ASAR Training Course, Hanoi, 25 February 7 March 2008 Introduction to Radar Interferometry

Transcription

1 Introduction to Radar Interferometry Presenter: F.Sarti (ESA/ESRIN) 1

2 Imaging Radar : reminder 2

3 Physics of radar Potentialities of radar All-weather observation system (active system) Penetration capabilities estimation of vegetal biomass Dielectric properties of medium Sensitivity to water content Sensitivity to geometrical structures with scales of the same order than the wavelength ENVISAT ASAR ERS SAR, Radarsat: C band 5,6 cm JERS, ALOS PalSAR: L band 23 cm λ 3

4 4

5 RADARSAT SCANSAR IMAGE (500 km SWATH) Sea roughness Waves, wind, sea pollution, storms Topography, slope Cities Ships and military detection 5

6 Active instrument. Intensity and Phase. Coherent illumination. Speckle noise (consequence of a coherent illumination) pixel I n 1 m pixel n 2 I m R e R e Δ φ contribution of one scatterer pixel response 6

7 The speckle noise, consequence of a coherent illumination Large radiometry : large noise The speckle noise is a multiplicative noise Low radiometry : low noise Image SETHI, bande C, 3 m 7

8 Interferometry : content Principle of interferometry Products Digital Elevation Models (DEMs) Ground Movement mapping Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 8

9 Content Principle Products Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 9

10 Principle 1/8 Each image pixel (of a single look complex LSC product) contains two terms: Amplitude : A Phase : pixel ϕ specific ϕ = ϕ + ϕ specific is not estimable dist Pixel = A. e jφ ϕ dist 2π Dist λ = Two Way = 4π Dist λ (Single) Phase cannot be used as an information 10

11 Principle 2/8 Dist 1 Δϕ = ϕ If we have two images and if the ground didn t change, ϕ = ϕ specific _ 1 im _ 2 ϕ im _1 specific _ 2 = ϕ dist _ 2 ϕ dist _1 Pixel 1 = A 1. e jφ1 Dist 2 Pixel 2 = A 2. e jφ2 Δϕ = 4π ( Dist2 Dist 1 ) λ Δϕ Image of is called an Interferogram Image of Distance differences (removal of unknown phase term, pixel-specific) 11

12 Principle 3/8 Co-registration of images 1 2 Master image Slave image Geometry image1 (Master) Geometry image 2 (slave) Terrain geometry The distance measurement principle relies on the same terrain pixel. Practically, the two images have (always) a (slightly) different geometry. In order to compute a phase difference pixel by pixel, the images must be first precisely co-registered (made superimposable) : resampling of the slave image into the master image geometry. Coregistration must be subpixel precise (better than 0.3 pixels) and can be achieved by means of complex correlation. 12

13 Principle 4/8 Geometric information included in the interferograms (1/5) 1 1. Ground displacement Master image (Day 1) 1 Slave image (Day 2) Only the component of the displacement in the radar viewing direction can be measured by interferometry 13

14 Principle 5/8 Geometric information included in the interferograms (2/5) 2. Atmospheric propagation effects Day 1 Day 2 14

15 Principle 6/8 Geometric information included in the interferograms (3/5) 3. topography : DEM Etna - simulation Iso Altitude Curves 15

16 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 16

17 Interferometry : Applications B Elevation Ground Displacements i Borth Etna Etna Landers H.A. HA, Height of ambiguity = variation of altitude between two pixels induced by topography, giving one fringe on the interferogram (by stereoscopic effect). For ERS: H.A.~10,000 /Borth (m) Iso-altitude curves After elimination of orbital fringes, ground elevation is represented by iso- altitude curves.. Phase gives then a measure of elevation modulo the altitude of ambiguity (function of the orbital baseline, causing a stereoscopic effect). Iso-displacement curves (non simultaneous acquisitions) If a pixel was displaced between the two acquisitions, this generates a difference in distance and therefore a phase difference. The accuracy of the measurement is of the order of mm. Phase measurements are modulo 2π, 2 thus showing up as fringes (need of unwrapping) 17

18 Content Principle Products (applications) Digital Elevation Models Terrain Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 18

19 Relief Slight stereo effect (B/H = 10-4!) But sufficient for small image distortions (only at phase level) few centimeters enough to produce phase shifts proportional to Elevation Precise measurement but known modulo creates fringes λ need to be unwrapped Etna - simulation Iso Altitude Curves question : what variation of altitude corresponds to one fringe? By definition, it corresponds to the altitude of ambiguity 19

20 Relief The altitude of ambiguity (1/3) S 2 B orth 4π d Δϕ = = λ 4π hδ i λsin( i) S 1 i δ i h λ.sin( i) =.Δϕ 4π. δ i Dist B d h With : δ i = Borth Dist A 20

