A Multipixel Time Series Analysis Method Accounting for Ground Motion, Atmospheric Noise, and Orbital Errors. Issue 4 (22nd February 2018) - Jolivet, R.; Simons, M.
Abstract: Interferometric synthetic aperture radar time series methods aim to reconstruct time‐dependent ground displacements over large areas from sets of interferograms in order to detect transient, periodic, or small‐amplitude deformation. Because of computational limitations, most existing methods consider each pixel independently, ignoring important spatial covariances between observations. We describe a framework to reconstruct time series of ground deformation while considering all pixels simultaneously, allowing us to account for spatial covariances, imprecise orbits, and residual atmospheric perturbations. We describe spatial covariances by an exponential decay function dependent of pixel‐to‐pixel distance. We approximate the impact of imprecise orbit information and residual long‐wavelength atmosphere as a low‐order polynomial function. Tests on synthetic data illustrate the importance of incorporating full covariances between pixels in order to avoid biased parameter reconstruction. An example of application to the northern Chilean subduction zone highlights the potential of this method. Key Points: A new inversion method for InSAR time series that considers all pixels simultaneously Incorporates a distance‐dependent covariance between pixels to describe atmospheric noise Allows reconstruction of displacement rates from low‐coherence data sets