ERS – ENVISAT TANDEM DATA OVER SEA AND SHELF ICE

Urs Wegmüller, Charles Werner, Maurizio Santoro, Tazio Strozzi and Andreas Wiesmann

Gamma Remote Sensing AG, Worbstrasse 225, CH-3073 Gümligen, Switzerland,

http://www.gamma-rs.ch, wegmuller@gamma-rs.ch

ABSTRACT

ERS – ENVISAT Tandem (EET) data are SAR data

pairs acquired by the ERS-2 and ENVISAT ASAR

instruments from approximately the same orbits within

28 minutes. During two dedicated campaigns in

2007/2008 and 2008/2009 ESA specifically acquired

EET pairs with baselines suited for cross-interferometry

(CInSAR). At perpendicular baselines of about 2km the

frequency difference and baseline effects on the

reflectivity spectrum compensate and so coherent

interferograms can be obtained. Sea and shelf ice has

usually a relatively flat surface and so there is little topographic phase observed, even for 2km

perpendicular baselines. Centimeter scale motion

occurring during the 28 minute interval results in

deformation phase. Motion at this rate is often observed

for sea and shelf ice and is of interest to understand

dynamics and stress occurring. More open sea ice

moves at even much higher rates. Here EET coherence

is typically lost but offset tracking and split-beam

interferometry may be used to retrieve motion fields.

The sensitivities of these techniques are in the order of

1/20 of a SAR image pixel. So in azimuth direction this

translates to a sensitivity of about 20cm per 28 minutes interval and in cross-track direction to about 1m per 28

minutes interval. On the other hand maximum rates

which can reliably be retrieved correspond to offsets of

several pixels between the two acquisitions

corresponding to rates up to the order of 100m per 28

minutes interval.

Repeat-pass interferometry, offset tracking, and split-

beam interferometry were already applied in the past

using data at different wavelengths and time intervals.

So far the shortest interval available was 1 day from the

ERS-1/2 Tandem mission. Now, EET data offers data at

a much shorter 28 minutes interval. Consequently, faster

motion rates can be investigated.

1. INTRODUCTION

In 2002 ESA launched the ENVISAT satellite with the

Advanced SAR (ASAR). ENVISAT is operated in the

same orbits as the ERS-2, preceding ERS-2 by

approximately 28 minutes. One of the ASAR modes,

namely IS2 at VV-polarization corresponds closely to

the ERS SAR mode, except for the slightly different

sensor frequency used. A unique opportunity offered by

these two similar SAR instruments operated in the same

orbital configuration is ERS – ENVISAT cross-

interferometry (CInSAR). At perpendicular baselines of

approximately 2 kilometers the look-angle effect on the reflectivity spectrum compensates for the carrier

frequency difference effect. As was shown with

examples over Germany, the Netherlands, Italy, and

Switzerland [1] CInSAR has a good potential to

generate accurate DEMs over relatively flat terrain.

In the case of fast moving targets interferometric data

acquired with a short 28 minute interval may also be of

interest for displacement mapping. Similarly, tracking

and split-beam interferometry techniques may be

applied to these short repeat interval pairs to map even

faster displacements.

After a review of the CInSAR, offset tracking and split-

beam interferometry methodologies the main focus of

this work is on the assessment of the displacement rate

ranges within which EET CInSAR, offset tracking and

split-beam interferometry can be used to derive motion

information.

2 METHODOLOGIES

2.1 EET CInSAR

A SAR observes a surface area under a specific

incidence angle. Given this incidence angle, the radar

carrier or center frequency, and the chirp bandwidth a

certain part of the reflectivity spectrum of the surface is

measured. Changes to the incidence angle or to the radar

frequency cause changes of the reflectivity spectrum. To

obtain coherence between two acquisitions, the

reflectivity spectra of the two signals being interfered

have to overlap. For two acquisitions acquired at the same frequency this means that the incidence angle

difference needs to be small. At larger incidence angle

differences, corresponding to baselines larger than the

so-called critical baseline the reflectivity spectra do not

overlap anymore, resulting in complete decorrelation of

the signal over distributed targets. In the case of

acquisitions at different frequencies the effect of the

frequency on the reflectivity spectrum has also to be

considered. In fact, there exists a condition under which

_____________________________________________________ Proc. ‘Fringe 2009 Workshop’, Frascati, Italy, 30 November – 4 December 2009 (ESA SP-677, March 2010)

the incidence angle effect is exactly compensated by the

radar frequency effect. For a given frequency difference

(f2 – f1) the perpendicular baseline component ⊥B for

which the two effects compensate each other is

approximately [2]

