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Remote Sensing
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Remote Sensing Monitoring for Earthquakes, Tectonics and Seismic Hazards
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Remote Sensing Monitoring for Earthquakes, Tectonics and Seismic Hazards

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 15 December 2024 | Viewed by 1948

Special Issue Editors

Dr. Nicola Alessandro Pino

E-Mail Website
Guest Editor
Istituto Nazionale Di Geofisica E Vulcanologia, 605, 00143 Rome, Italy
Interests: remote sensing; tectonics; earthquakes; seismic hazard
Dr. Stefano Carlino

E-Mail Website
Guest Editor
Istituto Nazionale Di Geofisica E Vulcanologia, 605, 00143 Rome, Italy
Interests: volcanology; geodesy and gravimetry; volcano seismology; heat flow; tectonics
Special Issues, Collections and Topics in MDPI journals
Dr. Raffaele Castaldo

E-Mail Website
Guest Editor
Institute for Electromagnetic Sensing of the Environment (IREA-CNR), Via Diocleziano, 328, 80124 Naples, Italy
Interests: remote and proximal sensing; InSAR data; finite element modelling; deformation field; potential field; multiscale analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technological improvements in sensors and advances in computational power, together with the increased number of satellites dedicated to Earth observation, have promoted a significant evolution in remote sensing science in the last decades.

Satellite-, aircraft-, and land-based geophysical, geodetic, and geochemical data have proved to be key tools to not only extensively map surface phenomena associated with tectonics and earthquakes, even for light-magnitude events, but also to depict tectonic strain, allowing the identification of areas of increased seismic risk.

Additionally, continuous data (in space and time) on slow surface displacement, e.g., post-seismic relaxation following large earthquakes, represent a precious reference for modeling the rheology of the crust and upper mantle in these regions.

Besides applications to natural seismic hazards, remote sensing techniques have also demonstrated the ability to detect the surface effects of underground industrial exploitation, providing timely information on the possible risks associated with induced seismicity and deformation caused by these anthropic activities.

More recently, the introduction of robot and drone technology in remote data acquisition has also facilitated more detailed characterizations of fault movements and monitoring of volcano tectonic activity, representing strong support in constraining the interpretation of satellite data.

Dr. Nicola Alessandro Pino
Dr. Stefano Carlino
Dr. Raffaele Castaldo
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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

  • remote sensing techniques
  • tectonics
  • earthquakes
  • lower crust and upper mantle rheology
  • seismic hazard
  • induced seismicity and ground deformation

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Published Papers (1 paper)

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Research

24 pages, 11944 KiB  
Article
Advancing the Limits of InSAR to Detect Crustal Displacement from Low-Magnitude Earthquakes through Deep Learning
by Elena C. Reinisch, Charles J. Abolt, Erika M. Swanson, Bertrand Rouet-Leduc, Emily E. Snyder, Kavya Sivaraj and Kurt C. Solander
Remote Sens. 2024, 16(11), 2019; https://doi.org/10.3390/rs16112019 - 4 Jun 2024
Viewed by 1240
Abstract
Detecting surface deformation associated with low-magnitude (Mw≤5) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic [...] Read more.
Detecting surface deformation associated with low-magnitude (Mw≤5) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic events, and thus characterizing the crustal displacement associated with them is crucial for regional seismic hazard assessment. We combine InSAR time-series techniques with a Deep Learning (DL) autoencoder denoiser to detect the magnitude and extent of crustal deformation from the Mw=3.4 Gallina, New Mexico earthquake that occurred on 30 July 2020. Although InSAR alone cannot detect event-related deformation from such a low-magnitude seismic event, application of the DL method reveals maximum displacements as small as (±2.5 mm) in the vicinity of both the fault and earthquake epicenter without prior knowledge of the fault system. This finding improves small-scale displacement discernment with InSAR by an order of magnitude relative to previous studies. We additionally estimate best-fitting fault parameters associated with the observed deformation. The application of the DL technique unlocks the potential for low-magnitude earthquake studies, providing new insights into local fault geometries and potential risks from higher-magnitude earthquakes. This technique also permits low-magnitude event monitoring in areas where seismic networks are sparse, allowing for the possibility of global fault deformation monitoring. Full article
(This article belongs to the Special Issue Remote Sensing Monitoring for Earthquakes, Tectonics and Seismic Hazards)
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