Fundamentals of Remote Sensing: SAR Interferometry

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1 INSIS Fundamentals of Remote Sensing: SAR Interferometry Notions fondamentales de télédétection : l interférométrie RSO Gabriel VASILE Chargé de Recherche CNRS gabriel.vasile@gipsa-lab.grenoble-inp.fr Nikola BESIC Doctorant nikola.besic@gipsa-lab.grenoble-inp.fr 1 Télédétection radar 3A SICOM SIM SN

2 azimut SAR focusing: ERS-1, Chamonix valley, pixels range Range focusing Azimuth focusing SAR image formation: Echolocation: short pulse Linear frequency (chirp) modulation Demodulation: match filtering Synthetic Aperture Radar SAR amplitude image SYTER, Telecom ParisTech 2 Télédétection radar 3A SICOM SIM SN

3 azimut SAR focusing: ERS-1, Chamonix valley, pixels range Range focusing Azimuth focusing SAR image formation: Echolocation: short pulse Linear frequency (chirp) modulation Demodulation: match filtering Synthetic Aperture Radar SAR phase image SYTER, Telecom ParisTech POL/In/POL-InSAR 3 Télédétection radar 3A SICOM SIM SN

Penetration depth + I E S E Propagation Backscattering mechanisms

4 Sinclair formula & differential measurements Emission: H and V Reception: H and V E S e jkr r I S E S S S HH VH S S HV VV Penetration depth + I E S E Propagation Backscattering mechanisms 2 phenomena -> differential measurements 4 Télédétection radar 3A SICOM SIM SN

5 Differential measurements InSAR E S e jkr r I S E -> wave/media interactions -> path difference Two SLC images: k M (master), k S (slave) Same target area Slightly different viewing angles Hermitian product -> complex cross-correlation M&S intensities Internal coherence 5 Télédétection radar 3A SICOM SIM SN

Differential measurements InSAR E S e jkr r I S E -> wave/media interactions -> path difference Two SLC images: k M (master), k S (slave) Same target area Slightly different viewing angles

6 Differential measurements InSAR E S e jkr r I S E -> wave/media interactions -> path difference Two SLC images: k M (master), k S (slave) Same target area Slightly different viewing angles Hermitian product -> complex cross-correlation Normalized complex cross-correlation INTERFEROMETRIC PHASE: = arg{c} INTERFEROMETRIC COHERENCE: c = ABS{C} 6 Télédétection radar 3A SICOM SIM SN

Differential measurements POLSAR E S e jkr r I S E -> wave/media interactions -> path difference Fully polarimetric SAR data Cross-polar symmetrisation (monostatic case)

7 Differential measurements POLSAR E S e jkr r I S E -> wave/media interactions -> path difference Fully polarimetric SAR data Cross-polar symmetrisation (monostatic case) Vectorisation on the Pauli basis (target vector): k=[s HH +S VV S HH -S VV 2S HV ] T Hermitian product -> complex correlation Polarimetric coherency matrix 7 Télédétection radar 3A SICOM SIM SN

Differential measurements POL-InSAR E S e jkr r I S E Two acquisitions -> wave/media interactions -> path difference Three polarization configurations k

8 Differential measurements POL-InSAR E S e jkr r I S E Two acquisitions -> wave/media interactions -> path difference Three polarization configurations k {HH,VV,HV} Hermitian product -> complex correlation Polarimetric M&S coherency matrices: Polarimetric interferometric coherency matrix: 8 Télédétection radar 3A SICOM SIM SN

Radar Interferometry Outlines Overview of interferometry Satellite Interferometry Satellite InSAR geometry InSAR processing measuring

9 Radar Interferometry Outlines Overview of interferometry Satellite Interferometry Satellite InSAR geometry InSAR processing measuring topography Satellite Differential InSAR D-InSAR processing measuring motion on the Earth s surface SAR examples 9 Télédétection radar 3A SICOM SIM SN

