Special Issue "Scaling-Up Deformation Monitoring and Analysis"

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 (31 July 2020).

Special Issue Editors

Dr. Charalampos Kontoes
Website
Guest Editor
Institute for Astronomy & Astrophysics, Space Applications and Remote Sensing National Observatory of Athens, Metaxa & Vas. Pavlou. 11523, Athens, Greece
Interests: mapping; earth observation; satellite image analysis; geoinformation; remote sensing, environmental impact assessment; geographic information system; spatial analysis; classification; geomatics
Dr. Ioannis Papoutsis

Guest Editor
National Observatory of Athens, Metaxa & Vasileos Pavlou Str, Athens, Greece
Interests: SAR interferometry; geohazards monitoring; big EO data processing; machine learning
Dr. Gregory Giuliani
Website SciProfiles
Guest Editor
Institute for Environmental Sciences & UNEP/GRID-Geneva, University of Geneva, 66 Boulevard Carl-Vogt, CH – 1205 Geneva, Switzerland
Interests: earth observations; data cube; sustainable development; GEO/GEOSS; environmental sciences
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Special Issue Information

Dear Colleagues,

Remote sensing based on synthetic aperture radar and/or multispectral data for mapping ground deformation has nearly become a commodity in the last few years. Conventional satellite interferometry, multiple aperture interferometry, offset tracking, persistent scatterer interferometry, small baseline subset, co-registration, and correlation of optical imagery, to name a few, have grown to become mature techniques for ground deformation assessment. The deformation signals studied may vary; geophysical phenomena, such as large earthquakes, volcanic activity, tectonic creep, and landslides, for example, cause clear displacement patterns that can be easily identified from space and analyzed further. The footprint of human activity has been also studied, including urban subsidence, groundwater and minerals extraction, construction activity, etc. The applications of these techniques also range in scale and impact from the single facility asset to the global level.

Nowadays, the big challenge is to shift the research focus from studying deformation due to single events and at the local level to systematic, continuous, and large-scale monitoring and analysis of deformations. The scaling-up of deformation monitoring and analysis is not trivial. There are two opportunities that lay ahead in this direction. The first one is the availability of big multi-modal satellite data, considering the assets that are currently on the table: SAR and optical data, diversity in imaging modes, variety in spectral and spatial resolution and revisit times, different carrier frequencies used in radar imaging systems, different deformation mapping techniques, s/w solutions, etc. Most importantly, with the advent of the Copernicus Programme, these large volumes of observations have become available on a free and open basis for studying the dynamically changing surface of the Earth. In parallel, there are now featured IT technologies, such as machine learning/deep learning models, data mining, data fusion, data cube for analytics, and feature extraction techniques on top of high performance and cloud computing environments (e.g., DIAS, the Geohazards Exploitation Platform, etc.), which have started to disrupt the remote sensing community, through efficient big satellite data analysis.

This Special Issue focuses on the implementation of novel techniques, as mentioned above, with high potential for mapping, monitoring, and analyzing deformations on a large scale, on a timely basis, and with high precision in the measured deformation patterns. There are no restrictions on the driver of the deformation, the methodology for the data processing, and/or the data type (radar or optical). The novelty should lay in the scale of the application and the potential to unveil new information about the observed deformations through the analysis of big satellite data.

Dr. Charalampos Kontoes
Dr. Ioannis Papoutsis
Dr. Gregory Giuliani
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 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

  • Deformation monitoring
  • Deformations analysis
  • Big satellite data
  • Scaling-up
  • Machine learning
  • Deep learning
  • Data cube
  • Data analytics
  • Data fusion

Published Papers (7 papers)

