We document one of several methodologies used to validate the NASA-ISRO Synthetic Aperture Radar (NISAR) mission requirements for solid earth deformation. NISAR’s deformation requirements cover steady-state, coseismic, and transient deformation processes and were designed to confirm that the mission is able to meet its solid earth science goals. We use independent observations of earth surface deformation from continuous Global Navigation Satellite System (GNSS) stations as ground truth for NISAR-observed deformation, and we provide a statistical framework to assess the quality of the associated NISAR data products. Our validation workflows have been developed as Jupyter Notebooks and are publicly available via GitHub/GitLab.

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.

We present the validation methodology and results of Dynamic Surface Water eXtent from Harmonized Landsat Sentinel-2 (DSWx-HLS). The DSWx-HLS product is the first of the DSWx suite, comprised of products each which map water from Earth Observation optical and SAR satellites. We detail the generation of high-resolution (3 m) validation datasets from a globally-stratified sample of dry, moderate, and wet sites. We provide the precise accounting of the classification metrics used to verify the Observational Products for End-users from Remote Sensing Analysis (OPERA) project requirements. We also report broader classification metrics across the validation datasets considered. OPERA performs validation in the public domain to ensure that the validation activities are transparent and reproducible. The resulting validation datasets and provisional OPERA products are publicly available; the software used for validation is also open-source.

NASA has committed to open-source science that enables Earth observation data transparency, inclusivity, accessibility, and reproducibility – all fundamental to the pace and quality of scientific progress. We have embraced this vision by producing standard InSAR science products that are freely available to the public through NASA Data Active Archive Centers (DAACs) and are generated using state-of-the-art open-source and openly-developed methods. The Advanced Rapid Image Analysis (ARIA) project’s Sentinel-1 Geocoded Unwrapped Phase product (ARIA-S1-GUNW) is a 90 meter InSAR product that spans major, land-based fault systems, the US Coasts, and active volcanic regions through the complete Sentinel-1 record. The products enable the measurement of centimeter-scale surface displacement with applications across the solid earth, hydrology, and sea-level disciplines. The ARIA-S1-GUNW also enables rapid response mapping of surface motion after earthquakes, landslides, and subsidence. The ARIA-S1-GUNW products are freely available through the Alaska Satellite Facility (ASF) DAAC. In the last year, we have successfully grown the archive to over 1.1 million products, a 6 fold increase, through NASA ACCESS by improving our processing workflow and leveraging HyP3, an AWS-based cloud processing environment. We are continuing to partner with researchers to generate more products over relevant areas of scientific interest. All the processing software and cloud infrastructure are open-source to ensure reproducibility and enable other scientists to modify, improve upon, and scale their own cloud workflows for related InSAR analyses. We have, in parallel, developed and supported open-source, well-documented tools to further streamline time-series analysis from the ARIA-S1-GUNW into deformation analysis workflows.

Use of Synthetic Aperture Radar (SAR) data has been steadily increasing over the past decade as data from sensors become freely available. In this article, our focus is on the NASA-ISRO SAR (NISAR), the Observational Products for End-Users from Remote Sensing Analysis (OPERA), and Surface Deformation and Change (SDC), and how their user engagement activities combine to build a cohesive user engagement effort for SAR remote sensing. All of NASA remote sensing data is openly and freely available through its Distributed Active Archive Centers (DAAC), and SAR data is no exception. Data going back to SEASAT in 1978 can be accessed through the Alaska Satellite Facility, NASA’s SAR DAAC. The NISAR mission is expected to significantly increase the volume of SAR data available to the end users after its launch in early 2024. OPERA project is already underway preparing high-level data products suited for end-users and will be leveraging NISAR data when it becomes available. Finally, NASA is already conducting the SDC mission study to define a mission architecture for the next decade.

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) project at the Jet Propulsion Laboratory (JPL) will provide a near-global Radiometric Terrain Corrected synthetic aperture radar (SAR) backscatter from Sentinel-1 (RTC-S1) product. The OPERA RTC-S1 product will deliver map-projected burst-based radar images with a geographic scope that includes all land masses excluding Antarctica, and with temporal sampling coincident with the availability of Sentinel-1 interferometric wide (IW) single-look complex (SLC) data. This paper presents the OPERA RTC-S1 product, providing details about its layers, static layers, and metadata; describing the product’s processing workflow, based on the ISCE3 framework and using the same algorithms developed for the NASA-ISRO Synthetic Aperture Radar (NISAR) mission; and outlining the algorithm verification and the product validation plan. We also present a global mosaic of preliminary OPERA RTC-S1 products generated from a global end-to-end test run from a Sentinel-1A orbit cycle. The OPERA RTC-S1 product will be publicly distributed through the Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) free of charge, with a release date scheduled for September 2023 with forward stream production.

