An accurate method to correct atmospheric phase delay for InSAR with the ERA5 global atmospheric model

Differential SAR Interferometry (DInSAR) has proven its unprecedented ability and merits of monitoring ground deformation on a large scale with centimeter to millimeter accuracy. However, atmospheric artifacts due to spatial and temporal variations of the atmospheric state often affect the reliability and accuracy of its results. The commonly-known Atmospheric Phase Screen (APS) appears in the interferograms as ghost fringes not related to either topography or deformation. Atmospheric artifact mitigation remains one of the biggest challenges to be addressed within the DInSAR community. State-of-the-art research works have revealed that atmospheric artifacts can be partially compensated with empirical models, point-wise GPS zenith path delay, and numerical weather prediction models. In this study, we implement an accurate and realistic computing strategy using atmospheric reanalysis ERA5 data to estimate atmospheric artifacts. With this approach, the Line-of-Sight (LOS) path along the satellite trajectory and the monitored points is considered, rather than estimating it from the zenith path delay. Compared with the zenith delay-based method, the key advantage is that it can avoid errors caused by any anisotropic atmospheric phenomena. The accurate method is validated with Sentinel-1 data in three different test sites: Tenerife island (Spain), Almería (Spain), and Crete island (Greece). The effectiveness and performance of the method to remove APS from interferograms is evaluated in the three test sites showing a great improvement with respect to the zenith-based approach.Peer ReviewedPostprint (published version

Long-term monitoring of geodynamic surface deformation using SAR interferometry

Thesis (Ph.D.) University of Alaska Fairbanks, 2014Synthetic Aperture Radar Interferometry (InSAR) is a powerful tool to measure surface deformation and is well suited for surveying active volcanoes using historical and existing satellites. However, the value and applicability of InSAR for geodynamic monitoring problems is limited by the influence of temporal decorrelation and electromagnetic path delay variations in the atmosphere, both of which reduce the sensitivity and accuracy of the technique. The aim of this PhD thesis research is: how to optimize the quantity and quality of deformation signals extracted from InSAR stacks that contain only a low number of images in order to facilitate volcano monitoring and the study of their geophysical signatures. In particular, the focus is on methods of mitigating atmospheric artifacts in interferograms by combining time-series InSAR techniques and external atmospheric delay maps derived by Numerical Weather Prediction (NWP) models. In the first chapter of the thesis, the potential of the NWP Weather Research & Forecasting (WRF) model for InSAR data correction has been studied extensively. Forecasted atmospheric delays derived from operational High Resolution Rapid Refresh for the Alaska region (HRRRAK) products have been compared to radiosonding measurements in the first chapter. The result suggests that the HRRR-AK operational products are a good data source for correcting atmospheric delays in spaceborne geodetic radar observations, if the geophysical signal to be observed is larger than 20 mm. In the second chapter, an advanced method for integrating NWP products into the time series InSAR workflow is developed. The efficiency of the algorithm is tested via simulated data experiments, which demonstrate the method outperforms other more conventional methods. In Chapter 3, a geophysical case study is performed by applying the developed algorithm to the active volcanoes of Unimak Island Alaska (Westdahl, Fisher and Shishaldin) for long term volcano deformation monitoring. The volcano source location at Westdahl is determined to be approx. 7 km below sea level and approx. 3.5 km north of the Westdahl peak. This study demonstrates that Fisher caldera has had continuous subsidence over more than 10 years and there is no evident deformation signal around Shishaldin peak.Chapter 1. Performance of the High Resolution Atmospheric Model HRRR-AK for Correcting Geodetic Observations from Spaceborne Radars -- Chapter 2. Robust atmospheric filtering of InSAR data based on numerical weather prediction models -- Chapter 3. Subtle motion long term monitoring of Unimak Island from 2003 to 2010 by advanced time series SAR interferometry -- Chapter 4. Conclusion and future work

Generic interferometric synthetic aperture radar atmospheric correction model and its application to co- and post-seismic motions

