GNGTS 2022 - Atti del 40° Convegno Nazionale

GNGTS 2022 Sessione 1.3 129 making it possible to compare the time series with other GPS in the area of interest (Fig. 1). The GPS time series are provided by the Nevada Geodetic Laboratory. We analyzed the time series of displacement using the correlation coefficients between correction/residuals and topography on SAR points recovered in an area of 1 degree longitude by 0,5 degrees of latitude (Fig. 2 and 3). We found that the CSS method is good at reducing scatter in the time series of displacement (Fig.1A) but in the residuals (Fig. 3) there is some remaining effect related to the topography contribution which manifests itself as a long-term deviation from the GPS. GACOS corrects most of the topography contribution (Fig. 2) but it is less effective in the reduction of the short period (Fig. 1B and 3). Instead, the application of CSS after the correction of GACOS results in a curve that finds good correspondence with the GPS (Fig. 1B), having reduced both the high frequencies and the long-term deviation. References Berardino P., Fornaro G., Lanar, R., Sansosti E.; 2002: A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on geoscience and remote sensing, 40(11), 2375-2383. Li Z., Duan M., Cao Y., Mu M., He X., Wei J.; 2022: Mitigation of time-series InSAR turbulent atmospheric phase noise: A review . Geodesy and Geodynamics. Sandwell D., Mellors R., Tong X., Wei M., Wessel P.; 2011: Open radar interferometry software for mapping surface deformation , Eos Trans. AGU, 92(28), doi:10.1029/2011EO280002. Sandwell D., Mellors R., Tong X., Xu X., Wei M., Wessel P.; 2016: GMTSAR: An InSAR Processing System Based on Generic Mapping Tools. UC San Diego: Scripps Institution of Oceanography Tymofyeyeva E. and Fialko Y.; 2015: Mitigation of atmospheric phase delays in InSAR data, with application to the eastern California shear zone. Journal of Geophysical Research: Solid Earth, 120, 5952–5963. https://doi. org/10.1002/2015JB011886 Yu C., Li Z., Penna N. T., Crippa P.; 2018a: Generic atmospheric correction model for Interferometric Synthetic Aperture Radar observations. Journal of Geophysical Research: Solid Earth, 123(10), 9202-9222. Yu C., Li Z., Penna N. T.; 2018b: Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model. Remote Sensing of Environment, 204, 109-121. Yu C., Penna N. T., Li Z.; 2017: Generation of real‐time mode high‐resolution water vapor fields fromGPS observations. Journal of Geophysical Research: Atmospheres, 122(3), 2008-2025.