Estimation of Ocean Tidal Loading Deformation From Time-Series InSAR Based on Blind Source Signal Separation and Physical Modeling

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Abstract

Estimating coastal ground deformation caused by ocean tidal loading (OTL) through time-series interferometric synthetic aperture radar (InSAR) techniques is challenging but achievable. Based on the two-dimensional wavelet decomposition method to extract spatial long-wavelength interferometric phases, the OTL deformation, residual orbital error, and atmospheric delay error hidden in long-wavelength phases can be isolated by independent component analysis. The ground OTL deformation in time-series InSAR phases is then accurately estimated using tidal harmonic functions. Experiments conducted with Sentinel-1 measurements in coastal areas reveal the following findings. Leveraging the blind source separation method allows for the effective extraction of high spatial resolution and large-scale ground OTL deformation correlation signals from the time-series InSAR phase. The differences between parameter values of main constituents estimated by the modeled InSAR ground OTL deformation and the FES2014b global tidal model range from 1.1% to 5.8%. Additionally, the difference in their predicted OTL deformation values is within the range of 0.9-4.9 mm. Compared to the FES2014b model correction method, the proposed approach removes OTL deformation from the time-series InSAR and results in a 26.1% reduction in the residual standard deviation value of ground deformation, which leads to a significant enhancement in the accuracy of ground deformation acquired for coastal areas. This work provides a novel approach to the theoretical research on OTL deformations, contributing to the refinement of InSAR ground deformation monitoring accuracy in coastal areas.

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APA

Peng, W., Zhou, J., Hu, W., Xing, X., Zhu, J., & Liu, B. (2024). Estimation of Ocean Tidal Loading Deformation From Time-Series InSAR Based on Blind Source Signal Separation and Physical Modeling. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 17327–17336. https://doi.org/10.1109/JSTARS.2024.3464736

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