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Geosciences
Special Issues
Remote Sensing Application for Earthquake and Tsunami Damage Assessment
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Remote Sensing Application for Earthquake and Tsunami Damage Assessment

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (28 February 2019) | Viewed by 20863

Special Issue Editor

Prof. Dr. Masashi Matsuoka

E-Mail Website
Guest Editor
Department of Architecture and Building Engineering, Tokyo Institute of Technology, Yokohama 226-8502, Japan
Interests: earthquake engineering; geomorphology; GIS and application of remote sensing technology to disaster management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Geosciences aims to gather high-quality original research articles, reviews and technical notes on “Remote Sensing Application for Earthquake and Tsunami Damage Assessment”.

Remote sensing technology has started to be used dramatically in various fields in the 2000s. The ground resolution and observation frequency improvements, systematic observation system with multiple artificial satellites, and advancements of computers and network technologies have become the driving forces, not only in areas, such as solutions to global environmental problems and resource exploration in recent years, application to disaster mitigation fields, such as collection of damage information and grasp of recovery/reconstruction situation are remarkable. One of them is the advancement of damage detection technology, immediately after the occurrence of a disaster, based on observation data for earthquakes and tsunamis that occur around the world. Specifically, the effectiveness of remote sensing technology has been demonstrated in a wide range of subjects, such as wide area recognition of earthquake damage and tsunami inundation areas, quantitative evaluation of structure and geotechnical damage, time series analysis of crustal deformation, and AI (artificial intelligence) applications for disaster management.

Therefore, I would like to invite you to submit articles about your recent work with respect to the above and/or the following topics:

  • Damage and loss estimation
  • Multi-sensor and multi-platform observation
  • Fusion of simulation and sensing technologies
  • Monitoring recovery process
  • Building inventory data development for damage assessment
  • Utilization of remote sensing archive

Prof. Masashi Matsuoka
Guest Editor

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

  • remote sensing
  • GIS
  • image processing
  • damage detection
  • digital building model
  • machine learning
  • fragility function
  • data integration
  • urban mapping
  • ground truth

Related Special Issues

Published Papers (3 papers)

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Research

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24 pages, 49502 KiB  
Article
Sequential Earthquake Damage Assessment Incorporating Optimized sUAV Remote Sensing at Pescara del Tronto
by Michael Freeman, Cory Vernon, Bryce Berrett, Nicole Hastings, Jeff Derricott, Jenessa Pace, Benjamin Horne, Joshua Hammond, Joseph Janson, Filiberto Chiabrando, John Hedengren and Kevin Franke
Geosciences 2019, 9(8), 332; https://doi.org/10.3390/geosciences9080332 - 29 Jul 2019
Cited by 12 | Viewed by 5213
Abstract
A sequence of large earthquakes in central Italy ranging in moment magnitudes (Mw) from 4.2 to 6.5 caused significant damage to many small towns in the area. After each earthquake in 2016 (24 August and 26 October), automated small unmanned aerial vehicles (sUAV) [...] Read more.
A sequence of large earthquakes in central Italy ranging in moment magnitudes (Mw) from 4.2 to 6.5 caused significant damage to many small towns in the area. After each earthquake in 2016 (24 August and 26 October), automated small unmanned aerial vehicles (sUAV) acquired valuable imagery data for post-hazard reconnaissance in the mountain village of Pescara del Tronto, and were applied to 3D reconstruction using Structure-from-Motion (SfM). In July 2018, the site was again monitored to obtain additional imagery data capturing changes since the last visit following the 30 October 2016 Earthquake. A genetic-based mission-planning algorithm that delivers optimal viewpoints and path planning was field tested and reduced the required photos for 3D reconstruction by 9.1%. The optimized 3D model provides a better understanding of the current conditions of the village, when compared to the nadir models, by containing fewer holes on angled surfaces, including an additional 17% surface area, and with a comparable ground-sampling distance (GSD) of ≈2.4 cm/px (≈1.5 cm/px when adjusted for camera pixel density). The resulting three time-lapse models provide valuable metrics for ground motion, progression of damage, resilience of the village, and the recovery progress over a span of two years. Full article
(This article belongs to the Special Issue Remote Sensing Application for Earthquake and Tsunami Damage Assessment)
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14 pages, 7010 KiB  
Article
A Weighted Overlay Method for Liquefaction-Related Urban Damage Detection: A Case Study of the 6 September 2018 Hokkaido Eastern Iburi Earthquake, Japan
by Sadra Karimzadeh and Masashi Matsuoka
Geosciences 2018, 8(12), 487; https://doi.org/10.3390/geosciences8120487 - 14 Dec 2018
Cited by 16 | Viewed by 5891
Abstract
We performed interferometric synthetic aperture radar (InSAR) analyses to observe ground displacements and assess damage after the M 6.6 Hokkaido Eastern Iburi earthquake in northern Japan on 6 September 2018. A multitemporal SAR coherence map is extracted from 3-m resolution ascending (track 116) [...] Read more.
We performed interferometric synthetic aperture radar (InSAR) analyses to observe ground displacements and assess damage after the M 6.6 Hokkaido Eastern Iburi earthquake in northern Japan on 6 September 2018. A multitemporal SAR coherence map is extracted from 3-m resolution ascending (track 116) and descending (track 18) ALOS-2 Stripmap datasets to cover the entire affected area. To distinguish damaged buildings associated with liquefaction, three influential parameters from the space-based InSAR results, ground-based LiquickMap (from seismic intensities in Japanese networks) and topographic slope of the study area are considered together in a weighted overlay (WO) analysis, according to prior knowledge of the study area. The WO analysis results in liquefaction potential values that agree with our field survey results. To investigate further, we conducted microtremor measurements at 14 points in Hobetsu, in which the predominant frequency showed a negative correlation with the WO values, especially when drastic coherence decay occurred. Full article
(This article belongs to the Special Issue Remote Sensing Application for Earthquake and Tsunami Damage Assessment)
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Review

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28 pages, 24941 KiB  
Review
Tsunami Damage Detection with Remote Sensing: A Review
by Shunichi Koshimura, Luis Moya, Erick Mas and Yanbing Bai
Geosciences 2020, 10(5), 177; https://doi.org/10.3390/geosciences10050177 - 12 May 2020
Cited by 41 | Viewed by 9081
Abstract
Tsunamis are rare events compared with the other natural disasters, but once it happens, it can be extremely devastating to the coastal communities. Extensive inland penetration of tsunamis may cause the difficulties of understanding its impact in the aftermath of its generation. Therefore [...] Read more.
Tsunamis are rare events compared with the other natural disasters, but once it happens, it can be extremely devastating to the coastal communities. Extensive inland penetration of tsunamis may cause the difficulties of understanding its impact in the aftermath of its generation. Therefore the social needs to technologies of detecting the wide impact of great tsunamis have been increased. Recent advances of remote sensing and technologies of image analysis meet the above needs and lead to more rapid and efficient understanding of tsunami affected areas. This paper provides a review of how remote sensing methods have developed to contribute to post-tsunami disaster response. The evaluations in the performances of the remote sensing methods are discussed according to the needs of tsunami disaster response with future perspective. Full article
(This article belongs to the Special Issue Remote Sensing Application for Earthquake and Tsunami Damage Assessment)
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