With the increase of high spatial and temporal resolution SAR data availability, novel applications and information extraction techniques become possible. Among these, the extraction of micro-motion information has the potential to unlock a range of applications, such as infrastructure monitoring, maritime surveillance and natural disaster damage assessment. However, sensors, acquisition modes and products have not been designed with in mind the optimization of micro-motion extraction and its applications, therefore, careful considerations need to take place when selecting the most suitable data and designing processing algorithms. In this paper practical and processing considerations when dealing micro-motion extraction from high-resolution SAR sensors are discussed and supported with experimental results obtained from Capella, Umbra and TerraSAR-X data.

Surface Topography and Vegetation (STV) is a NASA targeted observable for maturation into an observing system architecture. STV will acquire high-resolution, global height measurements, including bare surface land topography, ice topography, vegetation structure, and shallow water bathymetry. These measurements serve a broad range of science and applications objectives that span solid earth, cryosphere, biosphere and hydrosphere disciplines. A common set of measurements could meet many of the community needs. STV objectives would be best met by new observing strategies that employ flexible multi-source and sensor measurements from a variety of orbital and sub-orbital assets. Science and application objectives would be best met by new, 3-dimensional observations from lidar, radar, and stereoimaging. Simulations, experiments, data analysis and technology development in interferometric SAR, lidar and stereo photogrammetry approaches, platform options and system architectures will all mature STV toward an observing system.

Single-pass SAR interferometry (InSAR) has demonstrated a great potential for the monitoring of ice and snow melt dynamics. In particular, digital elevation models (DEM) derived from the TanDEM-X bistatic SAR mission are widely used for measuring elevation changes over glaciers through time-tagged DEM differencing. A critical aspect of this approach is represented by the mutual calibration of the input DEMs, which are normally affected by residual offsets and tilts, caused by uncertainties on the baseline estimation. Moreover, a further crucial aspect which needs to be addressed is the penetration of radar waves into the snow pack, which is closely linked to both the properties of snow and the radar parameters, such as frequency and acquisition geometry. This in turn jeopardizes the retrieval of the topographic height of the surface and adds a significant amount of uncertainty when performing DEM differencing over snow-covered areas. In this paper, we present an overview of the activities which are currently being carried out at DLR, together with partner institutions and companies, aimed at providing more reliable estimations of snow depth and glaciers topographic height changes using TanDEM-X bistatic InSAR data. We present a novel technique for performing an automatic selection of reliable calibration points, based on the use of natural targets, together with the mutual calibration procedure. Moreover, we rely on a data-driven machine learning approach for the estimation and compensation of the surface penetration bias. Preliminary results are extremely promising, also in view of future bistatic SAR missions, such as the ESA Harmony Earth Explorer mission.

In western countries, thousands of infrastructure assets have exceeded their intended design life and need continuous monitoring. Space-borne Interferometric Synthetic Aperture Radars (InSAR) are capable of wide-area monitoring, providing inexpensive and high-density measurements of buildings and infrastructure deformations with a millimetre-scale accuracy. Infrastructure catalogues can be used to associate the InSAR-based measurements with the corresponding structures. However, when large infrastructure networks are analysed, the manual extraction of the relevant InSAR-derived displacements is not feasible. In this paper, a new methodology based on the automated integration of InSAR-based displacements and infrastructure databases to warn potentially anomalous deformations over large infrastructure networks is presented. The proposed methodology is applied to the Los Angeles highway and freeway network, using Sentinel data from 2016 to 2019. Results can have a direct impact on transportation network management.

The United States National Aeronautics and Space Administration (NASA) has initiated a five-year study of a Surface Deformation and Change Observing System Architecture. The goal of the study is to define an observing system that would meet the recommendations of the 2017 US National Academy of Sciences, Engineering, and Medicine Decadal Survey for developing an affordable synthetic aperture radar-based system or systems that can address fundamental scientific questions about the nature of hazards, disasters, landscape change, and serve applications communities as well. The study is to consider the existing international constellation of SAR systems, both civil and commercial, as well as new technologies that could be employed to address scientific and applications objectives and to improve affordability. The study will be conducted in four phases: 1) expanding the architectural trade space; 2) assessing the science and applications value of each identified architecture; 3) down selecting to three final candidates and performing detailed assessments; 4) final reporting and preparation for mission formulation. The first phase is approximately 2 years in duration, and will concentrate on the scope of research and application areas to be addressed, defining the possible architectures to consider, and beginning the assessment of their performance. The study team comprises five NASA centers. Broad participation from the research, applications, technology, and commercial sectors is planned.

We present a detailed survey on the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is unstable due to the underlying geology that is formed by alternate and variable strata of highly soluble materials such as gypsum, anhydrite, marl and limestone. Here we present the first comprehensive multi-sensor cumulative deformation map for the dam generated from space-based synthetic aperture radar (SAR) measurements from the Italian constellation COSMO-SkyMed and the European Sentinel-1a satellite. We compared 2014-2016 data to an historic dataset spanning 2004-2010 acquired with the Envisat ASAR sensor. We found that deformation was rapid during 2004-2010, slowed down in 2012-2014, and restarted in August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State in Iraq and Syria (ISIS). We took advantage of the availability of data from multiple SAR satellites to infer the deformation at the dam in great spatial and temporal detail and shed new light on the processes of the ongoing destabilization. This study highlights how new constellations of SAR sensors together with the availability of historical datasets are leading to important advances in deformation monitoring of small scale geologic and manmade features.

We use data from the second generation of SAR systems e.g. the Italian COSMO-SkyMed constellation and the German TanDEM-X formation to monitor the characteristics of grounding line migration using short repeat-time interferometry and accurate InSAR DEM on Pine Island glacier (PIG), West Antarctica. Prior attempts of grounding lines mapping have been limited because few space-borne SAR missions offer the short-term repeat pass capability required to map the differential vertical displacement of floating ice at tidal frequencies with sufficient detail to resolve grounding line boundaries in areas of fast ice deformation.

