In this work we present a fully parallel and automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the effective and massive generation of Sentinel- 1 (S-1) Interferometric Wide Swath (IWS) displacement time-series and corresponding mean deformation velocity maps of very wide areas. The strategy chosen to implement such a parallel processing chain fully benefits from the Terrain Observation with Progressive Scans (TOPS) mode characterizing the IWS acquisitions of the S-1 constellation for systematic monitoring of large land and coastal areas. The TOPS mode consists of a series of bursts that can be considered as separate images to be independently processed. Such a data structure fosters the parallelization of the S-1 IWS interferometric data processing, which can be automatically carried out through the exploitation of both high-performance distributed computing infrastructures and efficient algorithms for tackling the huge data flow provided by the S-1 constellation. To demonstrate the capability of the presented S-1 P-SBAS processing chain to deal with the huge volume of data acquired by the S-1 constellation, we process a very extended dataset acquired over the Italian territory from which we compute the mean velocity maps and associated deformation time-series.
The Parallel SBAS-DInSAR Processing Chain for the Generation of National Scale Sentinel-1 Deformation Time-Series
C De Luca;M Bonano;F Casu;M Manunta;M Manzo;G Onorato;I Zinno;R Lanari
2018
Abstract
In this work we present a fully parallel and automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the effective and massive generation of Sentinel- 1 (S-1) Interferometric Wide Swath (IWS) displacement time-series and corresponding mean deformation velocity maps of very wide areas. The strategy chosen to implement such a parallel processing chain fully benefits from the Terrain Observation with Progressive Scans (TOPS) mode characterizing the IWS acquisitions of the S-1 constellation for systematic monitoring of large land and coastal areas. The TOPS mode consists of a series of bursts that can be considered as separate images to be independently processed. Such a data structure fosters the parallelization of the S-1 IWS interferometric data processing, which can be automatically carried out through the exploitation of both high-performance distributed computing infrastructures and efficient algorithms for tackling the huge data flow provided by the S-1 constellation. To demonstrate the capability of the presented S-1 P-SBAS processing chain to deal with the huge volume of data acquired by the S-1 constellation, we process a very extended dataset acquired over the Italian territory from which we compute the mean velocity maps and associated deformation time-series.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.