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Geosciences
Special Issues
Detecting Geospace Perturbations Caused by Earth II
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Detecting Geospace Perturbations Caused by Earth II

A special issue of Geosciences (ISSN 2076-3263).

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 2659

Special Issue Editors

Dr. Georgios Balasis

E-Mail Website
Guest Editor
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa & Vas. Pavlou Street, GR-15236 Penteli, Greece
Interests: space physics; space weather; geomagnetism; magnetic storms; complex systems; extreme geophysical events
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Angelo De Santis

E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
Interests: geomagnetism; earthquake precursors; LAIC; geosystemics; entropy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A systematic multiparametric and multiplatform approach to detect and study geo-space perturbations attributed to preparation processes related to natural hazards is fundamental in order to obtain useful insights on a series of complex dynamic phenomena of the Earth system, namely, earthquakes, volcanic and Saharan dust events, as well as geomagnetic disturbances. In particular, integrated analysis and interpretation of data from ground-based and spaceborne observations of the lower and upper atmospheres are of paramount importance for understanding the associated physical processes. In this Special Issue, we include pertinent studies on this field of research, presenting recent results and highlighting future directions for advances in the topic.

Dr. George Balasis
Prof. Dr. Angelo De Santis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural hazards
  • gravity waves
  • magnetospheric waves
  • geospace disturbances
  • earth observation

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Published Papers (1 paper)

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Research

48 pages, 8943 KiB  
Article
Optimal Setting of Earthquake-Related Ionospheric TEC (Total Electron Content) Anomalies Detection Methods: Long-Term Validation over the Italian Region
by Roberto Colonna, Carolina Filizzola, Nicola Genzano, Mariano Lisi and Valerio Tramutoli
Geosciences 2023, 13(5), 150; https://doi.org/10.3390/geosciences13050150 - 18 May 2023
Cited by 10 | Viewed by 2017
Abstract
Over the last decade, thanks to the availability of historical satellite observations that have begun to be significantly large and thanks to the exponential growth of artificial intelligence techniques, many advances have been made in the detection of geophysical parameters such as seismic-related [...] Read more.
Over the last decade, thanks to the availability of historical satellite observations that have begun to be significantly large and thanks to the exponential growth of artificial intelligence techniques, many advances have been made in the detection of geophysical parameters such as seismic-related anomalies. In this study, the variations of the ionospheric Total Electron Content (TEC), one of the main parameters historically proposed as a seismic-connected indicator, are analyzed. To make a statistically robust analysis of the complex phenomena involved, we propose a completely innovative machine-learning approach developed in the R programming language. Through this approach, an optimal setting of the multitude of methodological inputs currently proposed for the detection of ionospheric anomalies is performed. The setting is optimized by analyzing, for the first time, multi-year—mostly twenty-year—time series of TEC satellite data measured by global navigation satellite systems (GNSS) over the Italian region, matched with the corresponding multi-year time series of seismic events. Seismic events including all the countries of the Mediterranean area, up to Turkey, are involved in the analysis. Tens of thousands of possible combinations of input methodological parameters are simulated and classified according to pre-established criteria. Several inputs examined return clear results. These results combined with each other highlight the presence of anomalous seismic-related sequences that have an extremely low probability of having been detected randomly (up to 2 out of 1 million). The anomalies identified represent the most anomalous behaviors of the TEC recorded during the entire period under investigation (e.g., 20 years). Some of the main conclusions are that, at mid-latitudes, ① the detection of seismic-TEC anomalies can be more efficient looking for punctual rather than persistent phenomena; ② the optimal thresholds for the identification of co-seismic anomalies can assume different values depending on type of anomaly (positive or negative) and type of observation; ③ single GNSS receiver data can be useful for capturing local earthquake-ionospheric effects and Global Ionospheric Maps (GIM) data can be functional in detecting large-scale earthquake-ionospheric effects; ④ earthquakes deeper than 50 km are less likely to affect the ionosphere. Full article
(This article belongs to the Special Issue Detecting Geospace Perturbations Caused by Earth II)
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