International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
area surveyed, average canopy height was about 45 meters and
tree density about 280 stems/hectare.
Two points should be noted: (1) there appears to be little mean
offset irrespective of the tree density which implies that the at
the sub-meter level, the ground is being detected, and (2) the
RMSE grows with increasing tree density from about 1.3 meters
to 3.3 meters.
Similar lidar comparisons with truth indicated a bare lidar
RMSE of 0.5 meters in the uncut stand. This enables us to use
the lidar results with some confidence over the remainder of the
area. |n Figure 9 we summarize the (P-Band — Lidar)
differences for various tree height classes and for three slope
classes. We note that the tree height estimates are based upon
(X - P) height differences, which will therefore underestimate
the true heights as noted earlier. Moreover, they are likely to
underestimate the true heights increasingly as tree density is
reduced. This is not accounted for in this figure. The major
points to be observed are:
(1) (P-Band DTM - Lidar) RMSE increases with tree
height (from 1.6 to about 3.2 meters for moderate
slopes) with the larger error corresponding to tree
heights (after correction) greater than 45 meters.
2) (P-Band DTM - Lidar) RMSE increases with slope
for all tree height classes ( by 30% - 50% for the
largest slopes.
(3) These results are consistent with the ground survey
results
(4) Although not shown here, there is no consistent mean
offset that is dependent upon tree height. However
there appears to be a persistent increase of mean
offset with increasing slope.
P-Band RMSE vs. Tree Height
BSlope « 10*
910" « Slope « 20"
OSlope > 20°
(P-Band ~ Lidar) RMSE (m)
15-25
Tree Height (m)
Figure 9. (P-Band DTM - Bare Lidar) RMSE as a function of
tree height and for three slope categories («10 degrees, (10 —
20) degrees, and >20degrees). Tree height classes are
underestimated (see text) and show intervals (0-5), (5-15), (15-
25), (25-35) and >35 meters.
5. DISCUSSION AND CONCLUSIONS
This presentation has focussed on what the author believes are
two of the more important ‘events’ that have occurred in the
past few years, at least as seen from the perspective of
commercial airborne IFSAR and its growth and contribution to
mapping.
The first event was the demonstration of a mapping program on
a national scale - NextMap Britain - with the capability to
846
create DEMs with meter to sub-meter accuracy, posted at 5
meter intervals. The validation exercises described, one of
which is perhaps the most extensive to be conducted by the
mapping industry, would suggest that the ability of airborne
IFSAR to contribute to a mainstream mapping activity has been
well and satisfactorily demonstrated. Moreover, the economic
model described is such that it makes DEM data of mapping
quality, available to organizations and individuals at prices that
should promote its use to a greater extent than previously seen.
This in turn should further the growth of applications based
upon three-dimensional input. While we have in this paper
emphasized IFSAR-derived DEMs it is our belief that they are
complementary to the other technologies both space-borne and
airborne. The expectation is that we will see increased merging
of airborne IFSAR with other data sources in order to optimize
the solutions that users require.
The second event, is the demonstration of bare-earth DEMs
beneath significant closed forest canopy derived from fully-
polarized P-Band IFSAR. Together with X-Band as a proxy for
tree height, this appears to offer the possibility of creating
biomass maps and forest fuel mapping implementation (see
Andersen, et. al. (2004)). To date there have not been many
examples of long wavelength (L-Band or P-Band) IFSAR bare-
earth DEMs beneath canopy with well- ground-truthed ancillary
information. However it is expected that there will be more in
the near future from both commercial and research
organizations. There are a number of research issues and
operational implantations to be addressed that were not
discussed in this paper. Indeed the status is a long way from
that demonstrated with X-Band IFSAR in non-forested regions.
However the potential appears to warrant increased activity in
this area with consequent rewards for the effort.
ACKNOWLEDGEMENTS
The author would like to acknowledge his colleagues at
Intermap both in Engineering and Operations whose
contributions were decisive for the success of the two projects
described in this paper.
REFERENCES
Andersen, H-E, R. McGaughey, S. Reutebuch, and B. Mercer.
2004. Estimation of forest inventory parameters using
interferometric radar. First International Digital Forestry
Workshop, Beijing, China. June 14-18. 2004. (to appear)
Andersen H-E, RJ McGaughey, W. Carson, S. E. Reutebuch,
B. Mercer, J. Allan, 2003. A Comparison of Forest Canopy
Models Derived from Lidar and InSAR Data in a Pacific
Northwest Conifer Forest. Proceedings of the ISPRS WG [11/3
Workshop on 3-D reconstruction from airborne laserscanner
and InSAR data, Dresden, Germany
Cloude, S.R., K.P. Papathanassiou, 1998. Polarimetric SAR
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Duncan, A., B. Kerridge, J. Michael, A. Strachan, 2004. The
National Flood Mapping Program: Using IFSAR for Flood
Modeling in England and Wales. Proceedings of ASFPM 2004
Annual Floodplain Management Conference, Biloxi, Miss, USA
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