In this work, we demonstrate how harmonized optical and SAR satellite imagery can be utilized for robust identification of open water surfaces at a global scale. We train an image segmentation architecture based convolutional neural network (CNN) to extract the most salient features from the input data and generate a per-pixel water/not-water classification. We find that combining optical and radar imagery helps reduce false positive and false negative inferences, illustrating the effectiveness of this harmonization. The resulting model is able to classify water surfaces at the resolution of the SAR sensor (12.5 meters) with a validation set precision and recall of 0.74 and 0.81 respectively. We also demonstrate that the trained model is capable of generating inferences beyond the geographic bounds of the training data.

We study the distribution of slip on faults during earthquakes with integrated analysis of geodetic imaging and seismic data to learn about parameters that control how faults slip and potentially how damaging future earthquakes may be. We mapped complex fault ruptures for a number of large earthquakes in 2015–2020 using analysis of synthetic aperture radar (SAR) data from the Copernicus Sentinel-1A and Sentinel-1B satellites operated by the European Space Agency and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japan Aerospace Exploration Agency (JAXA). We used regular SAR interferometry, along-track or multiple-aperture interferometry, and pixel offset tracking to measure surface displacements and combined this with other geodetic and seismic data to infer slip on faults at depth.

The joint NASA/ISRO SAR (NISAR) satellite mission is anticipated to provide routine L-band coverage of most of the Earth's land surface every 12-days for both ascending and descending orbits. In terms of impact on solid earth science (SES), the primary measurement will be Interferometric SAR (InSAR) observations of ground deformation in two satellite line-of-sight (LOS) directions. Key observation characteristics include acquisitions with small interferometric baselines to maximize interferometric coherence and decrease sensitivity to topography, wide bandwidth allowing for split-band processing to model out the impacts of the ionosphere, and joint L- and S-band observations in selected regions. We describe here the key measurement requirements for solid earth science, as well as our approach to validating these requirements once the mission is underway.

During 2013-2017, the State of California experienced a major drought that impacted water management practices, water delivery, and groundwater extraction, any of which had the potential to impact the critical infrastructure used for water conveyance. The use of synthetic aperture radar interferometry (InSAR) and multi-polarization SAR images to monitor levees and aqueducts in California during the period 2009-2016, which overlapped the drought, is described. The study used data acquired with UAVSAR, an L-band airborne SAR instrument operated by NASA. An overview is given of the methodology adopted to measure subsidence rates of ≥ 2 mm/yr of earthen levees and aqueduct embankments. Results are presented showing the most significant identified hazards to the structures from ongoing land use practices, natural hazards, and groundwater withdrawal.

Within this study we tested a combination of processing tools in order to overcome certain limitations of Advanced Differential Interferometrie SAR (A-DInSAR) for the detection of intraplate surface motion. The study area is located over the Hyblean Plateau in south-east Sicily, Italy. Instead of usually applied spatio-temporal smoothing of the stacked dataset, we calculated the atmospheric contribution within the interferometrie signal by external data from the global meteorological model ERA-INTERIM. Furthermore we enhanced the coverage of the mean line-of-sight velocity by gap filling and applied a multi-directional filter. For this we used ENVISAT ASAR imagery (49 scenes descending and 58 scenes ascending orbit). The output was then integrated with local GPS data into the SISTEM framework to decompose the measurements into a 3-dimensional velocity field. While in areas of no GPS stations, detected deformation is not precise enough, the results in areas of good GPS coverage look promising with accuracies down to 1 mm/y and various zones of surface deformation could be detected successfully.

In February 2011, the Polarimetric Airborne Radar Ice Sounder (POLARIS) was flown in Antarctica in order to assess the feasibility of a potential space-based radar ice sounding mission. The campaign has demonstrated that the basal return is detectable in areas with up to 3 km thick cold ice, in areas with up to several hundred meters thick warm shelf ice, and in areas with up to 700 m thick crevassed glacier ice. However, major gaps in the basal return are observed, presumably due to excessive absorption, scattering from ice inclusions in the firn, low basal reflectivity, and the masking effect of the surface clutter. Internal layers are observed down to depths exceeding 2 km. The polarimetric data show that the internal layers are strongly anisotropic at a ridge, where the ice flow is supposed to be highly unidirectional. In case of space-based ice sounding, the antenna pattern cannot offer sufficient surface clutter suppression, but improved clutter suppression has been demonstrated with novel multi-phase-center techniques.