Pair Selection Optimization for InSAR Time Series Processing

Abstract

The ever-increasing amount of Synthetic Aperture Radar (SAR) data motivates the development of automatic processing chains to fully exploit the opportunities offered by these large databases. The Synthetic Aperture Radar Interferometry (InSAR) Mass processing Toolbox for Multidimensional time series is an optimized tool to automatically download SAR data, select the interferometric pairs, perform the interferometric mass processing, compute the geocoded deformation maps, invert and display the velocity maps and the 2D time series on a web page updated incrementally as soon as a new image is available. New challenges relate to data management and processing load. We address them through methodological improvements dedicated to optimizing the InSAR pair selection. The proposed algorithm narrows the classical selection based on the shortest temporal and spatial baselines thanks to a coherence proxy and balances the use of each image as Primary and Secondary images thanks to graph theory methods. We apply the processing to three volcanic areas characterized with different climate, vegetation, and deformation characteristics: the Virunga Volcanic Province (DR Congo), the Reunion Island (France), and the Domuyo and Laguna del Maule area (Chile-Argentina border). Compared to pair selection based solely on baseline criteria, this new tool produces similar velocity maps while reducing the total number of computed differential InSAR interferograms by up to 75%, which drastically reduces the computation time. The optimization also allows to reduce the influence of DEM errors and atmospheric phase screen, which increase the signal-to-noise ratio of the inverted displacement time series.