Automatic Retrieval of Tectonic Parameters with Neural Networks and Sar Interferometry: An Assessment with Experimental Data

A concurrent exploitation of the capabilities of neural networks and SAR interferometry is considered for the characterization of a seismic source and the estimation of its geometric parameters. This requires the generation of an appropriate number of synthetic interferograms necessary for the network training phase. After the training the network is ready to perform the inversion on new interferograms. The paper illustrates the assessment of such a methodology over a significant set of experimental data.