Big DInSAR data processing through the P-SBAS algorithm

In the present radar remote sensing scenario, the huge availability of SAR data acquired by a number of satellite constellations is a key point for investigating Earth´s surface at large scale. In particular, techniques as Differential SAR Interferometry (DInSAR) could strongly benefit from such data availability for measuring ground displacement at global scale. However, to efficiently and effectively exploit such amount of Big DInSAR Data, the development of new algorithms and techniques as well as the use of appropriate High Performance Computing infrastructure is becoming mandatory. In this work we present a number of case studies based on the recently proposed Parallel Small BAseline Subset (P-SBAS) DInSAR algorithm, that allows generating surface displacement maps in automatic and unsupervised way, aimed at providing effective solutions to the increased DInSAR data volume processing.