Accurate monitoring of ground deformation is important for understanding the processes that lead to natural disasters, and the health and safety of society. The discovery of a fading signal has put the accuracy of methods that utilise multilooking and short-temporal interferograms into question. A symptom of this signal is that multilooked interferograms may exhibit a non-zero phase loop closure. We compare the phase loop closure in C-band and L-band InSAR data over different land cover types for an area centered on Milan, Italy. Our findings suggest that changes in volume scattering are the leading cause of phase loop misclosure and the fading signal in this area. We also investigate the effects of multilooking on the magnitude of phase loop misclosure with the goal of developing a model of the fading signal for both C-band and L-band InSAR.

This article contains description of an improved tool for phase unwrapping, as developed and to be applied routinely within COMET LiCSAR system producing Sentinel-1 interferograms in 0.001° resolution (WGS-84). We apply existing standard methods on routinely available data in a way to improve reliability of the standard phase unwrapping procedure and increase coverage of unwrapped pixels. The primary idea is to reduce high phase gradients, causing both decorrelation and zonal unwrapping errors, by extracting and unwrapping long-wave spatial signal (extracted by a combination of multilooking and Gaussian filtering) and signal related to atmosphere that can be modeled (e.g. using COMET GACOS data or by correlation of phase with a DEM). We show the effect of the improved approach is significant in standard time series processing (here using LiCSBAS).

High precision monitoring of infrastructure using artificial reflectors is possible with freely available Sentinel-1 data, but large reflectors are needed. We find that a triangular trihedral corner reflector should typically have at least 1 m inner leg length. As such large reflectors are often not feasible for use in urban areas for essential infrastructure monitoring, we designed a multiple corner-reflector array to replace a single corner reflector with an inner leg length of 1 m. In this case, we use four reflectors where each of them is a truncated triangular trihedral with an inner leg length of 0.33 m. We measured InSAR amplitude, phase and coherence of this reflector array with various configurations of alignments of the array. We find that as long as great care is taken in the relative positioning of the four corner reflectors, so that they constructively interfere, each horizontal or vertical configuration provides the expected amplitude, coherence and phase stability. Applications of multiple small corner reflectors in urban areas range from essential infrastructure monitoring (e.g bridges, overpasses, tunnel constructions), through assessment of structural health of buildings, to monitoring highway and railway embankments. We show that the multiple corner array works when placed in a single InSAR resolution cell, but depending on the application, the number and projection of corner reflectors can be varied, as long as sufficient signal-to-clutter ratio is achieved in the area of interest.

This article contains brief overview on current key improvements in the interferograms generator part of LiCSAR, a system to generate open access moderate resolution Sentinel-1 interferograms aiming towards monitoring tectonic and volcanic deformation. We were focusing on improvements in performance and quality of unwrapping, and quality control of LiCSAR data.

Interferometric Synthetic Aperture Radar (InSAR) is a powerful tool for monitoring ground deformation associated with earthquakes, volcanoes, landslides, and different anthropogenic activities. The accuracy of the estimated deformation depends on a number of parameters including tropospheric and ionospheric delays, unwrapping errors, phase decorrelation due to changes in scattering behavior and system noise. However, recently an additional source of phase noise has been identified [1], which is strongest in short-interval multi-looked interferograms and, unlike other sources of noise, leads to biased, non-zero loop closure phases. This is problematic for time-series analysis because short-interval interferograms may be the only ones that maintain coherence for some areas. In this study, we explore the characteristics of this phenomenon and propose a mitigation strategy.

Bridge owners are faced with the challenge of maintaining an ageing and deteriorating asset portfolio. There is an increasing amount of InSAR data becoming available for built environment monitoring, with the opportunity to leverage free ESA Sentinel-1 data for regular monitoring. By understanding the potential to augment existing modelling tools used in common bridge engineering practice, InSAR can provide valuable additional insights and spot potential problems. In this paper we study Hammersmith Flyover, a concrete bridge in London, United Kingdom. We combine geometric models, structural models and InSAR data within a GIS environment and demonstrate how these systems can be used to regularly monitor specific behaviors including thermal expansion.

The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015-2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems.