10 Satellite Interferometry For satellite interferometry of the repeat-pass type, one image is taken one day, and a second image is taken of the same scene one or more days later. More images can be taken at later intervals and used in the processing, as long as the scene retains reasonable coherence over the longer time interval Because there is always a time delay, and usually parallax as well, assumptions must be made or processing must be done to remove the unwanted component of motion or topography In Feb. 2000, the Shuttle Radar Topography Mission obtained topographic (elevation) data of much of the Earth s surface using single-pass interferometry, i.e., image pairs were acquired at the same time using two radar antennas separated physically to create a 60-m fixed baseline. 10 Télédétection radar 3A SICOM SIM SN

11 Radar Interferometry from Space SRTM TANDEM ERS-1/2 11 Télédétection radar 3A SICOM SIM SN

12 Radar Interferometry from Space SRTM TANDEM ERS-1/2 12 Télédétection radar 3A SICOM SIM SN

13 Radar Interferometry from Space : SRTM mission NASA / DLR 13 Télédétection radar 3A SICOM SIM SN

14 Coverage of 11-day SRTM Mission (Feb. 2000) NASA / DLR 14 Télédétection radar 3A SICOM SIM SN

15 SRTM Perspective View with Landsat Overlay Elevation data from C-band across-track interferometric radar, SRTM Acquired Feb. 16, 2000 Height exaggeration 2x Landsat overlay Acquired: Dec. 14, 1984 View toward the North N W Santa Clara River Valley, California NASA / DLR 15 Télédétection radar 3A SICOM SIM SN

ERS 1 and ERS 2 TANDEM Mission (1995-2000) ESA Repeat pass interferometric SAR uses two antenna positions to acquire two SAR images.

16 ERS 1 and ERS 2 TANDEM Mission ( ) ESA Repeat pass interferometric SAR uses two antenna positions to acquire two SAR images. Vertical height is determined by comparing phase measurements. Observable terrain shifts are on the order of the radar wavelength or smaller. 16 Télédétection radar 3A SICOM SIM SN

17 Radar Interferometry from Space 17 Télédétection radar 3A SICOM SIM SN

ERS 1 and ERS 2 TANDEM Mission Schefferville, Québec Colour: Interferogram Phase, 16 steps from 0 to 2π radians Intensity: Interferogram Magnitude Saturation: Coherence Interferogram Magnitude is the

18 ERS 1 and ERS 2 TANDEM Mission Schefferville, Québec Colour: Interferogram Phase, 16 steps from 0 to 2π radians Intensity: Interferogram Magnitude Saturation: Coherence Interferogram Magnitude is the background black-and-white image - similar to regular SAR image. Coherence (colour brightness) indicates the degree of phase correlation. Low coherence indicates greater change (lakes at upper left). High coherence indicates least change (exposed rocks at lower left). Colour-coded interferogram phase: a phase change of 2π radians corresponds to an altitude change of 232 m 18 Télédétection radar 3A SICOM SIM SN

19 Satellite Repeat-pass InSAR Geometry A radar is essentially a distance or range measuring sensor It can measure range in 2 ways: Time delay: R=c/2B = 8 m Phase: R=λ/100 = 1 mm Phase is much more accurate but is a relative measurement only 19 Télédétection radar 3A SICOM SIM SN

20 How a SAR Measures Phase 20 Télédétection radar 3A SICOM SIM SN

21 Phase after Scattering from a Random Surface 21 Télédétection radar 3A SICOM SIM SN

22 Interferometer Phase 22 Télédétection radar 3A SICOM SIM SN

23 How Differential Phase Measures Topography 23 Télédétection radar 3A SICOM SIM SN

positioning, propagation global approach: least squares (phase or local frequencies)

24 Phase Unwrapping Interferometric phase ambiguity φ Wrapped phase = φ (mod 2π) Nyquist criterion φ(n) φ(m) < π Unwrapped phase Automatic methods: local approach : cuts positioning, propagation global approach: least squares (phase or local frequencies) (N) (M) if (N) (M) c (M,N) 2 if (N) (M) 2 if (N) (M) 24 Télédétection radar 3A SICOM SIM SN

