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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

Southern Methodist University, Roy M. Huffington Department of Earth Sciences, Dallas, TX 75275-0395, USA
Website | E-Mail
Phone: 214-768-0101
Interests: Radar remote sensing of geohazards
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
Prof. 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 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

  • SAR processing
  • Interferometric synthetic aperture radar (InSAR) 
  • Time series analysis
  • Earthquake
  • Landslide
  • Land subsidence
  • Sinkhole
  • Volcano
  • Fracking
  • Geohazards 
  • Man-made hazards

Published Papers (14 papers)

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Research

Open AccessArticle Small Magnitude Co-Seismic Deformation of the 2017 Mw 6.4 Nyingchi Earthquake Revealed by InSAR Measurements with Atmospheric Correction
Remote Sens. 2018, 10(5), 684; https://doi.org/10.3390/rs10050684
Received: 5 April 2018 / Revised: 24 April 2018 / Accepted: 26 April 2018 / Published: 28 April 2018
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Abstract
The Nyingchi Mw 6.4 earthquake on 17 November 2017 is the first large event since 1950 at the southeast end of the Jiali fault. This event was captured by interferometric synthetic aperture radar (InSAR) measurements from the European Space Agency (ESA) Sentinel-1A radar
[...] Read more.
The Nyingchi Mw 6.4 earthquake on 17 November 2017 is the first large event since 1950 at the southeast end of the Jiali fault. This event was captured by interferometric synthetic aperture radar (InSAR) measurements from the European Space Agency (ESA) Sentinel-1A radar satellite, which provide the potential to determine the fault plane, as well as the co-seismic slip distribution, and understand future seismic hazards. However, due to the limited magnitude of surface displacements and the strong topography variations, InSAR-derived co-seismic signals are contaminated by strong tropospheric effects which makes it difficult (if not impossible) to determine the source parameters and co-seismic slip distribution. In this paper, we employ the Generic Atmospheric Correction Online Service for InSAR (GACOS) to generate correction maps for the co-seismic interferograms, and successfully extract co-seismic surface displacements for this large event. The phase standard deviation after correction for a seriously-contaminated interferogram reaches 0.8 cm, significantly improved from the traditional phase correlation analysis (1.13 cm) or bilinear interpolation (1.28 cm) methods. Our best model suggests that the seismogenic fault is a NW–SE striking back-thrust fault with a right-lateral strike slip component. This reflects the strain partitioning of NE shortening and eastward movement of the Eastern Tibetan plateau due to the oblique convergence between the Indian and Eurasian plates. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Multi-Temporal DInSAR to Characterise Landslide Ground Deformations in a Tropical Urban Environment: Focus on Bukavu (DR Congo)
Remote Sens. 2018, 10(4), 626; https://doi.org/10.3390/rs10040626
Received: 14 March 2018 / Revised: 5 April 2018 / Accepted: 9 April 2018 / Published: 18 April 2018
PDF Full-text (4089 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Landslides can lead to high impacts in less developed countries, particularly in tropical environments where a combination of intense rainfall, active tectonics, steep topography, and high population density can be found. However, the processes controlling landslide initiation and their evolution through time remains
[...] Read more.
Landslides can lead to high impacts in less developed countries, particularly in tropical environments where a combination of intense rainfall, active tectonics, steep topography, and high population density can be found. However, the processes controlling landslide initiation and their evolution through time remains poorly understood. Here we show the relevance of the use of the multi-temporal differential radar interferometric (DInSAR) technique to characterise ground deformations associated with landslides in the rapidly-expanding city of Bukavu (DR Congo). We use 70 COSMO-SkyMed synthetic aperture radar images acquired between March 2015 and April 2016 with a mean revisiting time of eight days to produce ground deformation rate maps and displacement time series using the small baseline subset approach. We find that various landslide processes of different ages, mechanisms, and states of activity can be identified. Ground deformations revealed by DInSAR are found consistent with field observations and differential GPS measurements. Our analysis highlights the ability of DInSAR to grasp landslide deformation patterns affecting the complex tropical-urban environment of the city of Bukavu. However, longer time series will be needed to infer landside responses to climate, seismic, and anthropogenic drivers. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Spatiotemporal Evolution of Land Subsidence in the Beijing Plain 2003–2015 Using Persistent Scatterer Interferometry (PSI) with Multi-Source SAR Data
Remote Sens. 2018, 10(4), 552; https://doi.org/10.3390/rs10040552
Received: 17 January 2018 / Revised: 20 March 2018 / Accepted: 28 March 2018 / Published: 4 April 2018
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Abstract
Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor
[...] Read more.
