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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: closed (30 June 2018)

Special Issue Editors

Guest Editor
Dr. Zhong Lu

Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275-0395, USA
Website | E-Mail
Phone: 214-768-0101
Interests: SAR; InSAR; time-series InSAR; geophysical modeling; volcanoes; landslides; 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: synthetic aperture radar (SAR); interferometric SAR (InSAR); time series; precision agriculture; GNSS
Guest Editor
Prof. Roberto Tomás

Department of Civil Engineering, University of Alicante, Campus de San Vicente del Raspeig s/n, 03080 Alicante, Spain
Website | E-Mail
Interests: landslides; land subsidence; geohazards; infrastructures; remote sensing; EO techniques

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 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 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 (21 papers)

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Research

Open AccessArticle
Monitoring the Vulnerability of the Dam and Dikes in Germano Iron Mining Area after the Collapse of the Tailings Dam of Fundão (Mariana-MG, Brazil) Using DInSAR Techniques with TerraSAR-X Data
Remote Sens. 2018, 10(10), 1507; https://doi.org/10.3390/rs10101507
Received: 23 August 2018 / Revised: 13 September 2018 / Accepted: 15 September 2018 / Published: 20 September 2018
Cited by 1 | PDF Full-text (28071 KB) | HTML Full-text | XML Full-text
Abstract
The Fundão tailings dam in the Germano iron mining complex (Mariana, Brazil) collapsed on the afternoon of 5 November 2015, and around 32.6 million cubic meters of mining waste spilled from the dam, causing polluion with mining waste along a trajectory of 668 [...] Read more.
The Fundão tailings dam in the Germano iron mining complex (Mariana, Brazil) collapsed on the afternoon of 5 November 2015, and around 32.6 million cubic meters of mining waste spilled from the dam, causing polluion with mining waste along a trajectory of 668 km, extending to the Atlantic Ocean. The Sela & Tulipa and Selinha dikes, and the main Germano tailings dam, were directly or indirectly affected by the accident. This work presents an investigation using Advanced-Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques for risk assessment in these critical structures during 18 months after the catastrophic event. The approach was based on the integration of SBAS (Small Baseline Subset) and PSI (Persistent Scatterer Interferometry) techniques, aiming at detecting linear and nonlinear ground displacements in these mining structures. It used a set of 48 TerraSAR-X images acquired on ascending mode from 11 November 2015 to 15 May 2017. The results provided by the A-DInSAR analysis indicated an overall stability in the dikes and in the main wall of Germano tailings dam, which is in agreement with in situ topographic monitoring. In addition, it was possible to detect areas within the reservoir showing accumulated values of up to −125 mm of subsidence, probably caused by settlements of the waste dry material due to the interruption of the mining waste deposition, and values up to −80 mm on auxiliary dikes, probably caused by continuous traffic of heavy equipment. The spatiotemporal information of surface displacement of this large mining structure can be used for future operational planning and risk control. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle
Source Model and Stress Disturbance of the 2017 Jiuzhaigou Mw 6.5 Earthquake Constrained by InSAR and GPS Measurements
Remote Sens. 2018, 10(9), 1400; https://doi.org/10.3390/rs10091400
Received: 22 July 2018 / Revised: 27 August 2018 / Accepted: 30 August 2018 / Published: 3 September 2018
PDF Full-text (8058 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Seismogenic fault geometry, especially for a blind fault, is usually difficult to derive, based only on the distribution of aftershocks and interference fringes of Interferometric Synthetic Aperture Radar (InSAR). To better constrain the fault geometry of the 2017 Jiuzhaigou Mw 6.5 earthquake, we [...] Read more.
Seismogenic fault geometry, especially for a blind fault, is usually difficult to derive, based only on the distribution of aftershocks and interference fringes of Interferometric Synthetic Aperture Radar (InSAR). To better constrain the fault geometry of the 2017 Jiuzhaigou Mw 6.5 earthquake, we first carried out a nonlinear inversion for a single fault source using multi-peak particle swarm optimization (MPSO), Monte Carlo (MC), and Markov Chain Monte Carlo (MCMC) algorithms, respectively, with constraints of InSAR data in multiple SAR viewing geometries. The fault geometry models retrieved with different methods were highly consistent and mutually verifiable, showing that a blind faulting with a strike of ~154° and a dip angle of ~77° was responsible for the Jiuzhaigou earthquake. Based on the