Estimating Spatiotemporal Ground Deformation With Improved Permanent-Scatterer Radar Interferometry

Synthetic aperture radar interferometry has been applied widely in recent years to ground deformation monitoring although difficulties are often encountered when applying the technology, among which the spatial and temporal decorrelation and atmospheric artifacts are the most prominent. The permanent-scatterer interferometric synthetic aperture radar (PS-InSAR) technique has overcome some of the difficulties by focusing only on the temporally coherent radar targets in a time series of synthetic aperture radar (SAR) images. This paper presents an improved PS-InSAR technique by introducing PS-neighborhood networking and empirical mode decomposition (EMD) approaches in the PS-InSAR solution. Linear deformation rates and topographic errors are estimated based on a least squares method, while the nonlinear deformation and atmospheric signals are computed by singular value decomposition and the EMD method. An area in Phoenix, AZ, is used as a test site to determine its historical subsidence with 39 C-band SAR images acquired by European Remote Sensing 1 and 2 satellites from 1992 to 2000.

[1]  Fabio Rocca,et al.  Monitoring landslides and tectonic motions with the Permanent Scatterers Technique , 2003 .

[2]  Cheng Huang,et al.  Least Squares-Based Filter for Remote SensingImage Noise Reduction , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Fabio Rocca,et al.  Permanent scatterers in SAR interferometry , 1999, Remote Sensing.

[4]  D. Sandwell,et al.  Phase gradient approach to stacking interferograms , 1998 .

[5]  Xiaoli Ding,et al.  Atmospheric effects on repeat-pass InSAR measurements over Shanghai region , 2007 .

[6]  Fuk K. Li,et al.  Synthetic aperture radar interferometry , 2000, Proceedings of the IEEE.

[7]  C. Werner,et al.  Radar interferogram filtering for geophysical applications , 1998 .

[8]  Sergey V. Samsonov,et al.  Application of DInSAR-GPS Optimization for Derivation of Fine-Scale Surface Motion Maps of Southern California , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[9]  David T. Sandwell,et al.  Fault creep along the southern San Andreas from interferometric synthetic aperture radar, permanent scatterers, and stacking , 2003 .

[10]  A. Pepe,et al.  Large scale InSAR deformation time series: Phoenix and Houston case studies , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[11]  C. Ghilani,et al.  Adjustment Computations: Statistics and Least Squares in Surveying and GIS , 1987 .

[12]  Jordi J. Mallorquí,et al.  Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images , 2003, IEEE Trans. Geosci. Remote. Sens..

[13]  B. Tapley,et al.  Land subsidence in Houston, Texas, measured by radar interferometry and constrained by extensometers , 2003 .

[14]  Z. W. Li,et al.  Pre- and co-seismic ground deformations of the 1999 Chi-Chi, Taiwan earthquake, measured with SAR interferometry , 2004, Comput. Geosci..

[15]  Gabriel Rilling,et al.  Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.

[16]  P. Rosen,et al.  Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps , 1997 .

[17]  Fabio Rocca,et al.  Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry , 2000, IEEE Trans. Geosci. Remote. Sens..

[18]  G. Fornaro,et al.  Modeling surface deformation observed with synthetic aperture radar interferometry at Campi Flegrei caldera , 2001 .

[19]  Stefania Usai,et al.  A least squares database approach for SAR interferometric data , 2003, IEEE Trans. Geosci. Remote. Sens..

[20]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[21]  Gianfranco Fornaro,et al.  A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms , 2002, IEEE Trans. Geosci. Remote. Sens..

[22]  Xiaoli Ding,et al.  Multiple outlier detection by evaluating redundancy contributions of observations , 1996 .

[23]  Nico Adam,et al.  Velocity field retrieval from long term coherent points in radar interferometric stacks , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[24]  S. Buckley,et al.  Radar interferometry measurement of land subsidence , 2000 .

[25]  Michele Manunta,et al.  A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[26]  H. Zebker,et al.  High-Resolution Water Vapor Mapping from Interferometric Radar Measurements. , 1999, Science.

[27]  Howard A. Zebker,et al.  Decorrelation in interferometric radar echoes , 1992, IEEE Trans. Geosci. Remote. Sens..

[28]  Ricardo A. Olea,et al.  Geostatistics for Engineers and Earth Scientists , 1999, Technometrics.

[29]  Fabio Rocca,et al.  Submillimeter Accuracy of InSAR Time Series: Experimental Validation , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[30]  K. Feigl,et al.  Radar interferometry and its application to changes in the Earth's surface , 1998 .