Geodetic measurements of crustal deformation rates provide important information on earthquake hazard, indicating that strain is accumulating either faster or slower than the rate suggested by known earthquakes. With the COMET-LiCSAR InSAR processing system, which performs large-scale automated processing and timeseries analysis of Sentinel-1 data, we aim to generate strain rate maps for the entire Alpine-Himalayan Belt, and use these to investigate seismic hazard. In this paper we will present results for Anatolia. Deformation is also a key indicator of volcanic unrest, and is often associated with the flow of magma to shallower depths. The operational nature of Sentinel-1, with frequent revisits and rapid data delivery, makes it suitable for monitoring subaerial volcanoes globally. In order to deal with the large quantity of new data that is continuously being generated, we have developed machine learning approaches to flag when either a new deformation pattern emerges, or an existing deformation pattern changes rate.

Sentinel-1 represents a major step forward in enabling us to monitor the Earth's hazardous tectonic and volcanic zones. Here, we present the latest progress from the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET), where we provide deformation results to the community for volcanoes and the tectonic belts. For the estimation of seismic hazard, we require relative accuracy on the order of 1 mm/yr between points 100 km apart. This requires mass processing of long time series of radar acquisitions. As of January 2018, we are producing in-terferograms systematically for the entire Alpine-Himalayan belt (~9000 × 2000 km) and the majority of subaerial volcanoes. Currently we make interferograms and coherence products available to the community, but we plan to also provide average deformation rates and displacement time series, in the future. The results are made available through a dedicated COMET portal, and we are in the process of linking them to the ESA G-TEP and EPOS. COMET also responds routinely to significant continental earthquakes, larger than ~Mw 6.0. The short repeat interval of Sentinel-1, together with the rapid availability of the data, allows us to do this within a few days for most earthquakes. For example, after the Mw 7.8 Kaikoura earthquake we supplied a processed interferogram to the community just 5 hours and 37 minutes after the Sentinel-1 acquisition. In this paper we provide an overview of some of the latest results for tectonics and volcanism and discuss how the accuracy of these products will improve as the number of data products acquired by Sentinel-1 increases.

The interferometric coherence is a measure of the correlation between two SAR images and constitutes a commonly used estimator of the phase quality. Its estimation requires a spatial average within a 2-D window, usually named as multilook. The multilook processing allows reducing noise at the expenses of a resolution loss. In this letter, we analyze the influence of the multilook size while applying a polarimetric optimization of the coherence. The same optimization algorithm has been carried out with different multilook sizes and also with the nonlocal SAR filter filter, which has the advantage of preserving the original resolution of the interferogram. Our experiments have been carried out with a single pair of quad-polarimetric RADARSAT-2 images mapping the Mount Etna's volcanic eruption of May 2008. Results obtained with this particular data set show that the coherence is increased notably with respect to conventional channels when small multilook sizes are employed, especially over low-vegetated areas. Conversely, very decorrelated areas benefit from larger multilook sizes but do not exhibit an additional improvement with the polarimetric optimization.

The two-satellite Copernicus Sentinel-1 (S1) constellation became operational in Sep 2016, with the successful in-orbit commissioning of the S1B unit. During, the commissioning phase and early operational phase it has been confirmed that the interferometric performance of the constellation is excellent, with no observed phase anomalies. In this work, we show an analysis of selected performance parameters for the S1 constellation, as well as initial results based on the available data from the first months of operations.

The SuperSAR imaging system, a novel multi-azimuth synthetic aperture radar (SAR) system capable of detecting Earth surface deformation in three dimensions from a single satellite platform, has recently been proposed. In this paper, we investigate the feasibility of detecting precise 3-D surface displacement measurements with the SuperSAR imaging system using a point target simulation. From this simulation, we establish both a relationship between the interferometric SAR phase and the across-track displacement and a relationship between the multiple-aperture interferometry phase and the along-track displacement based on the SuperSAR imaging geometry. The theoretical uncertainties of the SuperSAR measurement are analyzed in the across- and along-track directions, and the theoretical accuracy of the 3-D displacement measurement from the SuperSAR system is also investigated according to both the decorrelation and the squint and look angles. In the case that the interferometric coherence is about 0.8 and that five effective looks are employed, the theoretical 2-D measurement precision values are about 3.67 and 6.35 mm in the across- and along-track directions, respectively, and the theoretical 3-D measurement precision values for 3-D displacement are about 4.05, 4.56, and 3.45 mm in the east, north, and up directions, respectively. The result of this study demonstrates that the SuperSAR imaging system is capable of measuring the 3-D surface displacement in all directions with subcentimeter precision.