Seismic Source Quantitative Parameters Retrieval From InSAR Data and Neural Networks

The basic idea of this paper relies on the concurrent exploitation of the capabilities of neural networks (NNs) and SAR interferometry (InSAR) for the characterization of a seismic source and the estimation of its geometric parameters. When a moderate-to-strong earthquake occurs, we can apply the InSAR technique to compute a differential interferogram. The earthquake is generated by an active seismogenic fault having its own specific geometry. The corresponding differential interferogram contains, in principle, information concerning the geometry of the seismic source that the earthquake comes from. To perform the inversion operation, a novel approach based on NNs is considered. This requires the generation of a statistically significant number of synthetic interferograms necessary for the network training phase. Each of them corresponds to a different combination of fault geometric parameters. After the training, the network is ready to perform, in real time, the inversion on new differential interferograms. This paper illustrates such a methodology and its validation on a set of experimental data.

[1]  T. Wright,et al.  The 2003 Bam (Iran) earthquake: Rupture of a blind strike‐slip fault , 2004 .

[2]  C. Werner,et al.  Satellite radar interferometry: Two-dimensional phase unwrapping , 1988 .

[3]  Ian Parsons,et al.  Surface deformation due to shear and tensile faults in a half-space , 1986 .

[4]  H. Zebker,et al.  Fault Slip Distribution of the 1999 Mw 7.1 Hector Mine, California, Earthquake, Estimated from Satellite Radar and GPS Measurements , 2002 .

[5]  C. Zehner,et al.  Application of neural algorithms for a real time estimation of ozone profiles from GOME measurements , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

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

[7]  Thomas H. Heaton,et al.  The slip history of the 1994 Northridge, California, earthquake determined from strong-motion, teleseismic, GPS, and leveling data , 1996, Bulletin of the Seismological Society of America.

[8]  Giorgio Franceschetti,et al.  The September 26, 1997 Colfiorito, Italy, earthquakes: Modeled coseismic surface displacement from SAR interferometry and GPS , 1999 .

[9]  Zhong Lu,et al.  Deformation of the 2002 Denali Fault Earthquakes, mapped by Radarsat-1 interferometry , 2003 .

[10]  H. Kanamori The energy release in great earthquakes , 1977 .

[11]  Kurt L. Feigl,et al.  RNGCHN: a program to calculate displacement components from dislocations in an elastic half-space with applications for modeling geodetic measurements of crustal deformation , 1999 .

[12]  Francesca Romana Cinti,et al.  InSAR surface displacement field and fault modelling for the 2003 Bam earthquake (southeastern Iran) , 2005 .

[13]  Claudio Prati,et al.  SAR Interferometry: A 2-D Phase Unwrapping Technique Based On Phase And Absolute Values Informations , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[14]  Salvatore Stramondo,et al.  Slip distribution of the 1997 Umbria‐Marche earthquake sequence: Joint inversion of GPS and synthetic aperture radar interferometry data , 2002 .

[15]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[16]  S. Casadio,et al.  Neural networks for the dimensionality reduction of GOME measurement vector in the estimation of ozone profiles , 2005 .

[17]  M. F. Iapaolo,et al.  Automatic selection by means of neural networks of GOME optimum spectral channels for the retrieval of ozone vertical profiles , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[18]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[19]  K. Feigl,et al.  The displacement field of the Landers earthquake mapped by radar interferometry , 1993, Nature.

[20]  S. Billings Simulated annealing for earthquake location , 1994 .

[21]  T. A. Grogan,et al.  Comparative analysis of five neural network models , 1992 .

[22]  Hiroo Kanamori,et al.  Magnitude scale and quantification of earthquakes , 1983 .

[23]  Concetta Nostro,et al.  Static stress changes and fault interaction during the 1997 Umbria-Marche earthquake sequence , 2000 .

[24]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[25]  Fabio Rocca,et al.  Focusing SAR data with time-varying Doppler centroid , 1992, IEEE Trans. Geosci. Remote. Sens..

[26]  Hermann Kaufmann,et al.  The 2003 Bam (SE Iran) earthquake: precise source parameters from satellite radar interferometry , 2004 .

[27]  James Jackson,et al.  Seismotectonic, rupture process, and earthquake-hazard aspects of the 2003 December 26 Bam, Iran, earthquake , 2006 .

[28]  Hiroo Kanamori,et al.  Source complexity of the 1994 Northridge earthquake and its relation to aftershock mechanisms , 1996, Bulletin of the Seismological Society of America.

[29]  Thierry Rabaute,et al.  Radar interferometry: limits and potential , 1993, IEEE Trans. Geosci. Remote. Sens..

[30]  D. L. Anderson,et al.  Preliminary reference earth model , 1981 .

[31]  Paolo Ferrazzoli,et al.  Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks , 2003 .

[32]  Howard A. Zebker,et al.  New approaches in interferometric SAR data processing , 1992, IEEE Trans. Geosci. Remote. Sens..

[33]  Lauro Chiaraluce,et al.  Imaging the complexity of an active normal fault system: The 1997 Colfiorito (central Italy) case study , 2003 .

[34]  J. C. Savage,et al.  Surface deformation associated with dip‐slip faulting , 1966 .

[35]  Salvatore Stramondo,et al.  Rupture history of the 1997 umbria-Marche (central Italy) main shocks from the inversion of GPS, DInSAR and near field strong motion data , 2004 .

[36]  Satoshi Fujiwara,et al.  Synthetic aperture radar interferogram of the 1995 Kobe Earthquake and its geodetic inversion , 1997 .

[37]  Christian Bignami,et al.  Finite fault inversion of DInSAR coseismic displacement of the 2009 L'Aquila earthquake (central Italy) , 2009 .

[38]  K. Feigl,et al.  Coseismic and Postseismic Fault Slip for the 17 August 1999, M = 7.5, Izmit, Turkey Earthquake. , 2000, Science.

[39]  Charles Werner,et al.  Accuracy of topographic maps derived from ERS-1 interferometric radar , 1994, IEEE Trans. Geosci. Remote. Sens..

[40]  Louis A. Romero,et al.  Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods , 1994 .

[41]  M. Tesauro,et al.  Modeling coseismic displacements resulting from SAR interferometry and GPS measurements during the 1997 Umbria-Marche seismic sequence , 2000 .

[42]  Christian Bignami,et al.  The May 12, 2008, (Mw 7.9) Sichuan Earthquake (China): Multiframe ALOS-PALSAR DInSAR Analysis of Coseismic Deformation , 2010, IEEE Geoscience and Remote Sensing Letters.

[43]  Semih Ergintav,et al.  Bulletin of the Seismological Society of America , 2002 .

[44]  A. Donnellan,et al.  Combined GPS and InSAR Models of Postseismic Deformation from the Northridge Earthquake , 2002 .