Land subsidence is one of the most important geological hazards in Beijing, China, and its scope and magnitude have been growing rapidly over the past few decades, mainly due to long-term groundwater withdrawal. Interferometric Synthetic Aperture Radar (InSAR) has been used to monitor the deformation in Beijing, but there is a lack of analysis of the long-term spatiotemporal evolution of land subsidence. This study focused on detecting and characterizing spatiotemporal changes in subsidence in the Beijing Plain by using Persistent Scatterer Interferometry (PSI) and geographic spatial analysis. Land subsidence during 2003–2015 was monitored by using ENVISAT ASAR (2003–2010), RADARSAT-2 (2011–2015) and TerraSAR-X (2010–2015) images, with results that are consistent with independent leveling measurements. The radar-based deformation velocity ranged from −136.9 to +15.2 mm/year during 2003–2010, and −149.4 to +8.9 mm/year during 2011–2015 relative to the reference point. The main subsidence areas include Chaoyang, Tongzhou, Shunyi and Changping districts, where seven subsidence bowls were observed between 2003 and 2015. Equal Fan Analysis Method (EFAM) shows that the maximum extensive direction was eastward, with a growing speed of 11.30 km2/year. Areas of differential subsidence were mostly located at the boundaries of the seven subsidence bowls, as indicated by the subsidence rate slope. Notably, the area of greatest subsidence was generally consistent with the patterns of groundwater decline in the Beijing Plain. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Integration of PSI, MAI, and Intensity-Based Sub-Pixel Offset Tracking Results for Landslide Monitoring with X-Band Corner Reflectors—Italian Alps (Corvara)
Remote Sens. 2018, 10(3), 409; https://doi.org/10.3390/rs10030409
Received: 17 January 2018 / Revised: 23 February 2018 / Accepted: 1 March 2018 / Published: 6 March 2018
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Abstract
This paper presents an analysis of the integration between interferometric and intensity-offset tracking-based SAR remote sensing for landslide hazard mitigation in the Italian Alps. Despite the advantages of Synthetic Aperture Radar Interferometry (InSAR) methods for quantifying landslide deformation, some limitations remain. The temporal
[...] Read more.
This paper presents an analysis of the integration between interferometric and intensity-offset tracking-based SAR remote sensing for landslide hazard mitigation in the Italian Alps. Despite the advantages of Synthetic Aperture Radar Interferometry (InSAR) methods for quantifying landslide deformation, some limitations remain. The temporal decorrelation, the 1-D Line Of Sight (LOS) observation restriction, the high velocity rate and the multi-directional movement properties make it difficult to monitor accurately complex landslides in areas covered by vegetation. Therefore, complementary and integrated approaches, such as offset tracking-based techniques, are needed to overcome these InSAR limitations for monitoring ground surface deformations. As sub-pixel offset tracking is highly sensitive to data spatial resolution, the latest generations of SAR sensors, such as TerraSAR-X and COSMO-SkyMed, open interesting perspective for a more accurate hazard assessment. In this paper, we consider high-resolution X-band data acquired by the COSMO-SkyMed (CSK) constellation for Permanent Scatterers Interferometry (PSI), Multi-Aperture Interferometry (MAI) and offset tracking processing. We analyze the offset tracking techniques considering area and feature-based matching algorithms to evaluate their applicability to CSK data by improving sub-pixel offset estimations. To this end, PSI and MAI are used for extracting LOS and azimuthal displacement components. Then, four well-known area-based and five feature-based matching algorithms (taken from computer vision) are applied to 16 X-band corner reflectors. Results show that offset estimation accuracy can be considerably improved up to less than 3% of the pixel size using the combination of the different feature-based detectors and descriptors. A sensitivity analysis of these techniques applied to CSK data to monitor complex landslides in the Italian Alps provides indications on advantages and disadvantages of each of them. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle SBAS Analysis of Induced Ground Surface Deformation from Wastewater Injection in East Central Oklahoma, USA
Remote Sens. 2018, 10(2), 283; https://doi.org/10.3390/rs10020283
Received: 20 December 2017 / Revised: 29 January 2018 / Accepted: 7 February 2018 / Published: 12 February 2018
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Abstract
The state of Oklahoma has experienced a dramatic increase in the amount of measurable seismic activities over the last decade. The needs of a petroleum-driven world have led to increased production utilizing various technologies to reach energy reserves locked in tight formations and
[...] Read more.
