SCEC Award Number 18005 View PDF
Proposal Category Individual Proposal (Data Gathering and Products)
Proposal Title Complementing CGM with Sentinel-1 InSAR data
Investigator(s)
Name Organization
Yuri Fialko University of California, San Diego
Other Participants Ekaterina Tymofyeyeva
SCEC Priorities 1a, 2a, 3a SCEC Groups Geodesy
Report Due Date 03/15/2019 Date Report Submitted 05/14/2019
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. Over the time span of SCEC5, there will be a dramatic increase in the amount of InSAR data thanks to the European Space Agency (ESA) mission Sentinel-1. Sentinel-1 mission will provide several key improvements over the existing InSAR data sets, 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. Over the last year we have set up a system for routine systematic processing of all Sentinel-1 data from Southern California. We also started generating higher-level products for integration into CGM.
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 the 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 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 InSAR measurements is typically constrained to fit some axilliary (e.g., Global Navigation Satellite System, or GNSS) data, or model assumptions. We investigated to what extent InSAR data from the current generation of InSAR satellites - in particular, the Sentinel-1 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 used in the CGM exercise (Los Angeles/Mojave area) to generate InSAR time series. We used 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 the study region. We compared data collected by Sentinel-1 between 2014-2019 with continuous GPS measurements, and computed the average line of sight (LOS) displacements over the respective epoch. The two data sets showed a reasonable agreement, indicating that the InSAR data can reliably measure deformation signals at wavelengths on the order of 100 km. Data from overlapping InSAR tracks with different look geometries can be combined with information on the local azimuth of the horizontal velocity vector (e.g., from the continuous GPS measurements) to obtain the 3 orthogonal components of surface motion.
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 will help us better understand a potential contribution of
geodetic observations to estimates of seismic hazard such as
UCERF. The proposed collection and analysis of space geodetic data
will 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.
Exemplary Figure Fig 2 or 3
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