optimal fault geometry model, the fault slip distribution jointly inverted from the InSAR and Global Positioning System (GPS) data by the steepest descent method (SDM) and the MC method showed that the slip was mainly concentrated at the depth of 1–15 km, and only one slip center appeared at the depth of 5–9 km with a maximum slip of about 1.06 m, some different from previous studies. Taking the shear modulus of μ = 32 GPa, the seismic moment derived from the distributed slip model was about 7.85 × 1018 Nm, equivalent to Mw 6.54, which was slightly larger than that from the focal mechanism solutions. The fault spatial geometry and slip distribution could be further validated with the spatial patterns of the immediate aftershocks. Most of the off-fault aftershocks with the magnitude > M2 within one year after the mainshock occurred in the stress positive stress change area, which coincided with the stress triggering theory. The static Coulomb stress, triggered by the mainshock, significantly increased at the Tazang fault (northwest to the epicenter), and at the hidden North Huya fault, and partial segments of the Minjiang fault (west of the epicenter). Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle
Using Dual-Polarization Interferograms to Correct Atmospheric Effects for InSAR Topographic Mapping
Remote Sens. 2018, 10(8), 1310; https://doi.org/10.3390/rs10081310
Received: 28 June 2018 / Revised: 1 August 2018 / Accepted: 16 August 2018 / Published: 20 August 2018
PDF Full-text (11588 KB) | HTML Full-text | XML Full-text
Abstract
Atmospheric effect represents one of the major error sources for interferometric synthetic aperture radar (InSAR), particularly for the repeat-pass InSAR data. In order to further improve the practicability of InSAR technology, it is essential to study how to estimate and eliminate the undesired [...] Read more.
Atmospheric effect represents one of the major error sources for interferometric synthetic aperture radar (InSAR), particularly for the repeat-pass InSAR data. In order to further improve the practicability of InSAR technology, it is essential to study how to estimate and eliminate the undesired impact of atmospheric effects. In this paper, we propose the multi-resolution weighted correlation analysis (MRWCA) method between the dual-polarization InSAR data to estimate and correct atmospheric effects for InSAR topographic mapping. The study is based on the a priori knowledge that atmospheric effects is independent of the polarization. To find the identical atmospheric phase (ATP) signals of interferograms in different polarizations, we need to remove the other same or similar phase components. Using two different topographic data, differential interferometry was firstly performed so that the obtained differential interferograms (D-Infs) have different topographic error phases. A polynomial fitting method is then used to remove the orbit error phases. Thus, the ATP signals are the only identical components in the final obtained D-Infs. By using a forward wavelet transform, we break down the obtained D-Infs into building blocks based on their frequency properties. We then applied weighted correlation analysis to estimate the wavelet coefficients attributed to the atmospheric effects. Thus, the ATP signals can be obtained by the refined wavelet coefficients during inverse wavelet transform (IWT). Lastly, we tested the proposed method by the L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR dual-polarization SAR data pairs covering the San Francisco (USA) and Moron (Mongolia) regions. By using Ice, Cloud, and land Elevation Satellite (ICESat) data as the reference data, we evaluated the vertical accuracy of the InSAR digital elevation models (DEMs) with and without atmospheric effects correction, which shows that, for the San Francisco test site, the corrected interferogram could provide a DEM with a root-mean-square error (RMSE) of 7.79 m, which is an improvement of 40.5% with respect to the DEM without atmospheric effects correction. For the Moron test site, the corrected interferogram could provide a DEM with an RMSE of 10.74 m, which is an improvement of 30.2% with respect to the DEM without atmospheric effects correction. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle
Resolving Surface Displacements in Shenzhen of China from Time Series InSAR
Remote Sens. 2018, 10(7), 1162; https://doi.org/10.3390/rs10071162
Received: 6 June 2018 / Revised: 15 July 2018 / Accepted: 22 July 2018 / Published: 23 July 2018
Cited by 1 | PDF Full-text (84876 KB) | HTML Full-text | XML Full-text
Abstract
Over the past few decades, the coastal city of Shenzhen has been transformed from a small fishing village to a mega city as China’s first Special Economic Zone. The rapid economic development was matched by a sharp increase in the demand for usable [...] Read more.
