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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
Table 1: SAR
Envisat C-band E-SAR L-band
1
3.1 em 24.3 cm
7.8 m 1.5m
4m 3m
>
0m
E 5 -.—.- Envisat C bandi
E-SAR L Band =
density / occurance
0.0 02 04 0e 0.8 1.0
coherence
Figure 1: Reconstructed coherence histograms corresponding to
the Aletsch glacier, after a 1 day and to Inyltshik glacier after
35 day time interval, using a coherence estimation window of
11 x 11 samples.
estimated along-track (a) and the across-track (b) displacements
through two SWISAR campaign acquisitions. In here, the am-
plitude of the displacements is the division of the displacements
vector by the time interval between acquisitions. The along-
track information turns out to be very valuable, since in some
areas the across-track (LOS) measurement cannot yield any dis-
placement due to the lack of movement in the across-track di-
rection, highlighting the limitation of DInSAR application. The
amplitude of the displacements in both directions can be easily
discriminated because of the geometrical characteristics of the
monitored glaciers. Considering previous in situ measurements,
the displacement maps are found correctly in both across-track
and along-track directions. The first one with the average of 17
cm/day and the other one with the average speed of 36 cm/day,
respectively.
To test the performances of the MI based tracking through whole
glacier, the classical maximum likelihood estimation performance
criteria:
> max(MI) — mean(MI) 4
^. mean(MI) — min(MI) e
has been plotted in Fig. 2(c). It can be easily seen that areas
including moving ice blocks, crevasses and rocks have a signifi-
cantly better estimation performance than areas including layers
of snow. Note that a detailed analysis of Aletsch glacier surface
velocity monitoring with single channel SAR (only temporal V V
channels) can be found in (Prats et al., 2009) and (Reigber et al.,
2008).
3.2 Inyltshik glacier (incoherent) monitoring with C-band
As final example for the MI based tracking, the surface displace-
ment map of Inyltshik glacier by single channel Envisat C-band,
highlighting the application potential of the proposed polarimet-
ric tracking in decorrelated data set (see Fig. 3(a)), has been ob-
tained. The surface velocity map -Fig. 3(b)-, which is in ac-
cordance with previous in situ measurements, shows the typical
surface velocity pattern of glaciers with an highest velocities in
the center of the glacier and a strong gradient towards the bound-
ary. A more detailed study about the geophysical properties of the
43
: (LT) meon MI
(c) mean( M I)—min(MI)
Figure 2: Retrieval of the along-track (a) and across-track (b) dis-
placements, after a 1 day time interval, using the proposed polari-
metric tracking. (c) The robustness map. The horizontal direction
corresponds to the along-track whereas the vertical direction cor-
responds to the across-track direction.
surface velocity of the Inyltshik glacier can be found in (Mayer
et al., 2008, Erten et al., 2009).
4 CONCLUSIONS AND DISCUSSIONS
Multi-channel (polarimetric) tracking approach has been demon-
strated to estimate 2-D glacier surface velocity by maximizing the
MI between temporal acquisitions. Two conclusions can be made
after analyzing the first results in multi-channel tracking. Firstly,
in the ablation zone of the glacier, the multi-channel tracking im-
proves the surface velocity estimation significantly. This can be
explained thanks to the natural properties of the ice blocks and
coherent scatters in this area. Since polarimetry does not have a
significant role in those features, making use of the multi-channel
-hence polarimetric channels, increase the randomness of the ac-
quisitions, and so the quality of the estimation. Secondly, in the
accumulation zone of the glacier, tracking between interferomet-
ric methods with different polarization can cause a misleading
information based on the difference in penetration depth of HH
and VV channels into snow. It has also been shown that thanks
to multi-channel tracking this misleading information can be op-
timized since the movement/shift between each temporal polari-
metric channel is the same. However, availability of ground mea-
surement is required for validating the proposed method. The fol-
lowing specific research questions will be answered with ground
measurements:
e At what level of accuracy can glacier surface velocity can
be measured thanks to POLSAR images?
e Can PoISAR glacier surface velocity measure improve the
one with single-channel single-polarized SAR images.
e How can the proposed algorithm be depended on the wave-
length (penetration to ice)?
