Aug 2026· Earth and Space Science· Vol 13· 0 citations· 92 references
Abstract
Routine Synthetic Aperture Radar (SAR) acquisitions from the Sentinel‐1 constellation enable monitoring of slow surface deformation (millimeters to centimeters per year), yet consistent and accessible pathways for producing validated, user‐ready velocity products remain limited. Here we present (a) a statewide Interferometric SAR (InSAR) line‐of‐sight secular surface velocity map for California derived from standardized Advanced Rapid Imaging and Analysis Sentinel‐1 Geocoded Unwrapped Phase (ARIA‐S1‐GUNW) products spanning 2014–2023, and (b) the details of a scalable processing and validation workflow for producing similar maps. Our workflow leverages several open‐source software tools for post‐processing of GUNW products, time series analysis, corrections for noise, and removal of earthquakes and transient signals. We apply it to data from nine ascending and descending Sentinel‐1 tracks across California, and validate the output against Global Navigation Satellite Systems (GNSS) data. The resulting velocity fields resolve tectonic and anthropogenic deformation signals, including elastic strain accumulation and shallow creep along the San Andreas Fault system, rapid subsidence exceeding 10 cm/yr in the Central Valley, and localized deformation associated with groundwater withdrawal and landsliding. We find millimeter‐per‐year agreement with GNSS velocities, and estimate typical velocity uncertainties to be ≤1 mm/yr over coherent terrain, increasing locally in regions of strong deformation gradients and/or decorrelation. Our velocity map provides an accessible data set for non‐specialists to investigate multiple sources of slow secular deformation across California; our workflow can also be used with GUNW products from the NASA‐ISRO SAR (NISAR) mission, enabling the leveraging of that rich data source in the future.
In this study, we derived pan-Arctic multiyear ice (MYI) and first-year sea ice (FYI) retrievals at 1.6 km resolution under no-melt conditions using the RADARSAT Constellation Mission (RCM) ScanSAR dual-polarization HH-HV synthetic aperture radar (SAR) data. The RCM products consistently provide fine-scale MYI/FYI deta...
Alexander S. Komarov, A. Caya, M. Buehner· IEEE Geoscience and Remote S...· 0 citations
Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has matured into a credible, non-contact technique for monitoring bridge deformation from individual structures to regional portfolios. The main challenge for routine engineering use is no longer measuring millimetre-scale line-of-sight (LOS) displace...
A. Khan, A. Pimanmas· Intelligent Transportation I...· 0 citations
Large wildfires cause casualties, ecosystem damage, and property loss. Reducing them requires predicting spread; validating a spread model requires pixel-level time of arrival (ToA) from real fires. Few regions have both such data and an independent reference. We combine polar-orbiting (VIIRS) and geostationary (GOES,...
Chulhyun Choi, Hyunjin Seo, Jaegyu Cha· Remote Sensing· 0 citations
High Frequency (HF) Radars measure surface currents at higher resolutions (hourly at every ∼6 km), which are essential for understanding the coastal ocean circulation processes at multiple spatio-temporal scales. However, as shore-based remote sensing platforms, these systems are susceptible to data gaps due to env...
Arun Kumar, Samiran Mandal, A. Gangopadhyay· Journal of Atmospheric and O...· 0 citations
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