1

112 )tan()(

f

rffB

αθ −⋅−≅⊥ (1)

In the case of the 31 MHz carrier frequency difference

between ERS2 and ENVISAT ASAR perpendicular

baselines of approximately 2 kilometer compensate the

look-angle effect on the reflectivity spectrum

compensate for a flat surface. The condition is however

sensitive to the local incidence angle, (θ - α). Figure 1

illustrates the orbital configuration and the acquisition

geometry with a 2km baseline that compensates the

frequency difference effect. The sign of the baseline is

such that ENVISAT sees the area under a steeper

incidence angle. ERS2 and ENVISAT carry right

looking sensors so seen in flight direction the ENVISAT

orbit has to be further to the right than the ERS2 orbit.

The effect of having a perpendicular baseline just close

to the optimal value is only partial overlap of the

reflectivity spectra. As long as the overlap is significant

high coherence can be maintained by common band

filtering, i.e. by only considering the overlapping part of the reflectivity spectra. Because of the spatial variation

of the slope angle α this common band filtering should

be done spatially adaptive.

Figure 1 The image to the left shows the orbital

geometry with large baselines at higher northern

latitudes. The image to the right shows the

interferometric imaging geometry. ENVISAT ASAR

has a 31MHz higher carrier frequency than ERS2.

Another constraint to finding coherence in an ERS -

ENVISAT interferometric pair is that overlapping

Doppler spectra of the images acquired by the two

sensors are required. Again, in the case of only partial

overlap the coherence is optimized by common band

filtering, this time of the azimuth spectra, is required.

Apart from the range common band filtering that needs

to be adapted considering the center frequency

difference the interferogram generation for a cross-

sensor interferogram is identical to that of a single

sensor interferogram.

In a complex-valued focused SAR image the phase corresponds to a sum of a term related to the return path

of the signal and a term related to the arrangement of

the scatterers in the resolution cell. For cells with many

distributed scatterers this second part results in speckle

with a spatially random phase in the interval [-π,π]. However, images acquired from almost the identical

aspect angle have almost identical speckle. Under such

conditions the phase difference φ can be expressed as

)

44( 1

12

2 rc

fr

c

f ππφ −−= (2)

where f1 and f2 are the radar center frequencies, r1 and r2

are the slant ranges of the two scenes. Notice, that there

is a significant range phase ramp even in the case of a

zero baseline related to the different center frequencies

m

radERSASAR

c

ff

dr

d3.1

)(4=

−=

πφ (3)

In the ERS – ENVISAT case this results in a phase

ramp of 1.3 radian per meter slant range, or more than a

full phase cycle per range pixel spacing.

For f1 = f2 well known equations describe the

dependence of the interferometric phase on orbit

geometry, scene topography, line-of-sight surface

displacements, and atmospheric path delay

noisepathdisporb rh

r

Bφφ

λ

π

θλ

πφφ +++

⋅+= ⊥ 4

sin

4 (4)

with an orbital phase term orbφ , the wavelength, λ , and

the baseline component perpendicular to the look

vector, ⊥B , the incidence angle, θ , the slant range, r ,

the path delay term pathφ , and a phase noise (or

decorrelation) term noiseφ . In the case of slightly

different frequencies f1 ≠ f2 equation (4) can still be used as a good approximation with only minor

adaptations. The orbital phase, this is the interferometric

phase observed of the flat ellipsoid, is calculated using

(2) with r1 and r2 being the slant ranges to the flat

ellipsoid. This term also contains the strong range phase

ramp of (3). Apart from this the only difference is that

an average wavelength is used

21

2

ff

c

+=λ (5)

The phase to height sensitivity of ERS – ENVISAT

interferograms at mid-swath is

⊥

°⋅⋅= B

mmdh

d

23sin000'852056439.0

4πφ

⊥⋅= Bm

rad

dh

d2

0006688.0φ

(6)

For a 2.0 km baseline this corresponds to 1.34 rad/m

corresponding to a height ambiguity, defined as the

height per topographic phase cycle, of 4.70m.