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Research

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Open AccessArticle
A Global Archive of Coseismic DInSAR Products Obtained Through Unsupervised Sentinel-1 Data Processing
Remote Sens. 2020, 12(19), 3189; https://doi.org/10.3390/rs12193189 (registering DOI) - 29 Sep 2020
Abstract
We present an automatic and unsupervised tool for the systematic generation of Sentinel-1 (S1) differential synthetic aperture radar interferometry (DInSAR) coseismic products. In particular, the tool first retrieves the location, depth, and magnitude of every seismic event from interoperable online earthquake catalogs (e.g., [...] Read more.
We present an automatic and unsupervised tool for the systematic generation of Sentinel-1 (S1) differential synthetic aperture radar interferometry (DInSAR) coseismic products. In particular, the tool first retrieves the location, depth, and magnitude of every seismic event from interoperable online earthquake catalogs (e.g., the United States Geological Survey (USGS) and the Italian National Institute of Geophysics and Volcanology (INGV) and then, for significant (with respect to a set of selected thresholds) earthquakes, it automatically triggers the downloading of S1 data and their interferometric processing over the area affected by the earthquake. The automatic system we developed has also been implemented within a Cloud-Computing (CC) environment, specifically the Amazon Web Services, with the aim of creating a global database of DInSAR S1 coseismic products, which consist of displacement maps and the associated wrapped interferograms and spatial coherences. This information will progressively be made freely available through the European Plate Observing System (EPOS) Research Infrastructure, thus providing the scientific community with a large catalog of DInSAR data that can be helpful for investigating the dynamics of surface deformation in the seismic zones around the Earth. The developed tool can also support national and local authorities during seismic crises by quickly providing information on the surface deformation induced by earthquakes. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
Open AccessArticle
Automatic Generation of Sentinel-1 Continental Scale DInSAR Deformation Time Series through an Extended P-SBAS Processing Pipeline in a Cloud Computing Environment
Remote Sens. 2020, 12(18), 2961; https://doi.org/10.3390/rs12182961 - 11 Sep 2020
Abstract
We present in this work an advanced processing pipeline for continental scale differential synthetic aperture radar (DInSAR) deformation time series generation, which is based on the parallel small baseline subset (P-SBAS) approach and on the joint exploitation of Sentinel-1 (S-1) interferometric wide swath [...] Read more.
We present in this work an advanced processing pipeline for continental scale differential synthetic aperture radar (DInSAR) deformation time series generation, which is based on the parallel small baseline subset (P-SBAS) approach and on the joint exploitation of Sentinel-1 (S-1) interferometric wide swath (IWS) SAR data, continuous global navigation satellite system (GNSS) position time-series, and cloud computing (CC) resources. We first briefly describe the basic rationale of the adopted P-SBAS processing approach, tailored to deal with S-1 IWS SAR data and to be implemented in a CC environment, highlighting the innovative solutions that have been introduced in the processing chain we present. They mainly consist in a series of procedures that properly exploit the available GNSS time series with the aim of identifying and filtering out possible residual atmospheric artifacts that may affect the DInSAR measurements. Moreover, significant efforts have been carried out to improve the P-SBAS processing pipeline automation and robustness, which represent crucial issues for interferometric continental scale analysis. Then, a massive experimental analysis is presented. In this case, we exploit: (i) the whole archive of S-1 IWS SAR images acquired over a large portion of Europe, from descending orbits, (ii) the continuous GNSS position time series provided by the Nevada Geodetic Laboratory at the University of Nevada, Reno, USA (UNR-NGL) available for the investigated area, and (iii) the ONDA platform, one of the Copernicus Data and Information Access Services (DIAS). The achieved results demonstrate the capability of the proposed solution to successfully retrieve the DInSAR time series relevant to such a huge area, opening new scenarios for the analysis and interpretation of these ground deformation measurements. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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Open AccessArticle
Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements Using Sentinel-1 Data
Remote Sens. 2020, 12(18), 2960; https://doi.org/10.3390/rs12182960 - 11 Sep 2020
Abstract
The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive [...] Read more.
The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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Open AccessArticle
LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity
Remote Sens. 2020, 12(15), 2430; https://doi.org/10.3390/rs12152430 - 29 Jul 2020
Cited by 3
Abstract
Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution [...] Read more.
Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR), an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 coordinate system). The products are continuously updated at a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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Open AccessArticle
Performance Analysis of Open Source Time Series InSAR Methods for Deformation Monitoring over a Broader Mining Region
Remote Sens. 2020, 12(9), 1380; https://doi.org/10.3390/rs12091380 - 27 Apr 2020
Abstract
Time Series Interferometric Synthetic Aperture Radar (TSInSAR) methods have been widely and successfully applied for spatiotemporal ground deformation monitoring. The main groups of methodological approaches are often referred to as Persistent Scatterer (PS), Small Baseline (SB), and hybrid approaches that incorporate PS and [...] Read more.
Time Series Interferometric Synthetic Aperture Radar (TSInSAR) methods have been widely and successfully applied for spatiotemporal ground deformation monitoring. The main groups of methodological approaches are often referred to as Persistent Scatterer (PS), Small Baseline (SB), and hybrid approaches that incorporate PS and SB concepts. While TSInSAR techniques have long been able to provide accurate deformation rates for various applications, their corresponding performance in complex environments such as mining areas has to be investigated. This study focuses on comparing the performance of three open source TSInSAR toolboxes (Stamps, Giant, Mintpy) over an extended region that includes an active opencast coal mine. We present the deformation results of each TSInSAR method on a Sentinel-1 dataset of 125 acquisitions spanning around 2.5 years over the Ptolemaida-Florina coal mine site that is characterized by several environmental and surface deformation conditions. First, a cross-comparison analysis is presented over different land cover classes. The study shows that all TSInSAR methods are capable for generating similar ground deformation results when the area has stable ground scattering conditions and the dataset sufficient temporal sampling. The most controversial results between TSInSAR approaches were found in land cover classes that include medium to high vegetation. An external comparative analysis between the different results from TSInSAR methods and leveling measurements is also performed. Stamps approach presented the best agreement with the in-situ deformation rates. The Giant approach yielded the best cumulative deformation results due to our a priori knowledge of temporal behavior of deformation in the vicinity of the leveling locations. Finally, we discuss the main pros and cons of each TSInSAR approach and we highlight the importance of comparison analysis that can provide insights and can lead to better interpretation of the results. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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Open AccessEditor’s ChoiceArticle
LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor
Remote Sens. 2020, 12(3), 424; https://doi.org/10.3390/rs12030424 - 28 Jan 2020
Cited by 12
Abstract
For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large [...] Read more.
For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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Review

