Tree species mapping with airborne hyper-spectral MIVIS data: the Ticino Park study case (Articolo in rivista)

Type
Label
  • Tree species mapping with airborne hyper-spectral MIVIS data: the Ticino Park study case (Articolo in rivista) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1080/01431160600928542 (literal)
Alternative label
  • Boschetti, M.; Boschetti, L.; Oliveri, S.; Casati, L.; Canova, I. (2007)
    Tree species mapping with airborne hyper-spectral MIVIS data: the Ticino Park study case
    in International journal of remote sensing (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Boschetti, M.; Boschetti, L.; Oliveri, S.; Casati, L.; Canova, I. (literal)
Pagina inizio
  • 1251 (literal)
Pagina fine
  • 1261 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 28 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 6 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Boschetti, M.: CNR-IREA Boschetti, L.: University of Maryland, Department of Geography Oliveri, S.: CRASL, Centro di Ricerche per l'Ambiente e lo Sviluppo sostenibile della Lombardia Casati, L.; Canova, I.: Parco Lombardo della Valle del Ticino, (literal)
Titolo
  • Tree species mapping with airborne hyper-spectral MIVIS data: the Ticino Park study case (literal)
Abstract
  • The present work describes the procedure, which was studied for mapping the spatial distribution of tree forest communities in the Ticino Park located in Northern Italy. Ten overlapping airborne runs of the Multispectral Infrared Visible Imaging Spectrometer (MIVIS) were acquired to cover the entire park extent (920 km(2)). An integrated supervised classification procedure was developed using band ratios in the red edge portion ( REP) of the spectrum and training collected by field survey and visual interpretation. Validation performed with a robust random stratified sampling scheme and taking into account the unequal distribution of the classes showed that, on large-scale application, high-resolution remotely sensed images can generate, in a cost-effective manner, accurate ( overall accuracy 75%) local-scale thematic products. (literal)
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