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

Cameron Saylor1, John B Rundle1,2,3, Andrea Donnellan4

  • 1Department of Physics and Astronomy University of California, Davis Davis CA USA.

Earth and Space Science (Hoboken, N.J.)
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Summary
This summary is machine-generated.

This study introduces a new method using seismic point sources and a genetic algorithm to analyze Interferometric Synthetic Aperture Radar (InSAR) data for mapping hidden earthquake faults. The analysis reveals multifractal properties in fault distributions, offering a novel tool for geological research.

Keywords:
InSARgenetic algorithminversionmultifractal

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Area of Science:

  • Geophysics
  • Remote Sensing
  • Computational Seismology

Background:

  • Interferometric Synthetic Aperture Radar (InSAR) interferograms provide crucial data on subsurface fault systems.
  • Accurately mapping earthquake faults remains a significant challenge in geophysical research.

Purpose of the Study:

  • To develop and apply a novel approach for fitting InSAR ground deformation data using distributed seismic point sources.
  • To assess the utility of a genetic algorithm in determining seismic source parameters from InSAR data.
  • To investigate the multifractal properties of fault systems revealed by this new method.

Main Methods:

  • Utilizing a genetic algorithm to fit InSAR ground deformation data with a distribution of multiple seismic point sources.
  • Applying the developed algorithm to an ALOS-2 InSAR interferogram.
  • Performing multifractal analysis on the resulting seismic source distribution.

Main Results:

  • The developed algorithm successfully fits InSAR ground deformation data.
  • The resulting distribution of seismic point sources exhibits multifractal properties.
  • The approach provides a new potential tool for mapping earthquake faults.

Conclusions:

  • The integration of genetic algorithms with InSAR data offers a promising new method for seismic source analysis.
  • The observed multifractal characteristics of fault distributions enhance our understanding of earthquake fault systems.
  • This approach presents both advantages and disadvantages that warrant further investigation for practical applications in fault mapping.