Investigations with the Sentinel-1 Interferometric Wide Swath Mode Pau Prats-Iraolaa, Matteo Nanninia, Rolf Scheibera, Francesco De Zana, Steffen Wollstadta , Federico Minatib, Francesco Vecchiolib, Mario Costantinib, Andrea Bucarellib ,
Sven Borgstromc , Thomas Walterd, Michael Foumelise, Yves-Louis Desnosf
a b c d f e
German Aerospace Center Microwaves and Radar institute
Outline
• Introduction • TOPS InSAR Chain • TOPS Special Considerations
– LOS variation – Considerations for PSI processing
• Sentinel-1 Results • Conclusion
German Aerospace Center Microwaves and Radar institute
Introduction • INSARAP: Sentinel-1 InSAR Performance
Evaluation with TOPS Data • Pilot Sites:
– Campi Flegrei/Vesuvius (1xasc/2xdesc) – Istanbul (1xasc/2xdesc) – Mount Etna (1xasc,1xdesc) – Mexico City (2xasc/2xdesc)
German Aerospace Center Microwaves and Radar institute
TOPS InSAR Chain • Particularities of the TOPS signal
– Azimuth-dependent Doppler centroid – Doppler variation larger than azimuth
sampling frequency – Burst mode (synchronization required,
burst-wise processing)
• Critical InSAR processing steps – Accurate azimuth offset computation for coregistration (1 cm ⇒ 0.001 azimuth
samples) – Interpolation – Azimuth spectral filtering
• Selected strategy – Geometric coregistration + global offset estimation – Valid for stationary scenarios (or scenarios with slow deformation rates, e.g., PSI)
German Aerospace Center Microwaves and Radar institute
TOPS InSAR Chain • Main Workflow [1]
– Backgeocoding
– Coregistration
• Global offset (overlap areas, ESD in azimuth)
• Nominal from geometry [2] (interpolation)
– Interferogram generation
• Spectral filtering (optional)
• TOPS specific processing
– ESD, interpolation, spectral filtering
– Burst-wise processing
– Debursting and mosaicking performed at the end (for interferogram generation)
[1] P. Prats, R. Scheiber, L. Marotti, S. Wollstadt, A. Reigber, “TOPS Interferometry with TerraSAR-X,” IEEE Trans. on Geosci. and Remote Sens., vol. 50, no. 8, Aug. 2012. [2] E. Sansosti, P. Berardino, M. Manunta, F. Serafino, G. Fornaro, “Geometrical SAR Image Registration,” IEEE Trans. on Geosci. and Remote Sens., vol. 44, no. 10, Oct. 2006.
Enhanced Spectral Diversity (ESD)
Update of range and azimuth offsets
Coregistration (interpolation)
Spectral filtering
Interferogram generationCoherence estimation
Debursting and sub-swath mosaicking
Filtered SLCs
Backgeocoding
Coregistered SLCs
Master SlaveOrbit DEM
Range and azimuth offsetsSlant phase
Interferometric products (burst-wise)
Mosaicked interferometric products
Interferogram generationInterferogram generation
CoregistrationCoregistrationIncoherent Cross
Correlation
More details under (INSARAP Workshop): http://seom.esa.int/insarap/page_participation.php
German Aerospace Center Microwaves and Radar institute
TOPS Special Considerations • TOPS has a varying line of sight! [1]
– And due to the burst operation, the LoS vector experiences jumps – Azimuth phase jumps should be expected at burst edges in the presence of
azimuthal motion: They simply reveal azimuth components of the motion, sensed by a sudden change in Doppler centroid. ∆𝑥𝑥
∆𝑦𝑦
sin (𝛽𝛽) co
s𝛽𝛽
𝛽𝛽
∆𝑟𝑟 = ∆x ∙ sin 𝛽𝛽 + ∆𝑦𝑦 ∙ cos (𝛽𝛽)
Δ 𝜙𝜙 = 2 𝜋𝜋 ⋅ 𝑓𝑓dc ⋅ Δ𝑡𝑡
= 𝑓𝑓dc =2𝑣𝑣𝜆𝜆 sin 𝛽𝛽
= 4𝜋𝜋𝜆𝜆 ⋅ Δ𝑥𝑥 ⋅ sin𝛽𝛽
[1] F. De Zan et.al., Interferometry with TOPS: coregistration and azimuth shifts, EUSAR 2014, Berlin, Germany.
www.DLR.de/HR > SEOM INSARAP • INSARAP Workshop • December 10, 2014 > Slide 7 Phase Discontinuities over Pine Island Glacier
azimuth →
German Aerospace Center Microwaves and Radar institute
Simulated Earthquake Signature 80
km
(4 b
urst
s)
(Azim
uth)
+ =
Zero-Doppler phase Along-track motion phase TOPS interferogram
+ =
Max disp.: 1.23 m Max phase: +/-150º
Max disp.: 37 cm Max phase: +/-45º
[1] A. Hooper, Sentinel-1 for Geo-Dummies, Wegener 2014, Leeds, Sep. 2014.
German Aerospace Center Microwaves and Radar institute
Simulated Earthquake Signature • Rationale:
– Processing should be straightforward for small earthquakes (just the “usual” phase unwrapping problems due to decorrelation).
– For large earthquakes: • Follow rationale as in [1][2]:
– First estimation of azimuth offsets with cross-correlation – Refinement with spectral diversity at burst level and exploiting overlap areas – Removal of azimuthal phase component – Unwrapping – Insertion of removed azimuthal components
• Model-based computation of earthquake signature (with a priori info from previous step) [3]. Residual should be small and unwrappable.
