Modelling studies, as means for assessing what could be called radar signatures, are a part of two radar remote sensing research programs with which the author is affiliated. First, at the University of New South Wales, assessment of SIR-B data is being undertaken for a number of purposes including its value in arid land geomorphological and geological studies, forest and crop assessment, and mapping. A number of early results have been reported, however modelling aspects are still at an early stage. Secondly, the author recently spent 6 months working on SIR-B invertible forest canopy modelling in the Department of Geography at the University of California, Santa Barbara. Results from this work are outlined

Richards, J. A.

English

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 8,7-17159
RADAR SIGNATURE DETERMINATION : TRENDS AND LIMITATIONS
J. A. Richards
Centre for Remote Sensing, and
School of Electrical Engineering and Computer Science
The University of New South Wales
Kensington NSW, Australia
I. INTRODUCTION
Knowledge of the backscattering characteristics of earth surface
features is essential for reliable interpretation of radar image data,
particularly if tonal discrimination, as against structural interpretation, is
required. Information on backscattering behavior can be derived from
measurements or by constructing and utilizing models of the interaction of
radar incident energy with cover types of interest. An appealing aspect of
the latter approach is that a suitably derived model might be invertible,
allowing significant physical properties of a surface to be determined using
radar remote sensing data as an input. Several different approaches may be
adopted in endeavoring to derive backscatter models, including the use of a
theoretical framework based upon propagation and scattering theory or the
adoption of regression fits to experimental data. One can also adopt a
phenomenological approach in which an apparently complicated situation can be
viewed as a set of readily handled components.
Modelling studies, as means for assessing what could be called radar
signatures, are a part of two radar remote sensing research programs with
which the author is affiliated. First, at the University of New South Wales,
assessment of SIR-B data is being undertaken for a number of purposes
including its value in arid land geomorphological and geological studies,
forest and crop assessment, and mapping. A number of early results have been
reported [1-6]; however modelling aspects are still at an early stage.
Secondly, the author recently spent 6 months working on SlR-B invertible
forest canopy modelling in the Department of Geography at the University of
California, Santa Barbara. Results from this work are outlined in the
following; fuller details will be found in Richards, Sun and Simonett [7].
II. SIMPLE FOREST BACKSCATTER MODELLING AT L-BAND
A forest stand, particularly at L-band, is a composite scattering
environment. In establishing a model one may need to account therefore for
volume scattering from the foliage, scattering from the underlying surface or
understory and scattering from the branches, branchlets and trunks. There is
also ample evidence to suggest that significant radar return can result from
bistatic scattering from tree elements onto the surface, followed by specular
reflection from the surface to the sensor [6,8]. Guided by tractability and
invertibility considerations, those components considered important need to be
realised as a model and then aggregated with forest statistical data to form a
model of a forest stand.
184
https://ntrs.nasa.gov/search.jsp?R=19870007726 2020-03-20T13:00:23+00:00Z
The simplified model adopted in the current treatment is shown in
Figure i, consisting of four componentsthat are easily described. A simple
exponential dependenceof diffuse surface backscatter was chosen for the soil
component, modified suitably for two waypath loss in the canopy. An order of
magnitude of 0.i Npm-I was chosen for the attenuation coefficient, with other
parameters chosen from Figure 11.98 of Ulaby et al. [9]. A simple water cloud
model was chosen for the foliage [i0] while the work of Engheta and Elachi [ii]
was used to account for backscattering via multiple reflection from the foliage
and surface. Parameter values for these were established from Attema and
Ulaby, and from the chosen value of the attenuation coefficient.
The fourth componentadopted is strong reflection via the trunk and
surface, with the trunk viewed as a lossy dielectric cylinder standing on a
lossy plane. However, rather than using available expressions for bistatic
scattering from cylinders [12], considerations of computational speed and the
need to keep the model simple if inversion is to be entertained, led to
representing the trunk/ground combination as a simple planer dihedral corner
reflector. An expression for the radar cross section for this structure is
available. In the work undertaken [7] this was modified to account for Fresnel
reflections at the trunk and ground and for the two way path loss through the