The state of Oklahoma has experienced a dramatic increase in the amount of measurable seismic activities over the last decade. The needs of a petroleum-driven world have led to increased production utilizing various technologies to reach energy reserves locked in tight formations and stimulate end-of-life wells, creating significant amounts of undesirable wastewater ultimately injected underground for disposal. Using Phased Array L-band Synthetic Aperture Radar (PALSAR) data, we performed a differential Synthetic Aperture Radar Interferometry (InSAR) technique referred to as the Small BAseline Subset (SBAS)-based analysis over east central Oklahoma to identify ground surface deformation with respect to the location of wastewater injection wells for the period of December 2006 to January 2011. Our results show broad spatial correlation between SBAS-derived deformation and the locations of injection wells. We also observed significant uplift over Cushing, Oklahoma, the largest above ground crude oil storage facility in the world, and a key hub of the Keystone Pipeline. This finding has significant implications for the oil and gas industry due to its close proximity to the zones of increased seismicity attributed to wastewater injection. Results southeast of Drumright, Oklahoma represent an excellent example of the potential of InSAR, identifying a fault bordered by an area of subduction to the west and uplift to the east. This differentiated movement along the fault may help explain the lack of any seismic activity in this area, despite the large number of wells and high volume of fluid injected. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Land Subsidence in Chiayi, Taiwan, from Compaction Well, Leveling and ALOS/PALSAR: Aquaculture-Induced Relative Sea Level Rise
Remote Sens. 2018, 10(1), 40; https://doi.org/10.3390/rs10010040
Received: 24 November 2017 / Revised: 22 December 2017 / Accepted: 22 December 2017 / Published: 26 December 2017
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Abstract
Chiayi County is located in the largest alluvial plain of Taiwan with extensive aquaculture and rice farming sustained by water extracted from groundwater wells. Chiayi is a typical aquaculture area affected by land subsidence, yet such lands worldwide combine to provide nearly 90%
[...] Read more.
Chiayi County is located in the largest alluvial plain of Taiwan with extensive aquaculture and rice farming sustained by water extracted from groundwater wells. Chiayi is a typical aquaculture area affected by land subsidence, yet such lands worldwide combine to provide nearly 90% of global aquaculture products, greatly reducing oceanic overfishing problems. This study uses precision leveling, multi-layer compaction monitoring well (MLCW) and spaceborne SAR interferometry (InSAR) to examine the cause and effect of land subsidence in Chiayi associated with groundwater extractions and changes. Heights at benchmarks in a leveling network are measured annually and soil compactions at 24–26 layers up to 300-m depths at 7 MLCWs are collected at one-month intervals. Over 2007–2011, 15 ALOS/PALSAR images are processed by the method of TCPInSAR to produce subsidence rates. All sensors show that land subsidence occur in most parts of Chiayi, with rates reaching 4.5 cm/year around its coast, a result of groundwater pumping from shallow to deep aquifers. MLCWs detect mm-accuracy seasonal soil compactions coinciding with groundwater level fluctuations and causing dynamic compactions. Compactions near Taiwan High Speed Rail may reduce the strength of the rail’s supporting columns to degrade its safety. The SAR images yield subsidence rates consistent with those from leveling and compaction wells after corrections for systematic errors by the leveling result. Subsidence in Chiayi’s coastal area leads to relative sea level rises at rates up to 15 times larger than the global eustatic sea level rising rate, a risk typical for world’s aquaculture-rich regions. At the fish pond-covered Budai Township, InSAR identifies subsidence spots not detected by leveling, providing crucial geo-information for a sustainable land management for aquaculture industry. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP)
Remote Sens. 2017, 9(12), 1291; https://doi.org/10.3390/rs9121291
Received: 27 September 2017 / Revised: 28 November 2017 / Accepted: 7 December 2017 / Published: 11 December 2017
Cited by 1 | PDF Full-text (7229 KB) | HTML Full-text | XML Full-text
Abstract
The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is
[...] Read more.
