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Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion

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 fou...

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Detalles Bibliográficos
Autores principales: Saylor, Cameron, Rundle, John B., Donnellan, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519160/
https://www.ncbi.nlm.nih.gov/pubmed/34692923
http://dx.doi.org/10.1029/2020EA001433
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author Saylor, Cameron
Rundle, John B.
Donnellan, Andrea
author_facet Saylor, Cameron
Rundle, John B.
Donnellan, Andrea
author_sort Saylor, Cameron
collection PubMed
description 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.
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spelling pubmed-85191602021-10-22 Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion Saylor, Cameron Rundle, John B. Donnellan, Andrea Earth Space Sci Technical Reports: Methods 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. John Wiley and Sons Inc. 2021-09-16 2021-09 /pmc/articles/PMC8519160/ /pubmed/34692923 http://dx.doi.org/10.1029/2020EA001433 Text en © 2021 The Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Technical Reports: Methods
Saylor, Cameron
Rundle, John B.
Donnellan, Andrea
Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title_full Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title_fullStr Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title_full_unstemmed Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title_short Multifractal Analysis of a Seismic Moment Distribution Obtained From InSAR Inversion
title_sort multifractal analysis of a seismic moment distribution obtained from insar inversion
topic Technical Reports: Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519160/
https://www.ncbi.nlm.nih.gov/pubmed/34692923
http://dx.doi.org/10.1029/2020EA001433
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