manage-
ment. For example, an assessment of biomass loss due to disease
could be tracked through time. Another advantage of UAV sys-
tems is their ability to generate very high resolution datasets. Al-
though it has not been a focus of this study, the measurement
of forest structure at the tree level is highly feasible with this
platform and requires further investigation. Such analysis could
aid studies into carbon modelling and the calibration of full scale
data. Furthermore, the use of return intensity as an indicator of
forest structure is becoming an important tool in forestry man-
agement (Garcia et al., 2010). The use of a UAV-borne scanners
limits the range and atmospheric effects in the measurement of
intensity. This suggest that UAV-borne intensity metrics could be
more accurate than similar full scale metrics.
In conclusion, the mapping of forest structure using the TerraLuma
UAV-borne LiDAR system has been demonstrated to be feasible
at the plot level. There are a number of potential uses for UAV-
borne LiDAR within forest management some of which will be
the focus of the research with this system. However, the next
stage of this research will focus on the comparison and calibra-
tion of the tree level metrics with ground inventory data.
Disney, M., Kalogirou, V., Lewis, P., Prieto-Blanco, a., Han-
cock, S. and Pfeifer, M., 2010. Simulating the impact of
discrete-return lidar system and survey characteristics over
young conifer and broadleaf forests. Remote Sens. Environ.
114(7), pp. 1546-1560.
Donoghue, D., Watt, P., Cox, N. and Wilson, J., 2007. Remote
sensing of species mixtures in conifer plantations using Li-
DAR height and intensity data. Remote Sens. Environ. 110(4),
pp. 509-522.