The launch of Sentinel-1 constellation raise a new era for InSAR applications and time series analysis. The wide coverage, fine temporal and spatial resolution, precise control of orbits and the free distribution policy bring more new chances than ever to Earth observations applications. In this experiment we use Sentinel-1A data that covers a period of one year and a half (from November 2014 to June 2016) to study the ground movement of California Central Valley. Two different datasets were used and persistent scatterers interferometry technique was adopted for the time series analysis. The result indicates severe ground subsidence inside the study area, reaching a maximum rate of approximately 250 mm/yr at some locations.

We present a method for inferring time-dependent three-component surface deformation fields given a set of geodetic images of displacements collected from multiple viewing geometries. Displacements are parameterized in time with a dictionary of displacement functions. The algorithm extends an earlier single-component (i.e., single line of sight) framework for time-series analysis to three spatial dimensions using combinations of multitemporal, multigeometry interferometic synthetic aperture radar (InSAR) and/or pixel offset (PO) maps. We demonstrate this method with a set of 101 pairs of azimuth and range PO maps generated for a portion of the Rutford Ice Stream, West Antarctica, derived from data collected by the COSMO-SkyMed satellite constellation. We compare our results with previously published InSAR mean velocity fields and selected GPS time series and show that our resulting three-component surface displacements resolve both secular motion and tidal variability.

The April 25, 2015 M7.8 Gorkha earthquake caused more than 8,000 fatalities and widespread building damage in central Nepal. Four days after the earthquake, the Italian Space Agency's (ASI's) COSMO-SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area. Nine days after the earthquake, the Japan Aerospace Exploration Agency's (JAXA's) ALOS-2 SAR satellite covered larger area. Using these radar observations, we rapidly produced damage proxy maps derived from temporal changes in Interferometric SAR (InSAR) coherence. These maps were qualitatively validated through comparison with independent damage analyses by National Geospatial-Intelligence Agency (NGA) and the UNITAR's (United Nations Institute for Training and Research's) Operational Satellite Applications Programme (UNOSAT), and based on our own visual inspection of DigitalGlobe's WorldView optical pre- vs. post-event imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

Over the last three decades interferometric synthetic aperture radar (InSAR) techniques have attained a fundamental role in surface deformation monitoring. The main importance is given by two key factors: the exploitement of rich SAR data archives and the development of processing techniques able to extract information from these datasets. InSAR time series techniques such as permanent scatterers (PS) or SBAS have proven capable of estimating displacements to with 1 mm precision for targets that show a stable electromagnetic signature. At the same time the availability of SAR constellations with a reduced revisit time, such as the X band COSMO-SkyMed (CSK) and TerraSAR-X/PAZ satellites, has reduced the minimum detectable deformation gradient between two neighboring points and improved the theoretical precision given for a network of selected stable pixels. Independently from the applied processing methodology, the main drawback at X-band is the shorter time interval to temporal decorrelation. This effect can be partially mitigated by a short repeat time acquisitions plan. A technique able to deal with distributed scatterers is fundamental for extending the spatial coverage of the coherent area. In this paper we analyze the potential of X-band COSMO-SkyMed short repeat pass interferometry over a rural area in the southern part of Italy for assessing the capabilities and limitations of the Quasi-PS (QPS) technique in an X-band non-optimal scenario.

Mechanical properties of glacier beds impose fundamental constraints on glacier flow across a wide range of timescales [1]. Despite their importance in governing glacier dynamics, basal mechanics are not well understood, particularly where glaciers are underlain by deformable till [2]. While some till samples have been retrieved from beneath several glaciers and tested in laboratories in order to ascertain till rheology [3, 4], limitations on clast sizes imposed by apparatus dimensions and the difficulty of understanding and reproducing subglacial environments in the lab necessitate observations of the mechanical properties of in situ tills [5]. Such observations are sparse, owing to the inherent difficulty in attaining them, and this observational paucity has helped foment persistent uncertainties concerning the proper rheology of subglacial till and the rheological dependence on mechanical, thermal, and hydrological forcing [1, 2].

In this paper, we investigate the potential of Cosmo-SkyMed (CSK) platform to offer a basis for the generation of hybrid ScanSAR-Stripmap differential interferograms to be used for the retrieval of long-lasting time-series of deformation via advanced multi-temporal DInSAR approaches. In particular, this study represents a first preliminary step in the perspective to extend the well-known small baseline subset (SBAS) approach to the use of such hybrid CSK datasets, thus expanding what already proposed in literature for ENVISAT data. Experimental results were achieved by processing hybrid stripmap-ScanSAR SAR data pairs collected over a mine facility in Chile; achieved results confirm the validity of applied methods.

Stability of monuments and subsidence of residential quarters in Rome (Italy) are depicted based on geospatial analysis of more than 310,000 Persistent Scatterers (PS) obtained from Stanford Method for Persistent Scatterers (StaMPS) processing of 32 COSMO-SkyMed 3m-resolution HH StripMap ascending mode scenes acquired between 21 March 2011 and 10 June 2013. COSMO-SkyMed PS densities and associated displacement velocities are compared with almost 20 years of historical C-band ERS-1/2, ENVISAT and RADARSAT-1/2 imagery. Accounting for differences in image processing algorithms and satellite acquisition geometries, we assess the feasibility of ground motion monitoring in big cities and metropolises by coupling newly acquired and legacy SAR time series. Limitations and operational benefits of the transition from medium resolution C-band to high resolution X-band PS data are discussed, alongside the potential impact on the management of expanding urban environments.