There is a growing trend towards making Synthetic Aperture Radar (SAR), SAR Interferometry (InSAR), and their applications more accessible to end users. Directly delivering geocoded, co-registered, and flattened SLC data (GSLC) eliminates the need for the complex geocoding and co-registration procedures which require professional domain knowledge and software. GSLC products dramatically simplify InSAR processing flows, making InSAR products easily available to a wide range of users. However, challenges still exist for SAR/InSAR analysis using GSLC datasets. In this paper, we analyze the feasibility of using GSLC for deformation measurements based on offset tracking, both in theory and practice. We find that correct GSLC offset tracking requires the input GSLCs to be 1) unflattened, 2) deramped, and 3) adequately sampled. We also show that the direct result from GSLC offset tracking is a projection of displacement in the slant range and azimuth directions. We can transform the offset measurement from GSLCs to the deformation field, but the current transformation relation is not precise enough. This research may help deepen the understanding of GSLCs and their applications.

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.

Volcano monitoring and eruption response is centered on local volcano observatories who are informed through their local networks of in situ instruments, especially seismometer and Global Navigation Satellite System (GNSS) geodetic time series. Interferometric synthetic aperture radar (InSAR) has an increasing role in volcano monitoring. Typically, this occurs with InSAR providing context during episodes of unrest and eruption, usually with a request by the local observatory to relevant scientists. Here we provide some examples of recent InSAR contributions to volcano unrest and eruption, mostly from satellite InSAR, but also with an example from single pass airborne interferometry for topography change during the 2018 Kilauea eruption. We will conclude by pointing towards future directions applying large scale processing combined with dynamical volcano modeling to aid system forecasting.

Volcano monitoring is centered around volcano observatories that rely on local networks of in situ instruments to monitor activity in near-real time. Primary observations include seismicity, surface deformation, and thermal and gas emissions. Satellite remote sensing observations of surface deformation (from interferometric synthetic aperture radar; InSAR) and spectroscopic data are showing increasing potential for volcano monitoring as their availability and quality improve. Here we present new insights we derive from the combination of InSAR and thermal time series on driving models for volcano processes, and their implications for volcano monitoring. We present analyses of three volcanoes: Domuyo (Argentina), Taal (Philippines), and Nevados de Chillán (Chile), whose geodetic time series show a deflation-inflation striking pattern. We discuss the implications of these observations for volcano dynamics at these diverse volcanic systems.