Generation of Earth’s Surface Three-Dimensional (3-D) Displacement Time-Series by Multiple-Platform SAR Data

In this chapter, the recent advancements of differential synthetic aperture radar interferometry (DInSAR) technique are presented, with the focus on the DInSAR-based approaches leading to the generation of three-dimensional time-series of Earth’s surface deformation, based on the combination of multi-platform line-of-sight (LOS)-projected time-series of deformation. Use of pixel-offset (PO) measurements for the retrieval of North-South deformation components, which are difficult to be extracted from DInSAR data, only, is also discussed. A review of the principal techniques based on the exploitation of amplitude and phase signatures of sequences of SAR images will be first provided, by emphasizing the limitations and strength of each single approach. Then, the interest will be concentrated on the recently proposed multi-track InSAR combination algorithm, referred as minimum acceleration InSAR combination (MinA) approach. The algorithm assumes the availability of two (or more) sets of SAR images acquired from complementary tracks. SAR data are pre-processed through one of currently available multi-temporal DInSAR toolboxes, and the LOS-projected surface deformation time-series are computed. An under-determined system of linear equations is then solved, based on imposing that the 3-D displacement time-series have minimum acceleration (MA). The presented results demonstrate the validity of the MinA algorithm

Joint exploitation of space-borne and ground-based multitemporal InSAR measurements for volcano monitoring: The Stromboli volcano case study

Abstract We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas

Advanced SBAS-DInSAR technique for controlling large civil infrastructures: an application to the Genzano di Lucania dam

Monitoring surface deformation on dams is commonly carried out by in situ geodetic surveying, which is time consuming and characterized by some limitations in space coverage and frequency. More recently microwave satellite-based technologies, such as advanced-DInSAR (Differential Synthetic Aperture Radar Interferometry), have allowed the integration and improvement of the observation capabilities of ground-based methods thanks to their effectiveness in collecting displacement measurements on many non-destructive control points, corresponding to radar reflecting targets. The availability of such a large number of points of measurement, which are distributed along the whole structure and are characterized by millimetric accuracy on displacement rates, can be profitably adopted for the calibration of numerical models. These models are implemented to simulate the structural behaviour of a dam under conditions of stress thus improving the ability to maintain safety standards. In this work, after having analysed how advanced DInSAR can effectively enhance the results from traditional monitoring systems that provide comparable accuracy measurements on a limited number of points, an FEM model of the Genzano di Lucania earth dam is developed and calibrated. This work is concentrated on the advanced DInSAR technique referred to as Small BAseline Subset (SBAS) approach, benefiting from its capability to generate deformation time series at full spatial resolution and from multi-sensor SAR data, to measure the vertical consolidation displacement of the Genzano di Lucania earth dam

A GeoNode-based platform for an effective exploitation of advanced DInSAR measurements

This work presents the development of an efficient tool for managing, visualizing, analysing, and integrating with other data sources, the deformation time-series obtained by applying the advanced differential interferometric synthetic aperture radar (DInSAR) techniques. To implement such a tool we extend the functionalities of GeoNode, which is a web-based platform providing an open source framework based on the Open Geospatial Consortium (OGC) standards, that allows development of Geospatial Information Systems (GIS) and Spatial Data Infrastructures (SDI). In particular, our efforts have been dedicated to enable the GeoNode platform to effectively analyze and visualize the spatio/temporal characteristics of the DInSAR deformation time-series and their related products. Moreover, the implemented multi-thread based new functionalities allow us to efficiently upload and update large data volumes of the available DInSAR results into a dedicated geodatabase. The examples we present, based on Sentinel-1 DInSAR results relevant to Italy, demonstrate the effectiveness of the extended version of the GeoNode platform

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

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

Exploitation of large archives of ERS and ENVISAT C-band SAR data to characterize ground deformations

In the last few years, several advances have been made in the use of radar images to detect, map and monitor ground deformations. DInSAR (Differential Synthetic Aperture Radar Interferometry) and A-DInSAR/PSI (Advanced DInSAR/Persistent Scatterers Interferometry) technologies have been successfully applied in the study of deformation phenomena induced by, for example, active tectonics, volcanic activity, ground water exploitation, mining, and landslides, both at local and regional scales. In this paper, the existing European Space Agency (ESA) archives (acquired as part of the FP7-DORIS project), which were collected by the ERS-1/2 and ENVISAT satellites operating in the microwave C-band, were analyzed and exploited to understand the dynamics of landslide and subsidence phenomena. In particular, this paper presents the results obtained as part of the FP7-DORIS project to demonstrate that the full exploitation of very long deformation time series (more than 15 years) can play a key role in understanding the dynamics of natural and human-induced hazards. © 2013 by the authors