25 Interferogram Estimation 2 images single look complex (SLC): u 1 ( m, n) ( m, n) e After co-registration: u 1 ( m, n). u 1 * 2 i ( m, n) 1 1 u 2 ( m, n) ( m, n) e ( m, n) ( m, n). ( m, n). e 2 2 i ( m, n) 2 i( ) 1 2 SLC 1 u1( m, n) SLC 2 u2( m, n) Complex multi-looking: C( i, j) ( m, n) ( m, n) 1 u ( m, n). u 1 u ( m, n) 2 * 2 ( m, n) ( m, n) u 2 (m,n) ( m, n) 2 (i,j) Amp 1 a1( i, j) Coh. C( i, j) Amp 2 a2( i, j) Phase arg( C( i, j)) 25 Télédétection radar 3A SICOM SIM SN

26 Coherence Estimation Distribution of the sample coherence d as function of theoretical coherence value D and the number of looks L>1: p( d D, L) 2( L 1)(1 D 2 ) L d(1 d 2 ) L2 2 F ( L, L;1; d 1 2 D 2 ) Distribution function of L, D = 0.5 Bias function of L 26 Télédétection radar 3A SICOM SIM SN

27 Télédétection radar 3A SICOM SIM SN Distribution of the sample phase as function of theoretical coherence value D and the number of looks L>1: ) ( ) ( ) ( )) ( cos ; ; ( ) cos( ))

27 27 Télédétection radar 3A SICOM SIM SN Distribution of the sample phase as function of theoretical coherence value D and the number of looks L>1: ) ( ) ( ) ( )) ( cos ; ; ( ) cos( )) ( cos ; 2 1 ; (1, 2 ) (1 ),, ( L L D L F D D L F D L D p L Distribution function of D = 0, L = 4 Distribution function of L = 0, D = 0.7 D Phase Estimation

28 Measuring Coherence Coherence must always be measured to assess the suitability of the data set for InSAR processing Coherence magnitude is closely related to the local standard deviation of differential phase High coherence magnitude tells us: images have good SNR phase centres of scatterers are stable any motion is spatially organized Coherence magnitude: is useable, but noisy is good is excellent Coherence has also been successfully used as a terrain classification parameter: water, vegetation, desert, city 28 Télédétection radar 3A SICOM SIM SN

29 InSAR Processing Process data to SLC images Register the two images to 1/10 pixel Over-sample by a factor of 2 in both dimensions Filter common bands in spectrum Conjugate multiply to form interferogram Smooth the interferogram Measure coherence Unwrap phase Estimate geometry parameters (especially baseline) Remove flat-earth fringes Convert unwrapped phase to height and/or motion 29 Télédétection radar 3A SICOM SIM SN

30 InSAR Processing: Chitina River Valley, S.E. Alaska B = 40 m Flat-earth fringes were removed. Phase is still wrapped. Each revolution of the colour wheel represents an increase of 200 m in altitude. ERS images acquired Feb Télédétection radar 3A SICOM SIM SN

31 Topography Contours from Interferogram: ERS-1, 1991 Franklin Bluffs and Sagavanirktok River on the North Slope of Alaska Perspective view generated from an interferometrically derived DEM 31 Télédétection radar 3A SICOM SIM SN

32 Radar Differential Interferometry from Space 32 Télédétection radar 3A SICOM SIM SN

33 Radar Differential Interferometry from Space The information contained in the D-InSAR phase can be decomposed in: 33 Télédétection radar 3A SICOM SIM SN

34 Radar Differential Interferometry from Space 34 Télédétection radar 3A SICOM SIM SN

35 D-InSAR: orbital compensation 35 Télédétection radar 3A SICOM SIM SN

36 D-InSAR: topographic compensation (DTM) 36 Télédétection radar 3A SICOM SIM SN

37 D-InSAR: adaptive filtering 37 Télédétection radar 3A SICOM SIM SN

N / 7 00 30 E Area / Length 3,5 (km²) / 4.

