DocumentCode
575982
Title
Retrieval of fault parameters of October 23, 2011 Eastern Turkey eartquake obtained by Neural Network
Author
Picchiani, Matteo ; Chini, Michael ; Del Frate, Fabio ; Stramondo, Salvatore ; Schiavon, Giovanni
Author_Institution
Earth Obs. Lab., Tor Vergata Univ., Rome, Italy
fYear
2012
fDate
22-27 July 2012
Firstpage
2998
Lastpage
3001
Abstract
We have analysed the seismic source of the active fault generated Van Mw=7.1 earthquake occurred in Eastern Turkey the 23rd October 2011. To this aim the surface displacement field has been measured applying SAR Interferometry (InSAR) technique to the available dataset of coseismic COSMO-SkyMed image pairs. The seismic source model has been obtained by the use of a data inversion procedure based on the concurrent application of InSAR techniques and Neural Networks. The proposed approach elaborates the information on the coseismic deformation pattern stemming from available differential interferograms. The interferogram is the expression of the active fault at depth, thus its shape, size and its features somehow refer to the geometry and slip of the fault generating the seism. A Neural Network has been trained to recognize some fault parameters (Length, Width, Strike, Dip, Depth) from the unwrapped interferogram. The retrieval exercise consists in estimating these parameters from the coseismic interferogram exploiting Neural Networks.
Keywords
earthquakes; faulting; geophysical signal processing; inverse problems; neural nets; parameter estimation; radar interferometry; radar signal processing; remote sensing by radar; synthetic aperture radar; AD 2011 10 23; InSAR; SAR interferometry; active fault; coseismic COSMO-SkyMed image pairs; coseismic deformation pattern; data inversion procedure; differential interferograms; eastern Turkey earthquake; fault depth; fault dip; fault length; fault parameter recognition; fault parameter retrieval; fault strike; fault width; neural network; seismic source model; surface displacement field; unwrapped interferogram; Artificial neural networks; Displacement measurement; Earthquakes; Interferometry; Seismic measurements; Synthetic aperture radar; COSMO-SkyMed; Neural networks; SAR Interferometry; Seismic parameters retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6350795
Filename
6350795
Link To Document