[1] R. Scheiber, et. al. , Speckle Tracking and Interferometric Processing of TerraSAR-X TOPS Data for Mapping Nonstationary Scenarios, IEEE JSTARS, early access paper available. [2] F. De Zan et.al., Interferometry with TOPS: coregistration and azimuth shifts, EUSAR 2014, Berlin, Germany. [3] A. Hooper, Sentinel-1 for Geo-Dummies, Wegener 2014, Leeds, Sep. 2014.
German Aerospace Center Microwaves and Radar institute
PSI Processing • One straightforward solution is to discard half of the overlap area per burst/sub-swath.
• However, overlap areas might contain slightly different PSs due to the different observation geometries (scientific experiments possible).
• Operationally, overlap areas can be used mainly for quality check purposes.
• Such PSs can be also exploited ⇒ larger PS density at overlap areas!
burst 1
burst 2
common
ca. 20% of points are
detected in both bursts
German Aerospace Center Microwaves and Radar institute
Sentinel-1 Results
German Aerospace Center Microwaves and Radar institute
Std.Dev. Burst mis: 1.8 ms Std.Dev. 𝐵𝐵⊥ = 75 m Std.Dev. Doppler = 20 Hz
Statistical Analysis with Sentinel-1 Interferograms
-10.00-8.00-6.00-4.00-2.000.002.004.006.008.00
10.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106
Burst mis-synchronization [ms]
-250.00
-200.00
-150.00
-100.00
-50.00
0.00
50.00
100.00
150.00
200.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106
Perpendicular baseline [m]
-40.00-30.00-20.00-10.00
0.0010.0020.0030.0040.0050.0060.00
07/1
0/20
14
19/1
0/20
14
31/1
0/20
14
12/1
1/20
14
24/1
1/20
14
06/1
2/20
14
18/1
2/20
14
30/1
2/20
14
11/0
1/20
15
23/0
1/20
15
04/0
2/20
15
16/0
2/20
15
28/0
2/20
15
12/0
3/20
15
Doppler centroid [Hz]
German Aerospace Center Microwaves and Radar institute
Mexico City: Descending (Dawn) 15.10.2014 – 08.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 12 Far range
08.10.2014 – 13.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 13 Near range
German Aerospace Center Microwaves and Radar institute
Mexico City: Ascending (Dusk) 23.10.2014 – 16.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 12 Far range
18.10.2014 – 11.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 12 Near range
German Aerospace Center Microwaves and Radar institute
Mexico City: Cross-Comparison
vs
vs
vs
Comparison confirms expectations: - APS main responsible for observed
differences - Ascending acquisitions (dusk) more affected
by APS - Best cross-result between descending
configurations (0.056 cm/month = 6.7 mm/year) with just 5 months of acquisitions
German Aerospace Center Microwaves and Radar institute
e-GEOS’ PSP-IFSAR Processing Chain [1]
[1] M. Costantini et al., Persistent Scatterer Pair Interferometry: Approach and Application to High-Resolution COSMO-SkyMed SAR Data, IEEE JSTARS, vol. 7, no. 7, 2014.
Very high PS density! PSP temporal coherence threshold = 0.9 Graph connectivity = 6
German Aerospace Center Microwaves and Radar institute
Campi Flegrei: GPS Measurements
January - June 2014 July - September 2014
Start of time series beginning of October
~2 cm
Horizontal and Vertical GPS deformation pattern at Campi Flegrei (2014)
German Aerospace Center Microwaves and Radar institute
Campi Flegrei: Descending 07.10.2014 – 12.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 10
Uplift confirmed by in-situ measurements
German Aerospace Center Microwaves and Radar institute
Campi Flegrei: Ascending 20.10.2014 – 13.03.2015 𝑁𝑁𝑖𝑖𝑖𝑖𝑖𝑖 = 11
Strong APS signal (dusk)
German Aerospace Center Microwaves and Radar institute
Campi Flegrei: Preliminary Validation
*Measurement validation kindly provided by Prospero de Martino, INGV-Vesuvius Observatory
RITE
ACAE
German Aerospace Center Microwaves and Radar institute
• Triplets analsyis [1] No phase consistency, i.e., Φ123= arg < 𝐼𝐼1𝐼𝐼2∗ >< 𝐼𝐼2𝐼𝐼3∗ >< 𝐼𝐼3𝐼𝐼1∗ > ≠ 0, is related
to the presence of two or more scatterers (volume, moisture [2]). [1] F. De Zan et.al., Lack of triangularity in SAR interferometric phases, EUSAR 2014, Berlin, Germany. [2] F. De Zan et.al., A SAR Interferometric Model for Soil Moisture, IEEE TGRS, Vol. 52, No. 1, Jan 2014
Triplets & Moisture VV polarization
VH polarization
F. De Zan, M. Zonno, P. Lopez-Dekker, A. Parizzi, “Phase inconsistencies and water effects in SAR
interferometric stacks” Tuesday @ 9:20, Big Hall
German Aerospace Center Microwaves and Radar institute
Conclusion • TOPS InSAR requires more processing effort, but everything is
solvable. • Validation results presented over two pilot sites
– Cross-validation over Mexico City – Validation with in-situ measurements over Campi Flegrei – On-going work: cross-check of the two PSI chains
• The evaluated results confirm the excellent interferometric capabilities of the Sentinel-1 satellite: – Excellent burst synchronization and antenna pointing performance – Capability to build up stacks in short time spans (time series require
large stacks to achieve millimeter accuracy due to APS) – Reduced repeat-pass cycle & wide swath (≥ 2 LOS vectors within 12
days)
German Aerospace Center Microwaves and Radar institute
Thank you for your attention!