Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis (Contributo in atti di convegno)

Type
Label
  • Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis (Contributo in atti di convegno) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/CloudCom.2014.96 (literal)
Alternative label
  • Mossucca, L. 1; Zinno, I. 2; Elefante, S. 2; Luca, C.De 2,3; Casola, V. 3; Terzo, O. 1; Casu, F. 2; Lanari, R. 2 (2014)
    Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis
    in IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom), 2014, Singapore, 15-18 Dec. 2014
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Mossucca, L. 1; Zinno, I. 2; Elefante, S. 2; Luca, C.De 2,3; Casola, V. 3; Terzo, O. 1; Casu, F. 2; Lanari, R. 2 (literal)
Pagina inizio
  • 835 (literal)
Pagina fine
  • 840 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1) Istituto Superiore Mario Boella (ISMB), Torino, Italy 2) IREA-CNR, Napoli, Italy 3) UNINA - DIETI, Napoli, Italy (literal)
Titolo
  • Cloud Platform for Scientific Advances in Earth Surface Interferometric SAR Image Analysis (literal)
Abstract
  • The advanced Differential SAR Interferometers (DInSAR) methodologies are widely used for the investigation of Earth's surface deformation phenomena. In particular, the advanced DInSAR approach referred to as Small Baseline Subset (SBAS) technique is able to produce deformation velocity maps and the corresponding displacement time-series from a temporal sequence of space borne SAR acquisitions. Considering the already huge SAR data archives as well the upcoming massive data flow coming from the SENTINEL satellite constellation, cloud computing can be a valid solution to carry out DInSAR analyses thanks to its scalability and flexibility features. In this paper, the focus is given on the migration of the whole parallel version of the SBAS technique, namely P-SBAS, to a cloud environment by taking into account different parameters that influence processing time. Experimental tests that have been performed using both private and public cloud are also presented. (literal)
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