The phase to line-of-sight displacement sensitivity can

directly be found in (4)

noisepathdisporb rhr

Bφφ

λ

π

θλ

πφφ +++

⋅+= ⊥ 4

sin

4 (7)

The relation between phase noise σφ the number of

looks used, NL, and the coherence,γ can be

approximated by [3]

γ

γσ φ

21

2

1 −=

LN (8)

As we see from (7) the phase noise can be reduced by

taking more interferometric looks. For a coherence of 0.5,

for example, it is realistic to reduce the phase noise to 0.2

radian.

Introducing the phase noise into (6) and (7) tells us the

precision of EET CInSAR estimates for elevation

differences and slant range displacements. Using the 0.2 radian phase noise results in an elevation precision of

0.15m and a LOS displacement precision of 0.9mm and

for the average displacement rate over the 28’

observation period the precision is 1.9mm/hour,

respectively 4.5cm/day or 16.7m/year (see Table 1).

An example of an EET CInSAR example over the

Kugmallit Bay, Canada, is shown in Figure 2.

Interferometric phase that most likely relates to

displacement in the line-of-sight direction is observed

over the sea ice. Considering that phase unwrapping is

necessary for a quantitative interpretation we can

determine a very rough upper limit for displacements

which may be retrieved. Assuming that we can rarely

unwrap more than about 10 phase cycles results in a

maximum displacement of 28cm or, converted to an average displacement rate of 60cm/hour, respectively

14.4m/day or 5260m/year (see Table 1).

2.2 EET offset tracking

Since the late nineteen nineties SAR offset-tracking

procedures are a welcome alternative to SAR

interferometry for the estimation displacement rates [4-

8]) Intensity and coherence tracking can be used. With

both techniques the registration offsets of two SAR

images in both slant-range (i.e. in the line-of-sight of the

satellite) and azimuth (i.e. along the orbit of the

satellite) directions are generated and used to estimate

the displacements. The estimated offsets are

unambiguous values which means that there is no need

for phase unwrapping, one of the most critical step in

SAR interferometry. Typical slant-range and azimuth

offset estimation errors are of the order of 1/20th

of an

SLC pixel [9]. This value is rather a conservative

estimate. Using advanced matching techniques

accuracies up to about 1/100 pixel are possible [11]. For

EET pairs it is important to consider the effect of the

terrain height on the range offset. An ambiguity height of 4.7m (for a 2km baseline) means that 4.7m elevation

difference will also cause a 2.8cm slant range

registration offset. For EET pairs the accuracies

resulting from the more conservative 1/20 pixel offset

estimation accuracy in slant-range and azimuth direction

are 40cm and 20cm, respectively. Converting this to

average displacement rate accuracies results for the

azimuth displacements in 43cm/hour and for the slant

range displacement in 86cm/hour (see Table 1). Offsets

of several pixels can reliably be estimated. As an upper

limit to the applicability of the technique (Table 1) we assume that offsets up to 10 pixels in slant range and 50

pixels in azimuth can be estimated.

An EET offset tracking result over sea ice is shown in

Figure 3. Displacements of tens of meters over the 28’

interval are observed.

2.3 EET split-beam interferometry

“Split-beam” interferograms were used in the past to

estimate displacements along the azimuth direction [12].

The processing sequence used is as follows. The

available azimuth bandwidth (about 50% in the case of

the EET pair on 7-Dec-2007) is divided in two non-

overlapping azimuth bands of equal width. This is done

for both SLCs of the EET pair by band-pass filtering.

For both pairs of sub-band SLCs one-pixel

interferograms are calculated. The combined interferogram is then calculated from the one-pixel

interferograms by multiplication of one complex

interferogram with the complex conjugate of the other

interferogram. The resulting phase corresponds to the

phase of the “split-window” interferogram. An initial

multi-looking is then applied to move from the one-

pixel geometry to a one-look geometry.