21 Relief The altitude of ambiguity (2/3) Altitude of ambiguity : elevation that corresponds to a 2π phase shift λsin( i) Δϕ = 2π h = = 2δ i λ. Dist.sin( i) 2. B orth Ea = λ. Dist.sin( i) 2. B orth Ea Numerical example : B orth : 100 m, Dist=890 km, i=23, λ=5.6 cm Ea=97 m If Borth = 0, then Ea=infinite 21

22 Relief The altitude of ambiguity (3/3) Influence of the altitude of ambiguity on the fringe density (Ea=500m) (Ea=250m) 22

23 Relief Vertical Accuracy a fraction of the Altitude of Ambiguity depends on the interferogram noise depends on the phase standard-deviation σ ϕ σ z =.Ea 2. π Examples ERS, ENVISAT : Ea/4 or Ea/5 50 down to 3 m SRTM : Ea/15 18 m in C Band ; 6 m in X Band Airborne : better than Ea/100 down to 10 cm 23

24 Relief : The SRTM mission 3D view X-SAR SRTM Cotopaxi altimetric resolution: 6 m 24

25 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 25

26 Ground movements (1/6) Non-simultaneous acquisitions If we can eliminate fringes due to the relief (Diff. Interferometry) Direct measurement of displacement (movement) sub-centimetric accuracy: each fringe corresponds to a displacement equals to λ/2 (irrespective of the baseline) differential within the image (relative) movements towards the satellite Landers Magnitude ERS Iso Displacement Curves 26

27 Ground movements (2/6) 1 Master image (Day 1) 1 Slave image (Day 2) δϕ = 4. π. displ λ // Movement in the radar viewing direction displ // displ _ orth The visible displacement is of the same order of magnitude as a fraction of λ (a few mm) The interferometric measurement is insensitive to displ_orth (North-South slip not measurable by interferometry with polar orbiting SAR) Remark: Non-simultaneous observations Relief effect correction (by model or topographic interferogram substraction) 27

28 Ground movements (3/6) Effect of a DEM error on the differential interferometric processing 1 2 Dist2 Dist2_cor Dist1_cor Dist1 Corrupted DEM information Err_DEM Real terrain 4π/λ.[(Dist2_cor-Dist1_cor)-(Dist2-Dist1)] 2π. Err_DEM/Ea Numerical example : Err_DEM=30m, Ea=90m, Err_DEM/Ea=0.33 The DEM error creates 0.33 fringe on the differential interferogram, which is equivalent to an displacement error of 0.9 cm. 28

29 Ground movements (4/6) Measurement Accuracy a fraction of half the wavelenght depends on the interferogram noise ( coherency) depends on the phase standard-deviation Displacement measurement accuracy Examples σ displ. σ ϕ =. λ 2. π 2 ERS : One fringe = λ/2 = 28 mm few mm JERS : One fringe = λ/2 = 11,5 cm few cm 29

30 Ground movements (4/6) Izmit earthquake I : Mean Amplitude H: Phase (Interf.) S: Coherence Izmit 17/08/99 30

31 Ground Displacement Modeling Monitoring ground deformation : magmatic chamber variations, seismic deformation (reverse modelling) Pre, post-seismic deformation (millimeters) Fault monitoring Integration with GPS 31

32 Ground movements (1/6) Subsidences over Paris Paris ONERA97/CNES 99 1,6 cm ERS 1Km 32

33 Processing chain DIFSAR Co-registration Coherency Unwrapped phase interferogram Interferogram Geocoded displacement map DEM Phase model Orbital data 33

34 Content Principle Products (applications) Digital Elevation Models Terrain Movement Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 34

35 Coherency Map coherence = γ = M M i i 2. E. i * E i 2 ; 0 γ 1 Computed on a window (n = 5, 20, 80, ) Measures mainly the phase stability between the two acquisitions : quality and reliability index of interferometric measurement A low level of coherence reflects the fact that changes took place between the two acquisitions Very sensitive to temporal change and therefore to land cover (vegetation, flow & erosion, human activity, ) : thematic applications 35

36 Coherence Map (thematic mapping) 36

37 Forest damage 1) Cartographic reference 2) Forestry inventory 3) SPOT data 4) Coherence before storm 5) Coherence after storm 6) Damaged areas (pink) 37

38 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 38

39 LIMITATIONS performances: precise measurement large surfaces temporal information Accuracy of a few mm S.Paul de Fenouillet limitations: geometrical constraints (baseline) coherency loss (noise on interferograms) atmospheric artifacts 39

40 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 40

41 Temporal Limitations Liquid surfaces (always in movement) Vegetation (growth, wind, plough, harvest, ) Erosion Unstable surfaces Human activity Underground concealment Any change on the ground Remark: higher (multitemporal) coherency in L band on low vegetation (penetration: soil coherency). Better for deformation monitoring 41

