SCEC Award Number 19234 View PDF
Proposal Category Collaborative Proposal (Data Gathering and Products)
Proposal Title Collaborative research: Complementing CGM with Sentinel-1 InSAR data
Name Organization
Yuri Fialko University of California, San Diego Susan Owen National Aeronautics and Space Administration Ekaterina Tymofyeyeva University of California, San Diego
Other Participants
SCEC Priorities 1a, 2a, 3a SCEC Groups Geodesy
Report Due Date 04/30/2020 Date Report Submitted 05/18/2020
Project Abstract
The SCEC Community Geodetic Model (CGM) aims to describe surface deformation in Southern California at highest possible spatio-temporal resolution and accuracy. This requires an optimal integration of GPS and InSAR data. Sentinel-1 mission of the European Space Agency provides several key features essential for CGM, including: i) frequent and regular acquisitions. The nominal revisit time for the currently operational Sentinel-1A and 1B satellites is 6 days. This can be compared to the minimum revisit time of 35 days for the previous ESA missions such as ERS-1/2 and ENVISAT. ii) A smaller revisit time not only improves temporal resolution, but also significantly reduces problems with decorrelation of the radar phase, and helps mitigate atmospheric artifacts by virtue of averaging. iii) Wide-swath capability. 300-km-wide swathes of Sentinel-1 ensure a complete coverage of Southern California with just a few tracks. iv) Uniform coverage from both ascending and descending satellite orbits. Data from two different look directions allow us to separate horizontal and vertical components of surface displacements. Incorporation of Sentinel-1 data is therefore expected to result in a significant improvement of CGM. We have set up a system for routine systematic processing of all of Sentinel-1 data from Southern California. We also developed and implemented algorithms for corrections for the atmospheric noise, and errors due to multi-looking and filtering of the radar phase.
Intellectual Merit Interferometric Synthetic Aperture Radar (InSAR) data are increasingly used to image deformation due to active faults. One of the well-recognized limitations of InSAR measurements of low-amplitude long-wavelength signals such as those due to interseismic deformation is increased uncertainty at wavelengths greater than several tens of kilometers. This stems from a number of factors, including imprecise knowledge of the satellite orbits and regional trends in phase delays due to the signal propagation through the ionosphere and troposphere. As a result, the long-wavelength component of the InSAR measurements is typically constrained to fit some axilliary (e.g., Global Navigation Satellite System, or GNSS) data, or model assumptions. We investigate to what extent InSAR data from the current generation of InSAR satellites - in particular, Sentinel-1A/B mission - are able to provide constraints on the long-wavelength tectonic deformation that are independent from those provided by the GNSS data. Toward this end, we processed a dataset from Southern California and compared the InSAR time series to the timeseries from the continuous GNSS network. We used the CANDIS method, a technique based on iterative common point stacking, to correct the InSAR data for tropospheric and ionospheric artifacts when calculating secular velocities and time series, and to isolate low-amplitude deformation signals in our study region. We computed the 3 orthogonal components of surface motion using overlapping InSAR tracks with different look geometries, together with an additional constraint provided by GPS measurements of the local azimuth of the horizontal velocity vector. The InSAR time series were computed using both filtered and unfiltered radar phase. The results show a good agreement with the independent GNSS data.
Broader Impacts Evaluation of seismic hazard is based primarily on historic seismicity
and long-term fault slip rates inferred from paleoseismic data.
Geodetic observations provide an important additional source of
information about contemporaneous accumulation of strain in the
seismogenic layer. UCERF3 model now incorporates estimates of fault
slip rates based on geodetic data. A major outstanding question is
whether geodetic observations can help identify areas of seismic
hazard that haven't been recognized based on available seismic and
geologic data. While mature faults such as the San Andreas fault by
and large have clear expression in geomorphology, young developing
faults and fault zones may be more difficult to recognize. Sentinel-1
InSAR data help us better understand a potential contribution of
geodetic observations to estimates of seismic hazard such as
UCERF. The performed analysis of space geodetic data helps improve our
understanding of the associated seismic hazard to populated areas in
Southern California. This project has provided training and support
for one graduate student (Zeyu Jin).
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