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G. Vasile , E. Trouvé, I. Petillot, Ph. Bolon, J.-M. Nicolas,

High Resolution SAR Interferometry: estimation of local frequencies in the context of Alpine glaciers. G. Vasile , E. Trouvé, I. Petillot, Ph. Bolon, J.-M. Nicolas, M. Gay, J. Chanussot, T. Landes and P. Grussenmeyer gabriel.vasile@univ-savoie.fr. Outlines. Context: InSAR high resolution

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G. Vasile , E. Trouvé, I. Petillot, Ph. Bolon, J.-M. Nicolas,

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  1. High Resolution SAR Interferometry: estimation of localfrequencies in the context of Alpine glaciers G. Vasile, E. Trouvé, I. Petillot, Ph. Bolon, J.-M. Nicolas, M. Gay, J. Chanussot, T. Landes and P. Grussenmeyer gabriel.vasile@univ-savoie.fr LISTIC / TSI / GIPSA-lab / MAP-PAGE

  2. Outlines • Context: InSAR high resolution • Local frequencies estimation algorithm • Results and discussions • Low Resolution ERS TANDEM data • High Resolution simulated TS-X data • Conclusions and perspectives LISTIC / TSI / GIPSA-lab / MAP-PAGE

  3. Low Resolution (LR) vs. High Resolution (HR) LR – 80m LR+HR – 2m Mer-de-glace surface May 2004 Longitudinal elevation profiles along the Mer-de-glace (m) • Strong topography -> narrow fringes • Glacier microrelief -> HR component • Different surface penetration • Different orientations LISTIC / TSI / GIPSA-lab / MAP-PAGE

  4. STATIONARITY ERGODICITY Need for frequencies estimates - Estimation • Estimation of 2nd order moments : complex correlation • 3 directions for preserving the stationarity & ergodicity • Spatial support: boxcar, directional, region growing… • Appropriate estimator: ML, LLMMSE… • Compensation of deterministic phase components Trade-off: ergodicity/stationarity – number of samples ! LISTIC / TSI / GIPSA-lab / MAP-PAGE

  5. Need for frequencies estimates – 2D unwrapping Phase ambiguity • Wrapped phase: φ = Φ (mod 2π) • Nyquist criterion: | Φ(N) − Φ(M)| < π • Phase difference test for unwrapping: Phase difference -> phase gradient -> local frequency LISTIC / TSI / GIPSA-lab / MAP-PAGE

  6. Outlines • Context: InSAR high resolution • Local frequency estimation algorithm • Results and discussions • Low Resolution ERS TANDEM data • High Resolution simulated TS-X data • Conclusions and perspectives LISTIC / TSI / GIPSA-lab / MAP-PAGE

  7. Phase LR+HR model • Analytical phase signal: • : 2D sine-wave estimated on large square windows (*) • : 2D sine-wave Need of adaptive neighborhood Need of new estimation technique (*)E. Trouvé et al. “Improving phase unwrapping techniques by the use of local frequency”,IEEE Transactions on Geoscience and Remote Sensing, 36(6):1963-1972, 1998 LISTIC / TSI / GIPSA-lab / MAP-PAGE

  8. Intensity Driven Adaptive Neighborhood (IDAN) • 2-step region growing technique (*) • Driven simultaneously on all the intensities of the input data set; • AN makes it possible to reach the number of pixels necessary for reliable estimation; • AN preserves the stationarity since most of the sources of phase nonstationarityare revealed by the SAR intensity which is mostly influenced by the local slope. (*) G. Vasile et al. “Intensity-Driven-Adaptive-Neighborhood Technique for Polarimetric and Interferometric SAR Parameters Estimation”. IEEE Transactions on Geoscience and Remote Sensing, 44(5):1609-1621, 2006 LISTIC / TSI / GIPSA-lab / MAP-PAGE

  9. Estimation of the local frequency • 2D phase model: • Estimation technique based on the autocorrelation function: under stationarity and phase noise iid hypothesis  K real • Step 1: estimation of on the Np,q available pixel pairs • Step 2: estimation of the local frequency: LISTIC / TSI / GIPSA-lab / MAP-PAGE

