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Special Issue "Radar Interferometry for Geohazards"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 30 June 2018

Special Issue Editors

Guest Editor
Prof. Zhong Lu

Huffington Department of Earth Sciences, Southern Methodist University, PO Box 750395, Dallas, TX 75275, USA
Website | E-Mail
Phone: 214-768-0101
Interests: technique developments of interferometric synthetic aperture radar (InSAR) and multi-temporal InSAR processing, and their applications to natural hazard monitoring and natural resource management
Guest Editor
Prof. Dr. Zhenhong Li

School of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
Website | E-Mail
Phone: +44 (0) 191 208 5704
Interests: InSAR atmospheric correction models, advanced InSAR time series techniques, high-rate GNSS, landslides (slope instability), stability monitoring of man-made infrastructure
Guest Editor
Dr. Roberto Tomas

Department of Civil Engineering, University of Alicante, P.O. Box 99, E-03080 Alicante, Spain
Website | E-Mail
Interests: land subsidence; landslides; InSAR; LiDAR; building monitoring

Special Issue Information

Dear Colleagues

Interferometric Synthetic Aperture Radar (InSAR) has been proven to be a powerful remote sensing tool to map changes in the Earth’s surface. InSAR has led to many new insights into geophysical and geological processes of geohazards, including earthquakes, volcanoes, landslides, land subsidence and sinkholes, among others. The launch of new radar satellites and the advent of cloud/parallel computing have been leading us to a new era of operational InSAR, but it is believed that there is still room to further advance InSAR processing algorithms and applications.

This Special Issue will focus on (i) innovative InSAR algorithms and processing methods, and (ii) characterizing and modeling geohazards from InSAR and other geophysical and geological measurements. Submissions are encouraged to cover a broad range of topics, which may include, but are not limited to, the following activities. Papers address anthropogenic hazards using innovative processing and modeling techniques are also welcome.

  • InSAR algorithm development, automation, implementation, and validation
  • Crustal deformation and earthquake cycle
  • Landslides
  • Volcanic processes
  • Land subsidence
  • Sinkholes
  • Mining activities
  • Groundwater related subsidence
  • Fracking and induced seismicity
 

Prof. Dr. Zhong Lu
Prof. Dr. Zhenhong Li
Dr. Roberto Tomás
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 papers will be 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 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 1600 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 processing
  • Interferometric synthetic aperture radar (InSAR) 
  • Time series analysis
  • Earthquake
  • Landslide
  • Land subsidence
  • Sinkhole
  • Volcano
  • Fracking
  • Geohazards 
  • Man-made hazards

Published Papers (3 papers)

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Research

Open AccessArticle A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images
Remote Sens. 2017, 9(10), 1002; doi:10.3390/rs9101002
Received: 4 August 2017 / Revised: 12 September 2017 / Accepted: 21 September 2017 / Published: 28 September 2017
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Abstract
This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and
[...] Read more.
This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Deriving Spatio-Temporal Development of Ground Subsidence Due to Subway Construction and Operation in Delta Regions with PS-InSAR Data: A Case Study in Guangzhou, China
Remote Sens. 2017, 9(10), 1004; doi:10.3390/rs9101004
Received: 17 July 2017 / Revised: 22 September 2017 / Accepted: 23 September 2017 / Published: 28 September 2017
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Abstract
Subways have been an important method for relieving traffic pressures in urban areas, but ground subsidence, during construction and operation, can be a serious problem as it may affect the safety of its operation and that of the surrounding buildings. Thus, conducting long-term
[...] Read more.
Subways have been an important method for relieving traffic pressures in urban areas, but ground subsidence, during construction and operation, can be a serious problem as it may affect the safety of its operation and that of the surrounding buildings. Thus, conducting long-term ground deformation monitoring and modeling for subway networks are essential. Compared with traditional geodetic methods, the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique offers wider coverage and denser measurements along subway lines. In this study, we mapped the surface deformation of the Guangzhou subway network with Advanced Synthetic Aperture Radar (ASAR) and Phased Array Type L-band Synthetic Aperture Radar (PALSAR) data using the Interferometric Point Target Analysis (IPTA) technique. The results indicate that newly excavated tunnels have regional subsidence with an average rate of more than 8 mm/year, as found on Lines Two, Three, Six, and GuangFo (GF). Furthermore, we determined the spatio-temporal subsidence behavior of subways with PALSAR in delta areas using Peck’s formula and the logistic time model. We estimated the tunneling-related parameters in soft soil areas, which had not been previously explored. We examined a section of line GF, as an example, to estimate the ground settlement trough development. The results showed the maximum settlement increased from −5.2 mm to −23.6 mm and its ground loss ratio ranged from 1.5–8.7% between 13 July 2008 and 19 January 2011. In addition, we found that the tunnels in line GF will become stable after a period of about 2300 days in peak subsidence areas. The results show that the proposed approach can help explain the dynamic ground subsidence along a metro line. This study can provide references for urban subway projects in delta areas, and for the risk assessment of nearby buildings and underground pipelines along metro lines. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle An Adaptive Offset Tracking Method with SAR Images for Landslide Displacement Monitoring
Remote Sens. 2017, 9(8), 830; doi:10.3390/rs9080830
Received: 15 July 2017 / Revised: 29 July 2017 / Accepted: 9 August 2017 / Published: 11 August 2017
PDF Full-text (10906 KB) | HTML Full-text | XML Full-text
Abstract
With the development of high-resolution Synthetic Aperture Radar (SAR) systems, researchers are increasingly paying attention to the application of SAR offset tracking methods in ground deformation estimation. The traditional normalized cross correlation (NCC) tracking method is based on regular matching windows. For areas
[...] Read more.
With the development of high-resolution Synthetic Aperture Radar (SAR) systems, researchers are increasingly paying attention to the application of SAR offset tracking methods in ground deformation estimation. The traditional normalized cross correlation (NCC) tracking method is based on regular matching windows. For areas with different moving characteristics, especially the landslide boundary areas, the NCC method will produce incorrect results. This is because in landslide boundary areas, the pixels of the regular matching window include two or more types of moving characteristics: some pixels with large displacement, and others with small or no displacement. These two kinds of pixels are uncorrelated, which result in inaccurate estimations. This paper proposes a new offset tracking method with SAR images based on the adaptive matching window to improve the accuracy of landslide displacement estimation. The proposed method generates an adaptive matching window that only contains pixels with similar moving characteristics. Three SAR images acquired by the Jet Propulsion Laboratory’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected to estimate the surface deformation of the Slumgullion landslide located in the southwestern Colorado, USA. The results show that the proposed method has higher accuracy than the traditional NCC method, especially in landslide boundary areas. Furthermore, it can obtain more detailed displacement information in landslide boundary areas. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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