In the last decades Earth Observation (EO) from space has very fast evolved through the development of remote sensing data-acquisition systems, contributing to the creation of a Big EO Data scenario. In this work, we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing Sentinel-1 (S1) Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation maps and corresponding displacement time series in an efficient, automatic and systematic way. The presented approach has been used to perform a national-scale DInSAR analysis over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Details on the cloud infrastructure and processing times will be presented.
Large Spatial Scale Ground Displacement Mapping through the P-SBAS Processing of Sentinel-1 Data on a Cloud Computing Environment
De Luca C;Bonano M;Casu F;Lanari R;Manunta M;Manzo M;Zinno I
2017
Abstract
In the last decades Earth Observation (EO) from space has very fast evolved through the development of remote sensing data-acquisition systems, contributing to the creation of a Big EO Data scenario. In this work, we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing Sentinel-1 (S1) Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation maps and corresponding displacement time series in an efficient, automatic and systematic way. The presented approach has been used to perform a national-scale DInSAR analysis over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Details on the cloud infrastructure and processing times will be presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.