38 Location Glaciology: temperate glaciers French Alps Chamonix Mont-Blanc test site Mer-de-Glace Argentière Location N/ E N / E Area / Length 3,5 (km²) / 4.7 (km) 15 (km²) / 9 (km) Mean slope ~ 9 (17%) ~14 (26%) 38 LISTIC/LAPI Télédétection radar 3A SICOM SIM SN 38

39 ERS - 1/2: visibility assessment ERS ascending (image panchromatic SPOT-1) ERS descending 39 Télédétection radar 3A SICOM SIM SN

40 ERS-1/2 Interferogram (March 1996) SAR amplitude 5 km 100 km TANDEM ERS (Mer-de-glace) (c) InSAR coherence InSAR phase 40 Télédétection radar 3A SICOM SIM SN

41 D-InSAR Parameter Estimation amplitude coherence phase IDAN ML amplitude IDAN ML coherence IDAN ML phase Mer-de-glace [ pixels] 41 Télédétection radar 3A SICOM SIM SN

Measuring Glacier Velocity by D-InSAR filtered

10/11-March-1996 Chamonix Mont-Blanc Hypotheses

42 Measuring Glacier Velocity by D-InSAR filtered phase 2D local frequencies filtered coherence 2D phase unwrapping Geocoding 3D projection velocity field DTM In situ mesures TANDEM ERS, 10/11-March-1996 Chamonix Mont-Blanc Hypotheses on flow direction 42 Télédétection radar 3A SICOM SIM SN

43 D-InSAR Phase Unwrapping IDAN ML phase mod 2π IDAN ML unwrapped phase Mer-de-glace [ pixels]: weighted least-square phase unwrapping 43 Télédétection radar 3A SICOM SIM SN

44 From Slant Range to Ground Range DTM (Lat/Lon, WGS 1984): separating relief / displacement geocoding D-InSAR scalar measurement: slant range displacement 44 Télédétection radar 3A SICOM SIM SN

45 Glacier Velocity Field: Argentière & Mer-de-glace In situ measurements: unknown offset ablation sticks differential GPS D-InSAR/DTM measurements: 3D displacement field glacier flow direction (SPF,MSF) 45 Télédétection radar 3A SICOM SIM SN

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55 TerraSAR-X StripMap Acquisition (3m res) of the Pyramids of Giza, Egypt Prel. Image recorded during calibration phase Télédétection radar 3A SICOM SIM SN

56 South Nigeria, 3m res TerraSAR-X Basic Image Products Warri airport City of Warri 56 Télédétection radar 3A SICOM SIM SN 56

57 TerraSAR-X Basic Image Products Cape Town (South Africa) 1m res International airport 57 Télédétection radar 3A SICOM SIM SN 57

58 TerraSAR-X Basic Image Products Mombasa (Kenya) 1m res Télédétection radar 3A SICOM SIM SN

59 Addis Abeba (Ethiopia), 3m res TerraSAR-X Basic Image Products 59 Télédétection radar 3A SICOM SIM SN 59

60 Bibliography Presentation available at: H. Maître, Traitement des images de RSO, Hermes Sciences Publications, 2001 L. Lliboutry, Sciences Géométriques et Télédétection, Masson, 1992 C. Elachi, Introduction to the Physics and Techniques of Remote Sensing, Wiley Series in Remote Sensing, 1987 Tutoriel du Centre Canadien de Télédétection (CCT): Trouvé E., Imagerie Radar à Synthèse d Ouverture, cours ETASM, Université de Savoie, 2004 Faller N., TerraSAR-X: Surveying, Mapping & Infrastructure Development, Map Africa 2007 Hajnsek I. at al., TerraSAR-X Mission: Application and Data Access, Int. Summer School on Very High Resolution Remote Sensing, Télédétection radar 3A SICOM SIM SN

Fundamentals of Remote Sensing: the Imaging RADAR System

INSIS Fundamentals of Remote Sensing: the Imaging RADAR System Notions fondamentales de télédétection : le RADAR imageur Gabriel VASILE Chargé de Recherche CNRS gabriel.vasile@gipsa-lab.grenoble-inp.fr