Over the past few decades, the coastal city of Shenzhen has been transformed from a small fishing village to a mega city as China’s first Special Economic Zone. The rapid economic development was matched by a sharp increase in the demand for usable land and coastal reclamation has been undertaken to create new land from the sea. However, it has been reported that subsidence occurred in land reclamation area and around subway tunnel area. Subsidence and the additional threat of coastal inundation from sea-level rise highlight the necessity of displacement monitoring in Shenzhen. The time Series InSAR technique is capable of detecting sub-centimeter displacement of the Earth’s surface over large areas. This study uses Envisat, COSMO-SkyMed, and Sentinel-1 datasets to determine the surface movements in Shenzhen from 2004 to 2010 and from 2013 to 2017. Subsidence observed can be attributable to both land reclamation and subway construction. Seasonal displacements are likely to be associated with precipitation. The influence of ocean tidal level changes on seasonal displacement is not strongly evident from the results and requires further investigations. In general, InSAR has proven its ability to provide accurate measurements of ground stability for the city of Shenzhen. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessFeature PaperArticle
Subsidence Evolution of the Firenze–Prato–Pistoia Plain (Central Italy) Combining PSI and GNSS Data
Remote Sens. 2018, 10(7), 1146; https://doi.org/10.3390/rs10071146
Received: 1 June 2018 / Revised: 10 July 2018 / Accepted: 18 July 2018 / Published: 20 July 2018
Cited by 8 | PDF Full-text (8371 KB) | HTML Full-text | XML Full-text
Abstract
Subsidence phenomena, as well as landslides and floods, are one of the main geohazards affecting the Tuscany region (central Italy). The monitoring of related ground deformations plays a key role in their management to avoid problems for buildings and infrastructure. In this scenario, [...] Read more.
Subsidence phenomena, as well as landslides and floods, are one of the main geohazards affecting the Tuscany region (central Italy). The monitoring of related ground deformations plays a key role in their management to avoid problems for buildings and infrastructure. In this scenario, Earth observation offers a better solution in terms of costs and benefits than traditional techniques (e.g., GNSS (Global Navigation Satellite System) or levelling networks), especially for wide area applications. In this work, the subsidence-related ground motions in the Firenze–Prato–Pistoia plain were back-investigated to track the evolution of displacement from 2003 to 2017 by means of multi-interferometric analysis of ENVISAT and Sentinel-1 imagery combined with GNSS data. The resulting vertical deformation velocities are aligned to the European Terrestrial Reference System 89 (ETRS89) datum and can be considered real velocity of displacement. The vertical ground deformation maps derived by ENVISAT and Sentinel-1 data, corrected with the GNSS, show how the area affected by subsidence for the period 2003–2010 and the period 2014–2017 evolved. The differences between the two datasets in terms of the extension and velocity values were analysed and then associated with the geological setting of the basin and external factors, e.g., new greenhouses and nurseries. This analysis allowed for reconstructing the evolution of the subsidence for the area of interest showing an increment of ground deformation in the historic centre of Pistoia Town, a decrement of subsidence in the nursery area between Pistoia and Prato cities, and changes in the industrial sector close to Prato. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessFeature PaperArticle
Landslide Identification and Monitoring along the Jinsha River Catchment (Wudongde Reservoir Area), China, Using the InSAR Method
Remote Sens. 2018, 10(7), 993; https://doi.org/10.3390/rs10070993
Received: 30 April 2018 / Revised: 17 June 2018 / Accepted: 20 June 2018 / Published: 22 June 2018
Cited by 3 | PDF Full-text (23828 KB) | HTML Full-text | XML Full-text
Abstract
Landslide identification and monitoring are two significant research aspects for landslide analysis. In addition, landslide mode deduction is key for the prevention of landslide hazards. Surface deformation results with different scales can serve for different landslide analysis. L-band synthetic aperture radar (SAR) data [...] Read more.