PhD ThesisThe tremendous development of Interferometric Synthetic Aperture Radar (InSAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses more challenges for correcting atmospheric effects due to the spatial-temporal variability of atmospheric delays. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate the atmospheric delays, but they are limited by (i) the availability (and distribution) of GPS stations; (ii) the time difference between NWM and radar observations; and (iii) the difficulties in quantifying their performance. To overcome the abovementioned limitations, we have developed the Iterative Tropospheric Decomposition (ITD) model to reduce the coupling effects of the troposphere turbulence and stratification and hence achieve similar performances over flat and mountainous terrains. Highresolution European Centre for Medium-Range Weather Forecasts (ECMWF) and GPS-derived tropospheric delays were properly integrated by investigating the GPS network geometry and topography variations. These led to a generic atmospheric correction model with a range of notable features: (i) global coverage, (ii) all-weather, all-time usability, (iii) available with a maximum of two-day latency, and (iv) indicators available to assess the model’s performance and feasibility. The generic atmospheric correction model enables the investigation of the small magnitude coseismic deformation of the 2017 Mw-6.4 Nyingchi earthquake from InSAR observations in spite of substantial atmospheric contamination. It can also minimize the temporal correlations of InSAR atmospheric delays so that reliable velocity maps over large spatial extents can be achieved. Its application to the post-seismic motion following the 2016 Kaikoura earthquake shows a success to recover the time-dependent afterslip distribution, which in turn evidences the deep inactive subduction slip mechanism. This procedure can be used to map surface deformation in other scenarios including volcanic eruptions, tectonic rifting, cracking, and city subsidence.This work was supported by a Chinese Scholarship Council studentship. Part of this work was also supported by the UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET)

An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

Phase filtering and pixel quality (coherence) estimation is critical in producing Digital Elevation Models (DEMs) from Interferometric Synthetic Aperture Radar (InSAR) images, as it removes spatial inconsistencies (residues) and immensely improves the subsequent unwrapping. Large amount of InSAR data facilitates Wide Area Monitoring (WAM) over geographical regions. Advances in parallel computing have accelerated Convolutional Neural Networks (CNNs), giving them advantages over human performance on visual pattern recognition, which makes CNNs a good choice for WAM. Nevertheless, this research is largely unexplored. We thus propose "GenInSAR", a CNN-based generative model for joint phase filtering and coherence estimation, that directly learns the InSAR data distribution. GenInSAR's unsupervised training on satellite and simulated noisy InSAR images outperforms other five related methods in total residue reduction (over 16.5% better on average) with less over-smoothing/artefacts around branch cuts. GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0.54, 0.07, and 0.05 respectively compared to the related methods.Comment: to be published in a future issue of IEEE Geoscience and Remote Sensing Letter

A Method for Selecting SAR Interferometric Pairs Based on Coherence Spectral Clustering

To achieve accurate interferometric synthetic aperture radar (SAR) phase estimation, it is essential to select appropriate high-coherence interferometric pairs from massive SAR single-look complex (SLC) image data. The selection should include as many high-coherence interferometric pairs as possible while avoiding low-coherence pairs. By combining coherence and spectral clustering, a novel selection method for SAR interferometric pairs is proposed in this article. The proposed method can be adopted to classify SAR SLC images into different clusters, where the total coherence of interferometric pairs in the same cluster is maximized while that among different clusters is minimized. This is implemented by averaging the coherence matrices of representative pixels to construct an adjacency matrix and performing eigenvalue decomposition for estimating the number of clusters. The effectiveness of the proposed method is demonstrated using 33 TerraSAR-X and 38 dual-polarization Sentinel-1A data samples, yielding improved topography and deformation monitoring results

Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation

The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements’, such as height or displacement, phase filtering is therefore an essential step. In this work, an improved Goldstein interferogram filter is proposed to suppress the phase noise while preserving the fringe edges. First, the proposed adaptive filter step, performed before frequency estimation, is employed to improve the estimation accuracy. Subsequently, to preserve the fringe characteristics, the estimated fringe frequency in each fixed filtering patch is removed from the original noisy phase. Then, the residual phase is smoothed based on the modified Goldstein filter with its parameter alpha dependent on both the coherence map and the residual phase frequency. Finally, the filtered residual phase and the removed fringe frequency are combined to generate the filtered interferogram, with the loss of signal minimized while reducing the noise level. The effectiveness of the proposed method is verified by experimental results based on both simulated and real data

Summaries of the Sixth Annual JPL Airborne Earth Science Workshop

The Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996, was divided into two smaller workshops:(1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, and The Airborne Synthetic Aperture Radar (AIRSAR) workshop. This current paper, Volume 2 of the Summaries of the Sixth Annual JPL Airborne Earth Science Workshop, presents the summaries for The Airborne Synthetic Aperture Radar (AIRSAR) workshop