Seismic source parameters in New Zealand from broad-band data

Neural Networks to Retrieve Seismic Source Parameters

The use of supervised neural networks for the estimation of seismic source parameters from SAR interferometric data is presented in this paper. The RNGCHN software allowed the generation of the input-output pairs necessary for the learning phase of the net. After being trained, the net has been tested on real measured data. The obtained results encourage future developments of such an approach.

Source Separation on Seismic Data

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Neural Networks to Retrieve Seismic Source Parameters by Sar Interferometry

The use of supervised neural networks for the estimation of seismic source parameters from SAR interferometric data is presented in this paper. The RNGCHN software allowed the generation of the input-output pairs necessary for the learning phase of the net. After being trained, the net has been tested on real measured data. The obtained results encourage future developments of such an approach.

Rapidly Estimated Seismic Source Parameters for the 16 September 2015

On 16 September 2015, a great (Mw 8.3) interplate thrust earthquake ruptured offshore Illapel, Chile, producing a 4.7-m local tsunami. The last major rupture in the region was a 1943 MS 7.9 event. Seismic methods for rapidly characterizing the source process, of value for tsunami warning, were applied. The source moment tensor could be obtained robustly by W-phase inversion both within minutes ...

New Zealand Data Sheet Sandostatin