  10. 2D - LR local frequencies SAR intensities LR MUSIC Frequency Estimation LR Freq. Compensation 2D - HR local frequencies HR - IDAN Frequency Estimation SAR phase Algorithm implementation Local compensation of LR deterministic geometrical phase component The resulting phase signal exhibits the local differences between the 2D sine-wave model and the real HR fringe pattern LISTIC / TSI / GIPSA-lab / MAP-PAGE

  11. Outlines • Context: InSAR high resolution • Local frequency estimation algorithm • Results and discussions • Low Resolution ERS TANDEM data • High Resolution simulated TS-X data • Conclusions and perspectives LISTIC / TSI / GIPSA-lab / MAP-PAGE

  12. TANDEM ERS data set LUT masteramplitude phase LR fringe orientation HR fringe orientation Mer-de-glace glacier [C-band, 5-looks, 768x489 pixels, 20x20 m, ea=45m] LISTIC / TSI / GIPSA-lab / MAP-PAGE

  13. TANDEM ERS data set LUT masteramplitude phase IDANfiltered phase LR+HR fringe orientation Mer-de-glace glacier [C-band, 5-looks, 768x489 pixels, 20x20 m, ea=45m] LISTIC / TSI / GIPSA-lab / MAP-PAGE

  14. TANDEM ERS data set LUT LR+HRfringe orientation phase ROI-PACfiltered coherence IDAN filtered coherence Mer-de-glace glacier [C-band, 5-looks, 768x489 pixels, 20x20 m, ea=45m] LISTIC / TSI / GIPSA-lab / MAP-PAGE

  15. TerraSAR-X application (a) (b) The Mer-de-glace glacier: (a) Aerotriangulation, (b) DTM 2mx2m. LISTIC / TSI / GIPSA-lab / MAP-PAGE

  16. TerraSAR-X application Descending pass simulation 1.2x2m, αin=30, H=514km Slant range sampling of the SAR intensity Slant range sampling of the elevation (linear interpolation) LISTIC / TSI / GIPSA-lab / MAP-PAGE

  17. TerraSAR-X application Simulated HR SAR amplitude: σ2=1 (speckle variance), 1.2x2m Real LR ERS SAR amplitude: 20x20m LISTIC / TSI / GIPSA-lab / MAP-PAGE

  18. TerraSAR-X application Simulated HR SAR amplitude: σ2=1 (speckle variance), 1.2x2m Simulated HR SAR phase: ea=10m, uniform phase noise distribution ±π/4 LISTIC / TSI / GIPSA-lab / MAP-PAGE

  19. TerraSAR-X application LUT LR map:fringe orientation Simulated HR SAR phase: ea=10m, uniform phase noise distribution ±π/4 LISTIC / TSI / GIPSA-lab / MAP-PAGE

  20. TerraSAR-X application LUT LR map:fringe orientation LR+HR map:fringe orientation LISTIC / TSI / GIPSA-lab / MAP-PAGE

  21. TerraSAR-X application LUT LR+HR map:fringe orientation IDAN LR+HR filtered phase LISTIC / TSI / GIPSA-lab / MAP-PAGE

  22. TerraSAR-X application LUT 50m spatial profile along the surface of the Mer-de-glace glacier: real altitude resampled in the TerraSAR-X slant range, unwrapped HR+LR estimates of the local frequencies, unwrapped LR estimates of the local frequencies. May 2004Photo of the simulated TerraSAR-X region on the Mer-de-glace glacier (approximate position of the profile) LISTIC / TSI / GIPSA-lab / MAP-PAGE

  23. Conclusions and perspectives Conclusions: • HR frequency estimation combined with intensity driven adaptive neighborhood; • estimate local frequencies within HR interferograms; • measure the local topographic variations in interferograms with a small altitude of ambiguity. Future directions: • Chamonix – Mont Blanc glacier monitoring by D-InSAR, • New context: POL-InSAR airborne data. LISTIC / TSI / GIPSA-lab / MAP-PAGE

  24. E-SAR Campaign Argentière: Oct./06 & Feb./07 LISTIC / TSI / GIPSA-lab / MAP-PAGE

  25. Thank you! This work was supported by the French national project ACI-MEGATOR. The authors wish to thank the European Space Agency for providing the SAR data through the Category 1 proposal No.3525. LISTIC / TSI / GIPSA-lab / MAP-PAGE

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