Login / Signup

Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion.

Cameron SaylorJohn B RundleAndrea Donnellan
Published in: Earth and space science (Hoboken, N.J.) (2021)
Interferometric synthetic aperture radar (InSAR) interferograms contain valuable information about the fault systems hidden beneath the surface of the Earth. In a new approach, we aim to fit InSAR ground deformation data using a distribution of multiple seismic point sources whose parameters are found by a genetic algorithm. The resulting source distribution could provide another useful tool in solving the difficult problem of accurately mapping earthquake faults. We apply the algorithm to an ALOS-2 InSAR interferogram and perform a multifractal analysis on the resulting distribution, finding that it exhibits multifractal properties. We report first results and discuss advantages and disadvantages of this approach.
Keyphrases
  • machine learning
  • deep learning
  • gene expression
  • magnetic resonance imaging
  • neural network
  • drinking water
  • magnetic resonance
  • health information
  • computed tomography
  • social media
  • data analysis