IEEE Geoscience and Remote Sensing Magazine - March 2013 - 30

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are often preferred in repeat-pass acquisitions due to the
higher temporal stability they provide. In this case large
spatial baselines may compensate up to a certain degree
the strong ground contribution and increase the sensitivity to the crop volume. Fig. 20 shows a crop height map
obtained from the inversion of Pol-InSAR data acquired
at L-band using large spatial baselines in the frame of
the AGRISAR 2006 campaign [51]. The validation with
ground measured crop heights shows an estimation performance on the order of 10-20%.
The cryosphere is dominated by ice and snow scattering volumes. Admittedly, the understanding and development of Pol-InSAR applications with respect to ice and
snow is today in a rather early stage [140]-[146]. The reason for this is the limited amount of experimental and
validation data available as well as the limited understanding of the coherent interaction of electromagnetic
waves with ice volumes. Of key interest is the characterization of the vertical distribution of scatterers within ice
volumes as well as their seasonal and long-term dynamics especially in the percolation zone: There, the nearsurface vertical distribution of scatterers is influenced
by seasonal melting processes leading to the presence of
ice layers, lenses, and pipes, effecting the size and shape
of ice crystals and trapped gas bubbles. In this direction a first remarkable result is the robust estimation of
the scattering extinction profiles of ice volumes at different frequencies (L- and P-band) based on Pol-InSAR
data acquired in the frame of the ICESAR 2007 campaign [144]. Fig. 21 shows the vertical structure profiles
derived at X-, L- and P-band over the Ausfona Glacier in
Svalbard, Norway.

FIGURE 20. (a) Polarimetric Pauli RGB image with R = HH - VV ,
G = 2 HV , B = HH + VV . (b) Interferometric coherence image
scaled from 0 (black) to one (white). (c) Crop height map obtained
from the inversion of Pol-InSAR data acquired using large spatial
baselines at L-band.

of stand conditions which is based on vertical structure
components estimated from multibaseline Pol-InSAR
data [51], [138], [139].
In contrast to forest vegetation applications, the development of quantitative agricultural vegetation Pol-InSAR
applications is more challenging [116]-[118], [140].
The significant differences in vegetation height, form
and attenuation values and in the propagation properties through the vegetation layer make the adoption of
forest concepts for agriculture applications in many
questions inappropriate. Opposed to forest applications,
where lower frequencies are in general of advantage, in
agricultural vegetation monitoring the use of high(er)
frequencies that provide balanced volume and ground
scattering contributions and therefore a better volume
characterization is favored. However, lower frequencies

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-60

-60
HV
HH
VV

VV
-80

-80

1 2 3 4 5

HV
HH
VV
-80

Relative Intensity

(a)

(b)

(c)

FIGURE 21. Vertical structure profiles derived at (a) X- , (b) L- and (c) P-band over the

Ausfona Glacier in Svalbard, Norway.
30

VI. Tomography
As commented in the previous section, the transmitted electromagnetic
wave signal can penetrate through
semi-transparent media, hence being
sensitive to the volume of the observed
objects. Forest is such a prominent
volume scatterer, where at lower
frequencies the transmitted signal
penetrates-depending on the structure and dielectric properties of the
forest-down to the ground even in
very dense forests. However, due to
the cylindrical geometry of a SAR
sensor, targets at the same range
distance cannot be separated and
appear at the same resolution cell,
i.e., they appear in layover. By adding
a second acquisition, as InSAR does,
it is possible to retrieve only a mean
height of all backscattering contributions within the resolution cell. A
significant improvement is given by

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Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - March 2013