Landslide identification and monitoring are two significant research aspects for landslide analysis. In addition, landslide mode deduction is key for the prevention of landslide hazards. Surface deformation results with different scales can serve for different landslide analysis. L-band synthetic aperture radar (SAR) data calculated with Interferometric Point Target Analysis (IPTA) are first employed to detect potential landslides at the catchment-scale Wudongde reservoir area. Twenty-two active landslides are identified and mapped over more than 2500 square kilometers. Then, for one typical landslide, Jinpingzi landslide, its spatiotemporal deformation characteristics are analyzed with the small baseline subsets (SBAS) interferometric synthetic aperture radar (InSAR) technique. High-precision surface deformation results are obtained by comparing with in-situ georobot measurements. The spatial deformation pattern reveals the different stabilities among five different sections of Jinpingzi landslide. InSAR results for Section II of Jinpingzi landslide show that this active landslide is controlled by two boundaries and geological structure, and its different landslide deformation magnitudes at different sections on the surface companying with borehole deformation reveals the pull-type landslide mode. Correlation between time series landslide motion and monthly precipitation, soil moisture inverted from SAR intensity images and water level fluctuations suggests that heavy rainfall is the main trigger factor, and the maximum deformation of the landslide was highly consistent with the peak precipitation with a time lag of about 1 to 2 months, which gives us important guidelines to mitigate and prevent this kind of hazard. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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Open AccessArticle
Ground-Based Differential Interferometric Radar Monitoring of Unstable Mountain Blocks in a Coastal Environment
Remote Sens. 2018, 10(6), 914; https://doi.org/10.3390/rs10060914
Received: 27 April 2018 / Revised: 1 June 2018 / Accepted: 5 June 2018 / Published: 9 June 2018
Cited by 1 | PDF Full-text (11223 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we present the results of eight years of continuous monitoring with a ground-based, interferometric, real-aperture radar of two unstable mountain blocks at Tafjord on the western coast of Norway. A real-time, interferometric, ground-based radar has the capability to provide high [...] Read more.
In this paper, we present the results of eight years of continuous monitoring with a ground-based, interferometric, real-aperture radar of two unstable mountain blocks at Tafjord on the western coast of Norway. A real-time, interferometric, ground-based radar has the capability to provide high accuracy range measurements by using the phase of the transmitted signal, thus achieving sub-millimeter accuracy when a sufficient signal-to-noise level is present. The main challenge with long term monitoring is the variations in radio refractivity caused by changes in the atmosphere. The range variations caused by refractive changes in the atmosphere are corrected using meteorological data. We use triangular corner reflectors as references to improve the signal-to-clutter ratio and improve the accuracy of the measurements. We have also shown that by using differential interferometry, a significant part of the variation caused by radio refractivity variations is removed. The overall reduction in path length variation when using differential interferometry varies from 27 to 164 times depending on the radar-to-reflector path length. The measurements reveal cyclic seasonal variations, which are coherent with air temperature. The results show that radar measurements are as accurate as data from in situ instruments like extensometers and crack meters, making it possible to monitor inaccessible areas. The total measured displacement is between 1.2 mm and 4.7 mm for the two monitored mountain blocks. Full article
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
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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
Cited by 2 | PDF Full-text (4134 KB) | HTML Full-text | XML Full-text
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
Cited by 4 | 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
Cited by 6 | PDF Full-text (62853 KB) | HTML Full-text | XML Full-text
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
Cited by 4 | PDF Full-text (11955 KB) | HTML Full-text | XML Full-text
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
Cited by 3 | PDF Full-text (13758 KB) | HTML Full-text | XML Full-text
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
Cited by 6 | PDF Full-text (24264 KB) | HTML Full-text | XML Full-text
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
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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 7 | 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 9 | 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
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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
Cited by 1 | 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 5 | 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 17 | 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
Cited by 7 | 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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