GEMITOR GEoréférencement Multimodal d’Images Tridimensionnelles Optiques et Radar Centre Spatial de Liège Institut Montefiore Université de Liège, Belgium MULTIMODAL GEOREFERENCING of 3D VHR OPTICAL and X-BAND SAR IMAGERY Antonella Belmonte abelmonte@ulg.ac.be

OUTLINE Context Issues Phenomenology (review) Technological approach Results Conclusions Future work

Context

ORFEO Optical and Radar Federated Earth Observation Very High resolution Optical (PLEIADES) and RADAR (Cosmo-Skymed) modalities possibly acquired simultaneously Strong need for optical and radar modalities fusion at pixel level to take full advantage of the ORFEO opportunity Need for 3D information extraction (InSAR) for georeferencing the radar modality

GEMITOR GEoréférencement Multimodal d’Images Tridimensionnelles Optiques et Radar To investigate the limitations of current InSAR techniques To modify/adapt existing algorithms to VHR peculiarities To test algorithms on simulated Cosmo-SkyMed data To georeference visible and SAR images in common reference frame To fuse SAR and optical VHR images at the pixel level To develop 3D visualization tools (virtual reality)

Issues

C-band vs. X-band Airborne vs. spaceborne Standard resolution X-band Spaceborne Very High Resolution X-band Airborne Very High Resolution

Simulated data range Tests performed on simulated CosmoSkyMed RAMSES data set: Airborne SAR interferometric data set (RAMSES = Radar Aéroporté Multi-Spectral d’ Etude de Signatures) VHR: resolution cell azimuth: 0.55 m resolution cell slant range: 0.49 m Site: Baux de Provence Single polarization (VV) Single-pass azimuth

Geometrical differences between spaceborne and airborne SAR acquisitions Spaceborne SAR (ERS) Airborne SAR (RAMSES) SWATH 25 – 500 Km 10 – 100 Km INCIDENTCE ANGLE wrt NORMAL 20 – 45 deg. 30 – 85 deg. DISTANCE SENSOR-CENTER OF THE EARTH ~ 7 150 Km ~ 6 373 Km MINIMUN RANGE ~ 840 Km ~ 3,9 Km PULSE REPETITION FREQUENCY ~ 1679,79 Hz ~ 148,148 Hz

VHR images specific characteristics Some RAMSES images specific characteristics may lead to InSAR processing difficulties and require some specific algorithmic design: Shadowing Specific backscattering & brightness Man-made features

Phenomenology (review)

Shadowing example range Due to the low depression angle, in RAMSES images, shadowing is predominant with respect to layover and foreshortening. SHADOW SHADOW azimuth SHADOW

Buildings example range Buildings azimuth

VHR details At VHR one easily observes: range Vehicle Parcel limits Different crops azimuth At VHR one easily observes: topographical limits parcel limits buildings vehicles Buildings Road

Technical approach

InSAR testing Testing of CSL InSAR processor using RAMSES interferometric data set Slave image already coregistered ==> no testing of the coregistration module Same Doppler centroid ==> no azimuth filtering

Pixel averaging The testing study of the InSAR processor was done, using three different pixel averaging (5x5, 3x3, 1x1) when generating the interferometric products. Final goal is to work with the image at full resolution pixel 1x1 (RAMSES 0,55 x 0,49m).

Results

InSAR processing first results range RAMSES HEADER slave parameters Fos202208_MS_rad_0.dat # Mode interferometrique : Compensation_IF= distance_doppler Retard_apres_demod_hard= 0.000000 s Baseline_x= 0.000000 m Baseline_y= -0.1017500m Baseline_z= -0.6046000 m azimuth If we force Baseline_y= 0.0 m Baseline_z= 0.0 m, the processor gives the following interferogram. We thus suppose that the slave image is already compensated for “orbital” phase wrong « orbital » phase compensation correct « orbital » phase compensation

InSAR processing test samples – 1X1 pixel averaging Amplitude Coherence Interferogram Phase Unwrapping

Simulated CosmoSkyMed data Unwrapped phase test Simulated CosmoSkyMed data RAMSES data Pixel averaging 3x3 Pixel averaging 1x1 Pixel averaging 5x5 Pixel averaging 1x1 Pixel averaging 3x3 Pixel averaging 5x5

Amplitude SAR image Optical image Unwrapped phase At high resolution, the uniform pixels (containing scatterers sharing the same backscattering properties) are more numerous and give a phase response, peculiar to their own physical properties, in addition to the optical path component which is used to compute local heights. Consequently, backscattering characteristic variation appears from a pixel to an adjacent one in the unwrapping phase surface (particularly in the urban area). Unwrapped phase

45 deg. -rotated master image example Interpolation test (1) CSL interpolator is based on Chirp-Z transform It allows applying any affine transform to complex data: To test the interpolator, we apply a 45 deg. rotation to both the master and the slave images 45 deg. -rotated master image example

Interpolation test (2) We regenerate an interferogram from rotated image samples non-rotated interferogram 45 deg.-rotated interferogram

180 deg.-rotated interferogram Interpolation test (3) Master and slave images were rotated 45 deg. successively up to 180 deg. to generate the corresponding interferogram ==> Interpolator used 4 times successively 180 deg.-rotated interferogram

Interferogram differences Interpolation test (4) The obtained interferogram was flipped and compared to the original one No visible trends Histogram of the differences well centerd on a null phase ==> The CSL interpolator is convenient for VHR SAR Data Interferogram differences Histogram of differences

Current InSAR processor limitations The phase unwrapping module works well at full resolution (1x1). but other tests will be performed on more complex areas (i.e. urban area) Improvements : To work at multiple resolutions To improve the residues connection algorithm

Conclusions

The CSL InSAR processor is a good basis for the GEMITOR project since: Geometrical differences between airborne and spaceborne acquisitions must be taken into account in future developments The CSL InSAR processor is a good basis for the GEMITOR project since: The Chirp-Z transform based interpolator is suitable for handling VHR SAR data Phase unwrapping must be adapted to VHR peculiarities

Future work

To test (and adapt if required) the SAR georeferencing routines To study optical and radar modality complementary To bring the optical and SAR modality into the same geographical reference frame at pixel level To visualize the fusion products and all 3D information in 3D stereo

Thank you for your attention!