Characterization of snow cover areas by change detection applied to COSMO-SkyMed images (Contributo in atti di convegno)

Type
Label
  • Characterization of snow cover areas by change detection applied to COSMO-SkyMed images (Contributo in atti di convegno) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Alternative label
  • Pettinato S.; Santi E.; Paloscia S.; Aiazzi B.; Garzelli A. (2013)
    Characterization of snow cover areas by change detection applied to COSMO-SkyMed images
    in PIERS 2013, Progress In Electromagnetics Research Symposium, Stockholm, Sweden, 12-15 Aug. 2013
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Pettinato S.; Santi E.; Paloscia S.; Aiazzi B.; Garzelli A. (literal)
Pagina inizio
  • 531 (literal)
Pagina fine
  • 535 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84884740989&partnerID=q2rCbXpz (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Proceedings of PIERS 2013, Progress In Electromagnetics Research Symposium (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 5 (literal)
Note
  • Scopu (literal)
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Institute of Applied Physics, National Research Council, Firenze, Italy; Department of Information Engineering and Mathematical Sciences, University of Siena, Siena, Italy (literal)
Titolo
  • Characterization of snow cover areas by change detection applied to COSMO-SkyMed images (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-9341-4226-4 (literal)
Abstract
  • An experimental study on the characterization of snow cover areas from multitemporal COSMO-SkyMed (CSK) images is presented. Himage and PingPong data in Stripmap acquisition mode from the CSK constellation are processed by applying two alternative approaches: a classical threshold method and an effective change-detection method. The proposed information-theoretic approach to change detection provides very promising results on multitemporal 1-look SAR images at very high spatial resolution. (literal)
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