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Scaling-Up Deformation Monitoring and Analysis

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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) | Viewed by 73160

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Dr. Charalampos Kontoes

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National Observatory of Athens, Metaxa & Vasileos Pavlou Str., Athens, Greece
Interests: earth observation; big satellite data analysis; SAR interferometry; EO disaster management; GEO/Copernicus; data hubs
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Dr. Ioannis Papoutsis

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Institute of Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, GR-118 10 Athens, Greece
Interests: earth observation; synthetic aperture radar; SAR interferometry; persistent scatterer interferometry; machine learning and information extraction; disaster management
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Dr. Gregory Giuliani

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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
Special Issues, Collections and Topics in MDPI journals

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

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Keywords

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

Published Papers (8 papers)

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Research

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27 pages, 25315 KiB

Open AccessArticle

InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data

by Ioannis Papoutsis, Charalampos Kontoes, Stavroula Alatza, Alexis Apostolakis and Constantinos Loupasakis

Remote Sens. 2020, 12(19), 3207; https://doi.org/10.3390/rs12193207 - 01 Oct 2020

Cited by 25 | Viewed by 5123

Abstract

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community. Full article

(This article belongs to the Special Issue Scaling-Up Deformation Monitoring and Analysis)

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21 pages, 8511 KiB

Open AccessArticle

A Global Archive of Coseismic DInSAR Products Obtained Through Unsupervised Sentinel-1 Data Processing

by Fernando Monterroso, Manuela Bonano, Claudio De Luca, Riccardo Lanari, Michele Manunta, Mariarosaria Manzo, Giovanni Onorato, Ivana Zinno and Francesco Casu

Remote Sens. 2020, 12(19), 3189; https://doi.org/10.3390/rs12193189 - 29 Sep 2020

Cited by 12 | Viewed by 3895

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., 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)

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29 pages, 10396 KiB

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

by Riccardo Lanari, Manuela Bonano, Francesco Casu, Claudio De Luca, Michele Manunta, Mariarosaria Manzo, Giovanni Onorato and Ivana Zinno

Remote Sens. 2020, 12(18), 2961; https://doi.org/10.3390/rs12182961 - 11 Sep 2020

Cited by 44 | Viewed by 6279

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 (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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21 pages, 6921 KiB

Open AccessArticle

Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements Using Sentinel-1 Data

by Milan Lazecký, Emma Hatton, Pablo J. González, Ivana Hlaváčová, Eva Jiránková, František Dvořák, Zdeněk Šustr and Jan Martinovič

Remote Sens. 2020, 12(18), 2960; https://doi.org/10.3390/rs12182960 - 11 Sep 2020

Cited by 16 | Viewed by 3565

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 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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29 pages, 3955 KiB

Open AccessArticle

LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity

by Milan Lazecký, Karsten Spaans, Pablo J. González, Yasser Maghsoudi, Yu Morishita, Fabien Albino, John Elliott, Nicholas Greenall, Emma Hatton, Andrew Hooper, Daniel Juncu, Alistair McDougall, Richard J. Walters, C. Scott Watson, Jonathan R. Weiss and Tim J. Wright

Remote Sens. 2020, 12(15), 2430; https://doi.org/10.3390/rs12152430 - 29 Jul 2020

Cited by 121 | Viewed by 13208

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 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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18 pages, 5423 KiB

Open AccessArticle

Performance Analysis of Open Source Time Series InSAR Methods for Deformation Monitoring over a Broader Mining Region

by Kleanthis Karamvasis and Vassilia Karathanassi

Remote Sens. 2020, 12(9), 1380; https://doi.org/10.3390/rs12091380 - 27 Apr 2020

Cited by 14 | Viewed by 4466

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 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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29 pages, 6546 KiB

Open AccessEditor’s ChoiceArticle

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

by Yu Morishita, Milan Lazecky, Tim J. Wright, Jonathan R. Weiss, John R. Elliott and Andy Hooper

Remote Sens. 2020, 12(3), 424; https://doi.org/10.3390/rs12030424 - 28 Jan 2020

Cited by 182 | Viewed by 27547

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 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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20 pages, 5302 KiB

Open AccessReview

The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service

by Michele Crosetto, Lorenzo Solari, Marek Mróz, Joanna Balasis-Levinsen, Nicola Casagli, Michaela Frei, Anneleen Oyen, Dag Anders Moldestad, Luke Bateson, Luca Guerrieri, Valerio Comerci and Henrik Steen Andersen

Remote Sens. 2020, 12(12), 2043; https://doi.org/10.3390/rs12122043 - 25 Jun 2020

Cited by 96 | Viewed by 8000

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. 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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