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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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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. |
format | Online Article Text |
id | pubmed-8519160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT saylorcameron multifractalanalysisofaseismicmomentdistributionobtainedfrominsarinversion AT rundlejohnb multifractalanalysisofaseismicmomentdistributionobtainedfrominsarinversion AT donnellanandrea multifractalanalysisofaseismicmomentdistributionobtainedfrominsarinversion |