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SUMMARY InSAR displacement time-series are emerging as a valuable product to study a number of Earth processes. One challenge to current time-series processing methods, however, is that when large earthquakes occur, they can leave sharp coseismic steps in the time-series. These discontinuities can cause current atmospheric correction and noise smoothing algorithms to break down, as these algorithms commonly assume that deformation is steady through time. Here, we aim to remedy this by exploring two methods for correcting earthquake offsets in InSAR time-series: a simple difference offset estimate (SDOE) process and a multiparameter offset estimate (MPOE) parametric time-series inversion technique. We apply these methods to a 2-yr time-series of Sentinel-1 interferograms spanning the 2019 Ridgecrest, CA earthquake sequence. Descending track results indicate that the SDOE method precisely corrects for only 20 per cent of the coseismic offsets at 62 study locations included in our scene and only partially corrects or sometimes overcorrects for the rest of our study sites. On the other hand, the MPOE estimate method successfully corrects the coseismic offset for the majority of sites in our analysis. This MPOE method allows us to produce InSAR time-series and data-derived estimates of deformation during each phase of the earthquake cycle. In order to better isolate and estimate the signal of post-seismic lithospheric deformation in the InSAR time-series, we apply a GNSS-based correction to our interferograms. This correction ties the interferograms to median-filtered weekly GNSS displacements and removes additional atmospheric artefacts. We present InSAR-based estimates of post-seismic deformation for the area around the Ridgecrest rupture, as well as a 2-yr coseismic-corrected, GNSS-corrected InSAR time-series data set. This GNSS-corrected InSAR time-series will enable future modelling of post-seismic processes such as afterslip in the near field of the rupture, poroelastic deformation at intermediate distances and viscoelastic deformation at longer timescales in the far field.
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This content will become publicly available on July 1, 2026
InSAR Detection of Slow Ground Deformation: Taking Advantage of Sentinel-1 Time Series Length in Reducing Error Sources
Using interferometric synthetic aperture radar (InSAR) to observe slow ground deformation can be challenging due to many sources of error, with tropospheric phase delay and unwrapping errors being the most significant. While analytical methods, weather models, and data exist to mitigate tropospheric error, most of these techniques are unsuitable for all InSAR applications (e.g., complex tropospheric mixing in the tropics) or are deficient in spatial or temporal resolution. Likewise, there are methods for removing the unwrapping error, but they cannot resolve the true phase when there is a high prevalence (>40%) of unwrapping error in a set of interferograms. Applying tropospheric delay removal techniques is unnecessary for C-band Sentinel-1 InSAR time series studies, and the effect of unwrapping error can be minimized if the full dataset is utilized. We demonstrate that using interferograms with long temporal baselines (800 days to 1600 days) but very short perpendicular baselines (<5 m) (LTSPB) can lower the velocity detection threshold to 2 mm y−1 to 3 mm y−1 for long-term coherent permanent scatterers. The LTSPB interferograms can measure slow deformation rates because the expected differential phases are larger than those of small baselines and potentially exceed the typical noise amplitude while also reducing the sensitivity of the time series estimation to the noise sources. The method takes advantage of the Sentinel-1 mission length (2016 to present), which, for most regions, can yield up to 300 interferograms that meet the LTSPB baseline criteria. We demonstrate that low velocity detection can be achieved by comparing the expected LTSPB differential phase measurements to synthetic tests and tropospheric delay from the Global Navigation Satellite System. We then characterize the slow (~3 mm/y) ground deformation of the Socorro Magma Body, New Mexico, and the Tampa Bay Area using LTSPB InSAR analysis. The method we describe has implications for simplifying the InSAR time series processing chain and enhancing the velocity detection threshold.
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- Award ID(s):
- 2321754
- PAR ID:
- 10615117
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 17
- Issue:
- 14
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 2420
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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