canopy. A correction factor was also incorporated to match the reflection
from the dihedral arrangement to that for a cylinder over a plane.
Figure 2 shows simulated levels of backscatter versus incidence
angle for 20 trees of 20m height, added incoherently. Both the individual
backscattering components and the composite value are shown, suggesting that
at L band with the parameter values chosen, the trunk/ground component is
dominant over the midrange of incidence angles.
The importance of the trunk term is also evident in the results of
Figure 3. These compare simulated backscatter to measured (SIR-B) backscatter
of a region of the Klamath forest in the Mt. Shasta region of northern
California for 6 different natural stands and two plantations of Ponderosa
Pine; the stands were of differing heights and densities. Owing to the
uncalibrated nature of SIR-B, it was necessary to match the simulated and
measured values for one experimental site. As seen, when contribution from
the trunk is included there is a much better match of simulated and measured
results.
III. CONCLUDING REMARKS
Development of the forest canopy model is continuing at the
University of California, Santa Barbara. Present intentions are to incorporate
generalizations to other wavebands and polarization configurations, which
almost certainly will require better models for canopy scattering. The trunk
scattering term however is easily adjusted for these different conditions.
In the Australian experiment it is intended to modify the trunk
term to account for the different morphologies of native Eucalypts. In
addition however it is planned to extend the nature of the model to allow
simulations of backscatter from sugar cane plantations.
185
ACKNOWLEDGMENTS
The author is grateful to Professor D. S. Simonett of the
University of California, Santa Barbara, for the opportunity to work on forest
stand modelling with Sun Guoqing under NASA/JPL contract #JPL 956887. The
Australian project is supported by the Australian Research Grants Scheme.
REFERENCES
io J. A. Richards, B. C. Forster, G. R. Taylor, J. C. Trinder and
A. K. Milne. Preliminary results from an Australian multi-
experimental assessment of SIR-B. IEEE International Geoscience
and Remote Sensing Symposium, Amherst, Mass. 1985.
. G. J. Lynne and G. R. Taylor. Geological assessment of SIR-B imagery of
the Amadeus Basin, central Australia. IEEE Transactions on
Geoscience and Remote Sensing (in press).
o G. R. Taylor and G. J. Lynne. Pattern recognition and geological inter-
pretation of SIR-B images of central Australia. Proc. ERIM 5th
Thematic Conference (Remote Sensing for Exploration Geology).
Reno, Nevada. September 1986.
o
.
G. J. Lynne and G. R. Taylor. Integration of SIR-B imagery with
geological and geophysical data in central Australia. Proc. ERIM
5th Thematic Conference (Remote Sensing for Exploration Geology).
Reno, Nevada. September 1986.
J. C. Trinder, The use of SIR-B and LFC image for mapping. International
Seminar on Photogrammetry and Remote Sensing, Delhi, India. March
1986.
. A. K. Skidmore, P. W. Woodgate and J. A. Richards. Classification of the
Riverina forests of S. E. Australia using co-registered Landsat
MSS and SIR-B radar data. Symposium of Commission VII_
International Society of Photogrammetry and Remote Sensing. The
Netherlands, October 1986.
. J. A. Richards, G. Sun and D. S. Simonett. L-band radar backscatter
modelling of forest stands. Submitted for publication to IEEE
Transactions on Geoscience and Remote Sensing.
o J. P. Ormsby, B. J. Blanchard and A. J. Blanchard. Detection of lowland
flooding using active microwave systems. Photogrammetric
Engineering and Remote Sensing, 51, 1985, pp. 317-328.
. F. T. Ulaby, R. K. Moore and A. K. Fung. Microwave Remote Sensing:
Active and Passive, Vol. 2, Massachusetts. Addison Wesley, 1982.
i0. E. P. W. Attema and F. T. Ulaby. Vegetation modeled as a water cloud.
Radio Science, 13, 1978, pp. 357-364.
186
11.
12.
N. Engheta and C. Elachi. Radar scattering from a diffuse vegetation
layer over a smooth surface. IEEE Transactions on Geoscience and
Remote Sensing, GE-20, 1982, pp. 212-216.
G. T. Ruck, D. E. Barrick, W. D. Stuart and C. K. Kirchbaum. Radar Cross
Section Handbook, New York: Plenum 1970.
• 187
canopy
,I ,I
II
i I
I
////////_,y//,
volume
2
:runk to volume to
surface surface
surface
3
Figure i. Components of forest backscatter considered in
the model.
188
2O I I i I
0
- 2O
6° dB
- 40 -
- 60
- 80
Figure 2.
total _-
-. _ foliage
oliage to
e
I I I I
20 40 60 80
8° deg
Simulated backscattering coefficient as a function of
incidence angle for each of the four components of
forest scattering and for their aggregate (from Ref. 7).
189
• • • _ (a)
d° dB
(b)
10
6
2
0
-6
s2
\
s4
s6
p2
simulated
30 °
I
measured
I I I
I I I I
d ° dB
Figure 3.
-8
-I0
-12
-14
-16
simulated
s3
30 °
measured
..fl
\
\
_6
pl
I I I I
_2
Comparison of measured and simulated forest backscattering
coefficient for six natural stands and two plantations of
Ponderos Pine (a) with trunk term included (b) without the
trunk term (from Ref. 7).
190


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