Long-term flood-hazard modeling for coastal areas using InSAR measurements and a hydrodynamic model: The case study of Lingang New City, Shanghai

In this paper, we study long-term coastal flood risk of Lingang New City, Shanghai, considering 100- and 1000-year coastal flood return periods, local seal-level rise projections, and long-term ground subsidence projections. TanDEM-X satellite data acquired in 2012 were used to generate a high-resolution topography map, and multi-sensor InSAR displacement time-series were used to obtain ground deformation rates between 2007 and 2017. Both data sets were then used to project ground deformation rates for the 2030s and 2050s. A 2-D flood inundation model (FloodMap-Inertial) was employed to predict coastal flood inundation for both scenarios. The results suggest that the sea-level rise, along with land subsidence, could result in minor but non-linear impacts on coastal inundation over time. The flood risk will primarily be determined by future exposure and vulnerability of population and property in the floodplain. Although the flood risk estimates show some uncertainties, particularly for long-term predictions, the methodology presented here could be applied to other coastal areas where sea level rise and land subsidence are evolving in the context of climate change and urbanization

An insight in cloud computing solutions for intensive processing of remote sensing data

The investigation of Earth's surface deformation phenomena provides critical insights into several processes of great interest for science and society, especially from the perspective of further understanding the Earth System and the impact of the human activities. Indeed, the study of ground deformation phenomena can be helpful for the comprehension of the geophysical dynamics dominating natural hazards such as earthquakes, volcanoes and landslide. In this context, the microwave space-borne Earth Observation (EO) techniques represent very powerful instruments for the ground deformation estimation. In particular, Small BAseline Subset (SBAS) is regarded as one of the key techniques, for its ability to investigate surface deformation affecting large areas of the Earth with a centimeter to millimeter accuracy in different scenarios (volcanoes, tectonics, landslides, anthropogenic induced land motions). The current Remote Sensing scenario is characterized by the availability of huge archives of radar data that are going to increase with the advent of Sentinel-1 satellites. The effective exploitation of this large amount of data requires both adequate computing resources as well as advanced algorithms able to properly exploit such facilities. In this work we concentrated on the use of the P-SBAS algorithm (a parallel version of SBAS) within HPC infrastructure, to finally investigate the effectiveness of such technologies for EO applications. In particular we demonstrated that the cloud computing solutions represent a valid alternative for scientific application and a promising research scenario, indeed, from all the experiments that we have conducted and from the results obtained performing Parallel Small Baseline Subset (P-SBAS) processing, the cloud technologies and features result to be absolutely competitive in terms of performance with in-house HPC cluster solution

Monitoring ground movement at Volcán de Colima, Mexico, using Sentinel-1 data and SqueeSAR®

Volcán de Colima is a highly active stratovolcano in western Mexico which presents a significant hazard to over 300,000 people who live within ca 40 km of the volcano. Due to its persistent activity, the volcano is actively monitored and researched, and understanding the patterns of behaviour is vital to accurate hazard assessment. Sentinel-1 SAR images from ascending and descending orbits allow 1D and 2D ground motions to be retrieved using multi-interferogram techniques. SqueeSAR®’s unique processing allows a better characterisation of subtle ground movements in remote, rural mountainous areas compared to many other multi-interferogram techniques. A dataset of 147 SAR scenes (2017-2019) has been processed to show patterns of lava subsidence (<150 mm of downward vertical deformation over 2 years), as well as volcano deflation and apparent westward lateral movement. These data indicate that viscous andesitic lava flows may remain mobile for years following eruption and emplacement, and that the entire volcanic edifice is subsiding. Despite the apparent quiescence, volcanic edifices can remain highly dynamic after the termination of explosive or effusive activity. We interpret that the western flank of Volcán de Colima may become steeper with time and may be of long-term concern for hazard assessment activities. Thematic collection: This article is part of the Remote sensing for site investigations on Earth and other planets collection available at: https://www.lyellcollection.org/topic/collections/remote-sensing-for-site-investigations-on-earth-and-other-planet