42 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 42

43 Geometric limitations 1/6 The specific phase comes from the physical mechanism of wave backscattering It is linked to the speckle (reconstruction phase) Speckle derives from the vectorial summation of response of each elementary reflector in one pixel (coherent illumination) A φ vectorial summation (amplitude and phase) 1 pixel 43

44 Geometric limitations 2/6 S 2 If the incidence angle changes, the reconstruction phase changes The larger the pixel, the more sensitive it is to a small variation of incidence angle (directivity, like antenna) Sensitive to incidence Sensitive to slope Sensitive to Baseline (δi) S 1 δi Apparent pixel size viewed from the radar 1 pixel High Incidence Geometric loss of coherence Low Incidence radar sampling Slope > 0 44

45 Geometric limitations 3/6 The same stands for volumic backscattering Apparent pixel size, viewed from the radar radar sampling surfacic backscattering volumic backscattering Remark: for simultaneous interferometric, X band (smaller penetration, smaller apparent pixel) is more coherent on forests than L band : better for surfacic DEM ERS1&2 tandem coherence Forest / Non Forest Coast lines 45

46 Geometric limitations 4/6 Equivalent Frequency shift : ΔF = F p. δi tg( i α) = c. Borth λ. Dist. tg( i α) R 1 Borth R 2 (.sin( i )) 1/ α F p T = 1/ F p i δi α ( sin( i α δ )) 1/ i F p Observing a surface under two slightly different point of view (R 1 and R 2 ) is equivalent to a two-frequencies observation from one given location (ex : R1) 46

47 Geometric limitations 5/6 If ΔF B, there is no coherence Image 1 B Range spectral domain Image 2 Δ f d High resolution is more resistant for interferometry B Range spectral domain B Range spectral domain Δ f d Δ f d 47

48 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 48

49 Propagation Effects 1/4 Interferometry is corrupted by atmospheric artifacts, creating a path difference between the two images. Two types: istandard atmosphere variation (time-varying but topography-related) ilocal heterogeneities (time-varying) 49

50 Propagation Effects 3/4 Troposphere and Relief Even in case of global vapor content change Dilatation of distance depends on the relief Vapor content 50

51 Propagation Effects 4/4 Ionosphere The refactive index is function of the Total Electronic Content (TEC) Depends on the frequency band Strong effects in L Band (or P Band) Less effects in X or C Band 40,28 Δl iono =. TEC 2 f 51

52 Atmospheric artifacts Ionospheric hole Clouds - Cumulus Cloud chain (Etna) 52

53 LIMITATIONS : POSSIBLE SOLUTIONS Expert interpretation, on the basis of a-priori knowledge (topography, climate, displacement models and prediction, GPS...) Atmospheric modelling - limited application, need of dense vertical profiles, ionosphere... Stacking of interferograms for averaging Correlation of interferograms Permanent scatterers A mixed solution is possible. Compromise to be found as a function of required accuracy, auxiliary data available, number of images 53

54 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications 54

55 June 28 th 1992 Landers Earthquake (California) Area : 90 km x 90 km (7.3 event) 0 2π One fringe = 28 mm displacement Post-sismic event Main rift Interferogram processed with a pair of ERS-1 images taken before (April 24, 92) and after (June 93) Earthquake 55

56 Gulf of Corinthe Greece (North- East Peloponese) 1995 (ERS imagery) Subsidence effect that contributes in enlarging the Gulf Loss of coherence (the interferometric measurement cannot be used locally. Various reasons : meteo, vegetation, relief,... 56

57 Monitoring of industrial risks : Impact of a geothermal power plant on the environment (MESA, USA) USA Power plant Mexico ERS radar image Interferogram processed with a pair of ERS images separated by 2 years 57

58 Mount Etna : Volcano deflation monitored by radar interferometry 30 ERS-1 images studied (May 1992 Oct. 1993) Map projection interferogram showing large scale deflation 2 orbits : days, +518 days Modelling of the deflation on the same period (Institut de Physique du Globe, Paris) 58

59 Piton de la Fournaise Réunion Island (June 1998) Interferogram processed with a pair of RADARSAT images (orbites 7753 et 14270) 59

60 Piton de la Fournaise Ile de la Réunion (Juin 1998) Radarsat1 Differential Interferogram : Mars 1998 Eruption 10/04/97-30/07/ m altitude of ambiguity 60

61 Content Principle Products (applications) Digital Elevation Models Ground Movements Coherence map Limitations Temporal Geometric Atmospheric propagation Signal-to-Noise Ratio Illustrations of Applications An alternative technique: Permanent scatterers 61

62 An alternative: Permanent scatterers 62

63 An alternative: Permanent scatterers not all backscatterers are PS! not uniform distribution needs many acquisitions (40-60) 63