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Editorial Board Members’ Collection Series: Application of InSAR Technology in Geodesy, Earthquake, Landslides and Other Disaster Warning

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Environmental Sensing".

Deadline for manuscript submissions: 25 February 2025 | Viewed by 59

Special Issue Editors


E-Mail Website
Guest Editor
School of Earth Sciences and Information Physics, Central South University, Changsha 410017, China
Interests: InSAR; GPS; seismic source parameter inversion; natural disaster warning

E-Mail Website
Guest Editor
School of Geophysics and Spatial Information, China University of Geosciences (Wuhan), Wuhan 430074, China
Interests: remote sensing techniques; seismic source location; seismic wave form fitting; seismic properties and seismic risk analysis

Special Issue Information

Dear Colleagues,

Natural disasters such as earthquakes, land subsidence, and landslides pose significant threats to both human life and infrastructure, resulting in substantial socioeconomic losses annually. Surface displacements provide crucial data for monitoring natural disasters, facilitating the inversion of the necessary geological/geophysical parameters and allowing us to deduce the mechanisms behind these events. Ultimately, these efforts contribute to our understanding of the behavior of natural disasters and to mitigating the losses that they cause. Among the techniques for deformation monitoring, Interferometric Synthetic Aperture Radar (InSAR) has been widely used to monitor natural disasters owing to its wide coverage, high accuracy, and efficiency in terms of labor. Over the last three decades, rapid advancements in radar sensors, computer science, and InSAR data processing algorithms have greatly enhanced our capabilities in monitoring natural disasters.

The Special Issue aims to gather high-quality articles related to InSAR data processing and its applications in earthquakes, land subsidence, landslides, and other natural disasters. Contributions may include, but are not limited to, the following topics:  

  • the improvement of InSAR data processing algorithms;
  • InSAR earthquake monitoring;
  • InSAR land subsidence monitoring;
  • InSAR landslide monitoring;
  • reviews of InSAR in natural disaster monitoring;
  • reviews of InSAR data processing.

Prof. Dr. Guangcai Feng
Prof. Dr. Yong Zheng
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. Sensors 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 2600 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

  • SAR/InSAR
  • InSAR processing
  • InSAR applications
  • earthquakes
  • land subsidence
  • landslides
  • disaster monitoring

Published Papers

This special issue is now open for submission.
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