The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called “SBAS InSAR”. Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle The 2015–2016 Ground Displacements of the Shanghai Coastal Area Inferred from a Combined COSMO-SkyMed/Sentinel-1 DInSAR Analysis
Remote Sens. 2017, 9(11), 1194; https://doi.org/10.3390/rs9111194
Received: 21 September 2017 / Revised: 10 November 2017 / Accepted: 15 November 2017 / Published: 21 November 2017
Cited by 1 | PDF Full-text (47319 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this work, ground deformation of the Shanghai coastal area is inferred by using the multiple-satellite Differential Synthetic Aperture Radar interferometry (DInSAR) approach, also known as the minimum acceleration (MinA) combination algorithm. The MinA technique allows discrimination and time-evolution monitoring of the inherent
[...] Read more.
In this work, ground deformation of the Shanghai coastal area is inferred by using the multiple-satellite Differential Synthetic Aperture Radar interferometry (DInSAR) approach, also known as the minimum acceleration (MinA) combination algorithm. The MinA technique allows discrimination and time-evolution monitoring of the inherent two-dimensional components (i.e., with respect to east-west and up-down directions) of the ongoing deformation processes. It represents an effective post-processing tool that allows an easy combination of preliminarily-retrieved multiple-satellite Line-Of-Sight-projected displacement time-series, obtained by using one (or more) of the currently available multi-pass DInSAR toolboxes. Specifically, in our work, the well-known small baseline subset (SBAS) algorithm has been exploited to recover LOS deformation time-series from two sets of Synthetic Aperture Radar (SAR) data relevant to the coast of Shanghai, collected from 2014 to 2017 by the COSMO-SkyMed (CSK) and the Sentinel-1A (S1-A) sensors. The achieved results evidence that the Shanghai ocean-reclaimed areas were still subject to residual deformations in 2016, with maximum subsidence rates of about 30 mm/year. Moreover, the investigation has revealed that the detected deformations are predominantly vertical, whereas the east-west deformations are less significant. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Source Parameters of the 2016–2017 Central Italy Earthquake Sequence from the Sentinel-1, ALOS-2 and GPS Data
Remote Sens. 2017, 9(11), 1182; https://doi.org/10.3390/rs9111182
Received: 16 August 2017 / Revised: 11 November 2017 / Accepted: 15 November 2017 / Published: 17 November 2017
Cited by 1 | PDF Full-text (28428 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this study, joint inversions of Synthetic Aperture Radar (SAR) and Global Position System (GPS) measurements are used to investigate the source parameters of four Mw > 5 events of the 2016–2017 Central Italy earthquake sequence. The results show that the four events
[...] Read more.
In this study, joint inversions of Synthetic Aperture Radar (SAR) and Global Position System (GPS) measurements are used to investigate the source parameters of four Mw > 5 events of the 2016–2017 Central Italy earthquake sequence. The results show that the four events are all associated with a normal fault striking northwest–southeast and dipping southwest. The observations, in all cases, are consistent with slip on a rupture plane, with strike in the range of 157° to 164° and dip in the range of 39° to 44° that penetrates the uppermost crust to a depth of 0 to 8 km. The primary characteristics of these four events are that the 24 August 2016 Mw 6.2 Amatrice earthquake had pronounced heterogeneity of the slip distribution marked by two main slip patches, the 26 October 2016 Mw 6.1 Visso earthquake had a concentrated slip at 3–6 km, and the predominant slip of the 30 October 2016 Mw 6.6 Norcia earthquake occurred on the fault with a peak magnitude of 2.5 m at a depth of 0–6 km, suggesting that the rupture may have reached the surface, and the 18 January 2017 Mw 5.7 Campotosto earthquake had a large area of sliding at depth 3–9 km. The positive static stress changes on the fault planes of the latter three events demonstrate that the 24 August 2016 Amatrice earthquake may have triggered a cascading failure of earthquakes along the complex normal fault system in Central Italy. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Deriving 3-D Time-Series Ground Deformations Induced by Underground Fluid Flows with InSAR: Case Study of Sebei Gas Fields, China
Remote Sens. 2017, 9(11), 1129; https://doi.org/10.3390/rs9111129
Received: 15 August 2017 / Revised: 28 October 2017 / Accepted: 1 November 2017 / Published: 6 November 2017
PDF Full-text (89446 KB) | HTML Full-text | XML Full-text
Abstract
Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique has proven to be a powerful tool for the monitoring of time-series ground deformations along the line-of-sight (LOS) direction. However, the one-dimensional (1-D) measurements cannot provide comprehensive information for interpreting the related geo-hazards. Recently, a novel
[...] Read more.
Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique has proven to be a powerful tool for the monitoring of time-series ground deformations along the line-of-sight (LOS) direction. However, the one-dimensional (1-D) measurements cannot provide comprehensive information for interpreting the related geo-hazards. Recently, a novel method has been proposed to map the three-dimensional (3-D) deformation associated with underground fluid flows based on single-track InSAR LOS measurements and the deformation modeling associated with the Green’s function. In this study, the method is extended in temporal domain by exploiting the MT-InSAR measurements, and applied for the first time to investigate the 3-D time series deformation over Sebei gas field in Qinghai, Northwest China with 37 Sentinel-1 images acquired during October 2014–July 2017. The estimated 3-D time series deformations provide a more complete view of ongoing deformation processes as compared to the 1-D time series deformations or the 3-D deformation velocities, which is of great importance for assessing the possible geohazards. In addition, the extended method allows for the retrieval of time series of fluid volume changes due to the gas extraction in the Sebei field, which agrees well with those from the PetroChina Qinghai Oilfield Company Yearbooks (PQOCYs). This provides a new way to study the variations of subsurface fluids at unprecedented resolution. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle Effects of External Digital Elevation Model Inaccuracy on StaMPS-PS Processing: A Case Study in Shenzhen, China
Remote Sens. 2017, 9(11), 1115; https://doi.org/10.3390/rs9111115
Received: 30 July 2017 / Revised: 7 October 2017 / Accepted: 30 October 2017 / Published: 1 November 2017
PDF Full-text (81728 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
External Digital Elevation Models (DEMs) with different resolutions and accuracies cause different topographic residuals in differential interferograms of Multi-temporal InSAR (MTInSAR), especially for the phase-based StaMPS-PS. The PS selection and deformation parameter estimation of StaMPS-PS are closely related to the spatially uncorrected error,
[...] Read more.
External Digital Elevation Models (DEMs) with different resolutions and accuracies cause different topographic residuals in differential interferograms of Multi-temporal InSAR (MTInSAR), especially for the phase-based StaMPS-PS. The PS selection and deformation parameter estimation of StaMPS-PS are closely related to the spatially uncorrected error, which is directly affected by external DEMs. However, it is still far from clear how the high resolution and accurate external DEM affects the results of the StaMPS-PS (e.g., PS selection and deformation parameter calculation) on different platforms (X band TerraSAR, C band ENVISAT ASAR and L band ALOS/PALSAR1). In this study, abundant synthetic tests are performed to assess the influences of external DEMs on parameter estimations, such as the mean deformation rate and the deformation time-series. Real SAR images, covering Shenzhen city in China, are also selected to analyze the PS selection and distribution as well as to validate the results of synthetic tests. The results show that the PS points selected by the 5 m TanDEM-X DEM are 10.32%, 4.25% and 0.34% more than those selected by the 30 m SRTM DEM at X, C and L bands SAR platforms, respectively, when a multi-look geocoding operation is adopted for X band in the SRTM DEM case. We also find that the influences of external DEMs on the mean deformation rate are not significant and are inversely proportional to the wavelength of the satellite platforms. The standard deviations of the mean deformation rate difference for the X, C and L bands are 0.54, 0.30 and 0.10 mm/year, respectively. Similarly, the influences of external DEMs on the deformation time-series estimation for the three platforms are also slight, except for local artifacts whose root-mean-square error (RMSE) 6 mm. Based on these analyses, some implications and suggestions for external DEMs on StaMPS-PS processing are discussed and provided. 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; https://doi.org/10.3390/rs9101004
Received: 17 July 2017 / Revised: 22 September 2017 / Accepted: 23 September 2017 / Published: 28 September 2017
Cited by 1 | PDF Full-text (41037 KB) | HTML Full-text | XML Full-text
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 A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images
Remote Sens. 2017, 9(10), 1002; https://doi.org/10.3390/rs9101002
Received: 4 August 2017 / Revised: 12 September 2017 / Accepted: 21 September 2017 / Published: 28 September 2017
Cited by 3 | PDF Full-text (4666 KB) | HTML Full-text | XML Full-text
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 An Adaptive Offset Tracking Method with SAR Images for Landslide Displacement Monitoring
Remote Sens. 2017, 9(8), 830; https://doi.org/10.3390/rs9080830
Received: 15 July 2017 / Revised: 29 July 2017 / Accepted: 9 August 2017 / Published: 11 August 2017
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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
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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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