The phase φ of the split-beam interferogram can be

approximated for small squint angles by [12]

l

dazπφ

2= (9)

With daz the displacement in azimuth direction and l the

antenna size (about 10m for ERS-2 and ENVISAT

ASAR). As in the normal interferometry case the phase

noise can be estimated from the coherence and number

of looks (8).

Figure 2 EET CInSAR (10-Mar-2009, dt= 28minutes, B⊥= 2247m) differential interferometric phase (left, a color cycle corresponds to a phase cycle) relative to a constant height and RGB composite of the coherence (red) backscattering

(green) and backscatter change (blue, right) over Kugmallit Bay, Canada.

Table 1 Summery of ERS-ENVISAT Tandem DInSAR, split beam interferometry and offset tracking sensitivities,

precisions, and approximate maximum applicable displacement rates. The EET repeat interval used is 28 minutes.

Technique Parameter Sensitivity Precision Maximum

LOS

displacement

rate

Along-track

displacement

rate

LOS

displacement

rate

Along-track

displacement

rate

InSAR Unwrapped

phase π

λ

φ 4=

d

drdisp

0.9mm/28´ 4.5cm/day

16.7m/y

NA 28.0cm/28´ 14.4m/day

5260m/y

NA

Split-

beam

InSAR

Unwrapped

phase πφ 2

l

d

dazdisp=

NA 0.14m/28´

7.2m/day

2.6km/y

50m/28´

2.6km/day

940km/year

Offset

tracking

Range &

azimuth

offsets az

daz

dazr

dr

dr

off

disp

off

disp∆=∆= ,

0.40m/28´

20.6m/day

7.5km/y

0.20m/28´

10.3m/day

3.8km/y

80m/28´

4.1km/day

1500km/y

40m/28´

2.1km/day

750km/y

Figure 3 Geocoded sea ice displacement map derived from a 28’ ERS-ENVISAT pair acquired on 7-Dec-2007 over

Franz Josef Land (area size 53km x 56km). The image brightness corresponds to the backscattering of the ASAR

image. For more discussion on this result and the methodology used see [10].

In the case of fast coherent displacements along the

azimuth direction a non-zero phase is observed. In the

data over Franz Josef Land this is the case over some

fast moving sea-ice. Figure 4 shows the split-beam

interferogram phase for a small section of the 7-Dec-

2007 EET pair over Franz Josef Land. The observed

phase in the North-Western corner corresponds to fast

motion as is confirmed by the offset tracking result

shown in Figure 3.

For a coherence of 0.5 we estimated a phase noise of 0.2

radian when using 20 interferometric looks. Now in the

case of the slowly varying split-beam interferogram phase

significantly more than 20 looks can be used. Assuming

100 looks are used we get a phase estimation accuracy of

0.09 radian resulting in an azimuth displacement

accuracy of 0.14m which is lower than the estimated

offset tracking accuracy in azimuth direction. This

estimate conforms to [12] reporting for split-beam

interferometry a higher sensitivity than for offset

tracking.

Figure 4 Geocoded EET phase of split-beam

interferogram on 7-Dec-2007 over Franz Josef Land.

3. DISCUSSION

Concerning its potential for displacement mapping the

main difference of EET pairs is the sorter time interval

covered. As compared to one day interval of an ERS-1/2

Tandem pair, which was in the past the shortest time

interval available, the 28 minutes are about 50 times

shorter. Consequently, interferometry, offset tracking

and split-beam interferometry are applicable for

displacement rates which are about 50 times higher than

for ERS-1/2 Tandem pairs. EET CInSAR is of interest for very fast glaciers and for slowly moving sea ice in

with displacements between a few millimeters and

about 30cm for the 28 minute interval. Tracking and

split-beam interferometry are of interest for faster

moving sea ice with displacements between decimeters

and tens of meters for the 28 minute interval.

InSAR only permits estimation of displacements in the

line-of-sight slant range direction. Split-beam

interferometry only permits estimation of along-track

displacements. Using offset tracking both components

can be estimated. So for smaller displacements in range

direction InSAR is the most accurate technique. The

most accurate technique in the along-track direction is

split-beam interferometry.

