Mapping Ground Deformation by Radar Interferometry Based on Permanent-scatterer Network: Algorithm and Testing Results

The full operational capability of synthetic aperture radar (SAR) interferometry in deformation monitoring has not been achieved yet due to the negative influences of spatio-temporal decorrelation and atmospheric delay. With the use of time series of SAR images, deformation extraction can be however improved by only tracking some objects with steady radar reflectivity, generally referred to as permanent scatterer (PS). This paper presents an attempt to explore a PS-networking approach to isolate deformations from other effects such as atmospheric signals and topographic errors. The deforming process in time and space is modelled and estimated with a very strong network which is formed by connecting adjacent PSs. The linear deformations and topographic errors are estimated by optimizing objective functions and by adjusting the network via weighted least squares (LS) solution. The time series of nonlinear deformations and atmospheric signals are computed by singular value decomposition (SVD) and empirical mode decomposition (EMD). To validate the algorithm, 39 ERS C-band SAR images acquired over Phoenix in Arizona (USA) from 1992 to 2002 are used to detect land subsidence caused by the excessive groundwater withdrawal. * Corresponding author.