In order to demonstrate the capability of the implemented Cloud-based processing chain to deal with massive amount of data, we focus our analysis on the whole Italian territory by processing all the available data acquired both from ascending and descending orbits within the October 2014 March 2017 time interval. As final result we combine the retrieved LOS displacements in order to compute the mean velocity maps and time-series of the vertical and East-West surface deformation components.

In this work we implement a completely automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) deformation mean velocity maps and time-series of very wide areas, implemented within the Amazon Web Services (AWS) Elastic Cloud Compute environment. Our processing chain consists of the initial data query to the S-1 archive that we created on the AWS S3 storage, then the data transfer to the AWS computing nodes, the data processing and, finally, the transfer of the obtained interferometric results back to the original S3 storage.

SURFACE DEFORMATION MAPPING OF ITALY THROUGH THE P-SBAS DINSAR PROCESSING OF SENTINEL-1 DATA IN A CLOUD COMPUTING ENVIRONMENT

Zinno I;Bonano M;Buonanno S;Casu F;De Luca C;Lanari R;Manzo M;Manunta M;Zeni G
2018

Abstract

In this work we implement a completely automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) deformation mean velocity maps and time-series of very wide areas, implemented within the Amazon Web Services (AWS) Elastic Cloud Compute environment. Our processing chain consists of the initial data query to the S-1 archive that we created on the AWS S3 storage, then the data transfer to the AWS computing nodes, the data processing and, finally, the transfer of the obtained interferometric results back to the original S3 storage.
2018
Istituto di Metodologie per l'Analisi Ambientale - IMAA
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
In order to demonstrate the capability of the implemented Cloud-based processing chain to deal with massive amount of data, we focus our analysis on the whole Italian territory by processing all the available data acquired both from ascending and descending orbits within the October 2014 March 2017 time interval. As final result we combine the retrieved LOS displacements in order to compute the mean velocity maps and time-series of the vertical and East-West surface deformation components.
Sentinel-1
DInSAR
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/20.500.14243/356265
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