InSAR and split-beam interferometry require coherence

between the two scenes. Consequently only pairs with

suited perpendicular baselines near 2km and

significantly overlapping Doppler spectra can be used.

Furthermore, phase unwrapping is required. Tracking is always applicable and no phase unwrapping is required.

It is also applicable, for example, over Antarctic regions

where no EET pairs suited for CInSAR were acquired

so far.

4. CONCLUSIONS

In this paper techniques to map surface displacements

using EET pairs acquired with a 28 minute interval were

assessed. Because of the short interval EET CInSAR,

offset tracking and split-beam interferometry permit

mapping relatively fast movements. As shown in this contribution such movements are observed over sea ice.

Slower movements, e.g. in coastal areas can be mapped

using EET CInSAR. For faster moving ice such a

drifting ice, offset tracking and split-beam

interferometry are well suited.

5. ACKNOWLEDGMENTS

This work was supported by ESA under contract

22526/09/I-LG on ERS-ENVISAT Tandem Cross-

Interferometry Campaigns: Case Studies. ERS and

ASAR data copyright ESA (CAT 6744). SRTM DEM

copyright USGS.

6. REFERENCES

[1] Wegmüller U., M. Santoro, C. Werner, T. Strozzi, A.

Wiesmann, and W. Lengert, “DEM generation using

ERS–ENVISAT interferometry“, Journal of Applied Geophysics Vol. 69, pp 51–58, 2009,

doi:10.1016/j.jappgeo.2009.04.002.

[2] Santoro M., J. I. H. Askne, U. Wegmüller, and C. L. Werner, "Observations, modeling, and applications of ERS-ENVISAT coherence over land surfaces," IEEE

Trans. Geosci. Remote Sensing, vol. 45, pp. 2600-2611, 2007.

[3] E. Rodriguez and J. M. Martin, “Theory and design of

interferometric synthetic aperture radars“, IEE Proc. Part F Radar Signal Process, 139(2), 149-159, 1992.

[4] Rott H., M. Stuefer, A. Siegel, P. Skvarca, and A. Eckstaller, “Mass fluxes and dynamics of Moreno Glacier,

Southern Patagonia Icefield,” Geophysical Research

Letters, Vol. 25, No. 9, pp. 1407-1410, 1998.

[5] Gray L., K. Mattar, and P Vachon, “InSAR results from

the RADARSAT Antarctic mapping mission: estimation of glacier motion using a simple registration procedure,” Proceedings of IGARSS’98, Seattle, USA, 1998.

[6] Michel R., and E. Rignot, “Flow of Glaciar Moreno,

Argentina, from repeat-pass Shuttle Imaging Radar images: comparison of the phase correlation method with radar interferometry,” Journal of Glaciology, Vol. 45, No.

149, pp. 93-100, 1999.

[7] Gray L., K. Mattar, and P Vachon, “InSAR results from the RADARSAT Antarctic mapping mission: estimation

of glacier motion using a simple registration procedure,” Proceedings of IGARSS’98, Seattle, USA, 1998.

[8] Derauw D., “DInSAR and coherence tracking applied to glaciology: the example of Shirase Glacier,” Proceedings

of FRINGE’99, Liège, Belgium, 1999.

[9] Strozzi T., A. Luckman, T. Murray, U. Wegmüller, C. Werner, Glacier motion estimation using SAR offset-

tracking procedures, IEEE Trans. Geosci. Remote

Sensing, Vol. 40, No. 11, pp. 2384-2391, 2002.

10] Santoro M., U. Wegmüller, T. Strozzi, C. Werner, A. Wiesmann and W. Lengert, “Thematic applications of

ERS-ENVISAT cross-interferometry“, Proc. IGARSS'08, Boston, 6-11 Jul. 2008.

[11] Werner C., U. Wegmüller, T. Strozzi, and A. Wiesmann, “Precision estimation of local offsets between SAR SLCs

and detected SAR images”, Proc. IGARSS 2005, Seoul, Korea, 25-29 Jul. 2005.

[12] N. B. D. Bechor and H. Zebker, “Measuring two-

dimensional movements using a single InSAR pair”, Geophysical Research Letters, Vol. 33, L16311, doi:10.1029/2006GL026883, 2006.