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Spatial forecasting of seismicity provided from Earth observation by space satellite technology
Understanding the controls on the distribution and magnitude of earthquakes is required for effective earthquake forecasting. We present a study that demonstrates that the distribution and size of earthquakes in Italy correlates with the steady state rate at which the Earth’s crust moves. We use a n...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298034/ https://www.ncbi.nlm.nih.gov/pubmed/32546797 http://dx.doi.org/10.1038/s41598-020-66478-9 |
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author | Farolfi, Gregorio Keir, Derek Corti, Giacomo Casagli, Nicola |
author_facet | Farolfi, Gregorio Keir, Derek Corti, Giacomo Casagli, Nicola |
author_sort | Farolfi, Gregorio |
collection | PubMed |
description | Understanding the controls on the distribution and magnitude of earthquakes is required for effective earthquake forecasting. We present a study that demonstrates that the distribution and size of earthquakes in Italy correlates with the steady state rate at which the Earth’s crust moves. We use a new high-resolution horizontal strain rate (S) field determined from a very dense velocity field derived from the combination of Global Navigation Satellite System (GNSS) and satellite radar interferometry from two decades of observations. Through a statistical approach we study the correlation between the S and the magnitude of M ≥ 2.5 earthquakes that occurred in the same period of satellite observations. We found that the probability of earthquakes occurring is linked to S by a linear correlation, and more specifically the probability that a strong seismic event occurs doubles with the doubling of S. It also means that lower horizontal strain rate zone can have as large earthquakes as high horizontal strain rate zones, just with a reduced probability. The work demonstrates an independent and quantitative tool to spatially forecast seismicity. |
format | Online Article Text |
id | pubmed-7298034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72980342020-06-18 Spatial forecasting of seismicity provided from Earth observation by space satellite technology Farolfi, Gregorio Keir, Derek Corti, Giacomo Casagli, Nicola Sci Rep Article Understanding the controls on the distribution and magnitude of earthquakes is required for effective earthquake forecasting. We present a study that demonstrates that the distribution and size of earthquakes in Italy correlates with the steady state rate at which the Earth’s crust moves. We use a new high-resolution horizontal strain rate (S) field determined from a very dense velocity field derived from the combination of Global Navigation Satellite System (GNSS) and satellite radar interferometry from two decades of observations. Through a statistical approach we study the correlation between the S and the magnitude of M ≥ 2.5 earthquakes that occurred in the same period of satellite observations. We found that the probability of earthquakes occurring is linked to S by a linear correlation, and more specifically the probability that a strong seismic event occurs doubles with the doubling of S. It also means that lower horizontal strain rate zone can have as large earthquakes as high horizontal strain rate zones, just with a reduced probability. The work demonstrates an independent and quantitative tool to spatially forecast seismicity. Nature Publishing Group UK 2020-06-16 /pmc/articles/PMC7298034/ /pubmed/32546797 http://dx.doi.org/10.1038/s41598-020-66478-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Farolfi, Gregorio Keir, Derek Corti, Giacomo Casagli, Nicola Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title | Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title_full | Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title_fullStr | Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title_full_unstemmed | Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title_short | Spatial forecasting of seismicity provided from Earth observation by space satellite technology |
title_sort | spatial forecasting of seismicity provided from earth observation by space satellite technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298034/ https://www.ncbi.nlm.nih.gov/pubmed/32546797 http://dx.doi.org/10.1038/s41598-020-66478-9 |
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