SBAS-DInSAR parallel processing for deformation time-series computation (Articolo in rivista)

Type
Label
  • SBAS-DInSAR parallel processing for deformation time-series computation (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/JSTARS.2014.2322671 (literal)
Alternative label
  • Casu F.; Elefante S.; Imperatore P.; Zinno I.; Manunta M.; De Luca C.; Lanari R. (2014)
    SBAS-DInSAR parallel processing for deformation time-series computation
    in IEEE journal of selected topics in applied earth observations and remote sensing (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Casu F.; Elefante S.; Imperatore P.; Zinno I.; Manunta M.; De Luca C.; Lanari R. (literal)
Pagina inizio
  • 3285 (literal)
Pagina fine
  • 3296 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84908006262&partnerID=q2rCbXpz (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 7 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 8 (literal)
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto Per il Rilevamento Elettromagnetico dell'Ambiente (IREA), Italian National Research Council (CNR), Napoli, 80124, Italy; Department of Electrical Engineering and Information Technology, University of Naples Federico II, Napoli, Italy (literal)
Titolo
  • SBAS-DInSAR parallel processing for deformation time-series computation (literal)
Abstract
  • The aim of this paper is to design a novel parallel computing solution for the processing chain implementing the Small BAseline Subset (SBAS) Differential SAR Interferometry (DInSAR) technique. The proposed parallel solution (P-SBAS) is based on a dual-level parallelization approach and encompasses combined parallelization strategies, which are fully discussed in this paper. Moreover, the main methodological aspects of the proposed approach and their implications are also addressed. Finally, an experimental analysis, aimed at quantitatively evaluating the computational efficiency of the implemented parallel prototype, with respect to appropriate metrics, has been carried out on real data; this analysis confirms the effectiveness of the proposed parallel computing solution. In the current scenario, characterized by huge SAR archives relevant to the present and future SAR missions, the P-SBAS processing chain can play a key role to effectively exploit these big data volumes for the comprehension of the surface deformation dynamics of large areas of Earth. (literal)
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