C-Band SAR Data for Mapping Crops Dominated by Surface or Volume Scattering (Articolo in rivista)

Type
Label
  • C-Band SAR Data for Mapping Crops Dominated by Surface or Volume Scattering (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/LGRS.2013.2263034 (literal)
Alternative label
  • Satalino, Giuseppe; Balenzano, Anna; Mattia, Francesco; Davidson, Malcolm W. J. (2014)
    C-Band SAR Data for Mapping Crops Dominated by Surface or Volume Scattering
    in IEEE geoscience and remote sensing letters (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Satalino, Giuseppe; Balenzano, Anna; Mattia, Francesco; Davidson, Malcolm W. J. (literal)
Pagina inizio
  • 384 (literal)
Pagina fine
  • 388 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • Journal Category: Electrical and Electronic Engineering; Quartile: Q1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 11 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 5 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 2 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Consiglio Nazionale delle Ricerche (CNR); European Space Agency (literal)
Titolo
  • C-Band SAR Data for Mapping Crops Dominated by Surface or Volume Scattering (literal)
Abstract
  • In this letter, a C-band SAR classification algorithm mapping agricultural crops dominated by surface or volume scattering is derived and assessed. The algorithm is an adaptive thresholding method based on the iterative solution of the Kittler-Illingworth method applied to exploit temporal series of cross-polarized SAR data. The performances of the classification algorithm have been assessed on ENVISAT ASAR data acquired over Gormin (Germany) during the AgriSAR'06 campaign and on RADARSAT-2 data acquired over Flevoland (The Netherlands) and Indian Head (Canada) during the ESA AgriSAR'09 campaign. The results indicate that the classification method improves the accuracy with respect to the one obtained by the threshold method based on a constant value, unless the data distributions are mono-modal. The algorithm is fast and robust versus changes of site location and it is expected to achieve an average overall accuracy better than 80%. (literal)
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