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Subsidence Monitoring Using Polarimetric Persistent Scatterers Interferometry

Subsidence Monitoring Using Polarimetric Persistent Scatterers Interferometry. Victor D. Navarro-Sanchez and Juan M. Lopez-Sanchez Signals, Systems and Telecommunications Group University of Alicante, Spain. Overview. Introduction PSI optimization Polarimetric behaviour

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Subsidence Monitoring Using Polarimetric Persistent Scatterers Interferometry

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  1. Subsidence Monitoring Using Polarimetric Persistent Scatterers Interferometry Victor D. Navarro-Sanchez and Juan M. Lopez-Sanchez Signals, Systems and Telecommunications Group University of Alicante, Spain

  2. Overview • Introduction • PSI optimization • Polarimetric behaviour • Deformation results • Conclusions and future work

  3. Introduction Persistent Scatterers Interferometry (PSI) • Used extensively to measure surface deformation evolution • Exploits phase information of a stack of SAR differential interferograms • Selects for processing only good quality points (pixel candidates)‏ • Different quality criteria: • Average coherence • Amplitude dispersion index • Others • Traditionally formulated and applied to single-pol data

  4. Introduction Concerning Polarimetry: • Sensitive to physical features of the scene (orientation, shape...) • Widely used for physical parameter retrieval (forest height, biomass, soil moisture, etc.) • Polarimetric interferometry (PolInSAR) has a solid theoretical background Motivation: To find efficient ways to exploit polarimetric information in order to improve PSI performance: - Increase of the quality and number of pixel candidates - Extract additional information to classify scatterers

  5. Projection vector (normalized complex vector)‏ Scattering coefficient (scalar complex)‏ PSI optimization General framework and formulation for vector interferometry [Cloude and Papathanassiou, 1998]: Scattering complex matrix (Sinclair Matrix): Target vector: Projection:

  6. Search PSI optimization Formulation for vector interferometry adapted to the dual-pol case: Target vector: Projection vector parameterization: Navarro-Sanchez et al., IEEE GRSL, 2010

  7. PSI optimization Average coherence optimization: Average coherence: Scalar interferometry: Vector interferometry: Constraint:  k

  8. Amplitude standard deviation Average amplitude PSI optimization Amplitude dispersion optimization: Amplitude dispersion: Scalar interferometry: Vector interferometry: Constraint: same i

  9. PSI optimization Data set 40 images of Murcia (Spain) Feb-09 to May-10 • TerraSAR-X SLC data, stripmap mode • Dual-pol: HH and VV • Mean incidence angle: 37.8 degrees • Resolution: 6.6m Az, 1.17m Rg • Pixel spacing: 2.44m Az, 0.91m Rg • Oversampling factors: 2.7 Az, 1.28 Rg All images have been provided by DLR under the framework of project GEO0389

  10. PSI optimization Histograms of  and DA for conventional channels and computed optimum

  11. PSI optimization Average coherencecriterion, ML 7x7, threshold 0.7 VV Pixels selected = 24.07% OPT Pixels selected = 38.57%

  12. PSI optimization DA criterion, full-resolution, threshold 0.3 VV Pixels selected = 6.01% OPT Pixels selected = 16.32%

  13. Polarimetric Behaviour Rural area Urbanarea

  14. Polarimetric Behaviour Average coherence criterion, ML 7x7, threshold 0.7 Whole scene Urban Rural Interpretation of figures for the Pauli basis

  15. Polarimetric Behaviour DA criterion, full-resolution, threshold 0.3 Whole scene Urban Rural Interpretation of figures for the Pauli basis

  16. Deformation results • ML 7x7 • 167 interferograms • 3 selection layers: • γ> 0.9 - 0.8 - 0.7

  17. Deformation results OPT VV • New details are revealed • Results are consistent with ground truth data and with those presented in [Herrera et al. 2010] (single pol, ML 3x3)

  18. Summary • PSI can be enhanced by exploiting polarimetric information: • Average coherence: Improvement ≈ 60% more PCs selected • Amplitude dispersion: Improvement ≈ 170% more PCs selected • Polarimetric study of selected PSC: • Multi-look data: Dominance of dihedral-like scatterers • Single-look data: Dominance of anisotropic dihedrals and vertical structures • Retrieved deformation maps are denser and consistent with ground truth, proving the suitability of the approach • Future work: Study of selection criteria that make a more complete use of polarimetric information (i.e. polarimetric stationarity indicator) • Future work: Quad-pol extension

  19. Subsidence Monitoring Using Polarimetric Persistent Scatterers Interferometry Victor D. Navarro-Sanchez and Juan M. Lopez-Sanchez Signals, Systems and Telecommunications Group University of Alicante, Spain

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