The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008
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processing [Tabb, et al., 2002]. Forest height is then estimated
from the complex coherence of a volume-dominated
polarization by inverting Equation (1) with the assumption of
m=0. This volume-dominated polarization can be the one
corresponding to the high phase centre from phase optimization
or alternatively, by using HV as an approximation.
We examine three approaches that have been proposed in the
literature for forest height estimation: 1) DEM differencing, 2)
2-D search, and 3) Combined approach:
2.1 DEM Differencing
In the DEM differencing approach, the forest height h v is
estimated directly from the phase difference between the
ground phase and the volume-dominated polarization phase
[Cloude and Papathanassiou, 1998]. This approach enjoys the
light computational load and simple implementation effort.
However, as pointed out by Yamada et al. [2001], this approach
tends to underestimate height because the phase centre of the
selected volume-dominated polarization is seldom on the top of
the canopy.
2.2 2-D Search
Cloude and Papathanassiou (2003) introduced the 2-D search
approach, in which, a look-up table (LUT) of complex
interferometric coherences as calculated in Equation (1) is
established, using a set of extinction coefficient values and
forest height values. By finding the closest element in the LUT
to the observed complex coherence, we can estimate extinction
coefficient and forest height at the same time. Figure 1
illustrates the basic idea of this approach.
Complex Coherunc« (90,74)
Figure 1. 2-D search approach for tree height estimation (see
text).
In Figure 1, the green curves are estimated complex
interferometric coherence according to Equation (1) assuming
no ground return (m=0) with <7=0,0.1,...,1.0db/m from centre to
outer and /zv=0-40m with 0.5m as step. Red plus marks
correspond to tree heights of: 10, 20, 30, and 40m. The
black/blue pluses form the coherence region with the green star
as the high phase end, which is used for tree height inversion.
The closest point on the set of green curves is found by a 2-D
array search and the corresponding tree height and the
corresponding extinction rate are the inversion results.
One of the disadvantages of this approach is that it is very time
consuming especially if a blind search is used and an accurate
estimate is desired. A fine LUT (small step size for hv and a)
can increase the estimate accuracy but at the same time will
significantly increase the computation time. To this end, some
information can be used to guide the search and help reduce the
searching time. For example, the knowledge of forest height
range or the knowledge of extinction rate range, can narrow
down the search space.
Another disadvantage of this approach is, if the selected
coherence is not volume dominant (i.e. m = 0), then it will not
be intersected by one of the LUT curves and the method will
fail.
2.3 Combined Approach
An approach which combines elements of the previous
approaches was proposed in [Cloude, 2006]. The estimated
forest height consists of two terms. The first is from the DEM
differencing approach, which tends to underestimate height.
The second term provides an adjustment based on the forest
height estimated from a zero extinction scenario, which can be
directly achieved by inverting a sine function (Equation (4)).
/n ._ ar gQv)-^o , „2sine- 1 ([/,[) (4)
K z K z
In Equation (4), the first element is just the DEM differencing
term, while the second term is an inversion using the coherence
magnitude only for the zero extinction case. The second term is
weighted by a factor £ which has a constrained range as argued
in Cloude (2006).
3. RESULTS
In this research, the forest height estimation results from the
three approaches are compared first on PolSARproSim
[Williams, 2006] simulated L-Band data and then on repeat-
pass L-Band PolInSAR data acquired by German Aerospace
Center (DLR) E-SAR system in the European Space Agency
(ESA)-sponsored INDREX-II campaign [Hjansek, et al., 2005a].
The INDREX-II campaign was conducted in November 2004
as an experimental airborne radar experiment campaign over
Indonesian tropical forest. Some results of forest height
estimation from this dataset have been reported in [Hjansek, et
al., 2005b; Kugler, et al., 2006; Cloude, et al., 2007]. DEM
extraction beneath the forest canopy using this dataset has also
been presented in [Mercer, et al., 2007].
3.1 Results from Simulated Data
The PolSARproSim simulator developed by Dr. Mark Williams
(Williams, 2006) is used to generate L-Band polarimetric SAR
data over a forested area. PolSARproSim is a fully polarimetric-
interferometric coherent SAR scattering and imaging simulator.
It is distributed as part of ESA’s PolSARpro, a polarimetric
SAR data processing and educational toolbox. Detailed design