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Integration of InSAR and GPS data for 3-dimensional crustal deformation mapping

Zhen Liu, Zheng-Kang Shen, Cunren Liang, & Paul Lundgren

Published August 15, 2017, SCEC Contribution #7766, 2017 SCEC Annual Meeting Poster #104

GPS and InSAR are complementary to each other for crustal deformation mapping, with the former offering discrete high-fidelity 3-dimensional (3-D) point positioning while the latter providing 2-D dense spatial coverage of deformation measured along satellite-to-ground looking direction. Integration of the two data sets can provide 3-D deformation measurements with the accuracy and spatial resolution not available through either kind of data. We develop an algorithm to integrate the two data sets for the production of 3-D crustal motion map. In the algorithm point-based discrete GPS measurements are first interpolated to produce continuous 3-D vector map at chosen grids covered by the InSAR data. The interpolation takes into account of GPS station distance, network density and configuration for data weighting [Shen et al., 2015]. A Gaussian distance weighting function and a Voronoi cell spatial weighting function are used in the interpolation. The amount of weighting and degree of smoothing can be spatially variable and optimally determined based on in situ data strength. The approach can effectively smooth out the incoherencies in discretized GPS velocity data. At the locations where both InSAR and interpolated GPS data are available, optimal 3-D components are solved for using a weighted least square method. The InSAR data are weighted by their LOS uncertainties. The GPS interpolated data are weighted by their re-estimated uncertainties to ensure the estimates reflect the in situ data strength and not biased by uneven degree of smoothing. Including InSAR data from both ascending and descending viewing geometry, if available, provides improved constraint on the 3-D deformation field. We apply the algorithm to selected regions in southern California and shows that the GPS and InSAR data are generally consistent for the horizontal velocities at sub-millimeter level. The vertical velocity field is better determined than using GPS data only, showing hydrology related deformation signals as well as deformation signals related to earthquake and tectonic processes. In addition, we present initial results of crustal deformation using ongoing satellite sensors such as Sentinel-1 and ALOS-2. We show that the new satellite SAR data provide great potential for accurate measurements of crustal motion induced by both tectonic and non-tectonic sources.

Liu, Z., Shen, Z., Liang, C., & Lundgren, P. (2017, 08). Integration of InSAR and GPS data for 3-dimensional crustal deformation mapping. Poster Presentation at 2017 SCEC Annual Meeting.

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Tectonic Geodesy