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Open AccessReview
The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service
Remote Sens. 2020, 12(12), 2043; https://doi.org/10.3390/rs12122043 - 25 Jun 2020
Abstract
This study is focused on wide-area deformation monitoring initiatives based on the differential interferometric SAR technique (DInSAR). In particular, it addresses the use of advanced DInSAR (A-DInSAR) techniques, which are based on large sets of synthetic aperture radar (SAR) and Copernicus Sentinel-1 images. [...] Read more.
This study is focused on wide-area deformation monitoring initiatives based on the differential interferometric SAR technique (DInSAR). In particular, it addresses the use of advanced DInSAR (A-DInSAR) techniques, which are based on large sets of synthetic aperture radar (SAR) and Copernicus Sentinel-1 images. Such techniques have undergone a dramatic development in the last twenty years: they are now capable to process big sets of SAR images and can be exploited to realize a wide-area A-DInSAR monitoring. The study describes several initiatives to establish wide-area ground motion services (GMS), both at county- and region-level. In the second part of the study, some of the key technical aspects related to wide-area A-DInSAR monitoring are discussed. Finally, the last part of the study is devoted to the European ground motion service (EGMS), which is part of the Copernicus land monitoring service. It represents the most important wide-area A-DInSAR deformation monitoring system ever developed. The study describes its main characteristics and its main products. The end of the production of the first EGMS baseline product is foreseen for the last quarter of 2021. Full article
(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)
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