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.
2018
Istituto di Metodologie per l'Analisi Ambientale - IMAA
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
sentinel-1
InSAR
P-SBAS
deformation time-series
cloud computing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/356273
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