A vegetation classification scheme validated by model simulations
P. Ferrazzoli, Leila Guerriero, Giovanni Schiavon
Abstract
P. Ferrazzoli, Leila Guerriero, Giovanni Schiavon
Abstract
The capability of multifrequency polarimetric SAR to discriminate among nine vegetation classes is demonstrated using both experimental data and model simulations. The experimental data were collected by the multifrequency polarimetric SAR at the Dutch Flevoland site and the Italian Montespertoli site. Simulations are carried out using the vegetation model developed at Tor Vergata University.
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The capability of multifrequency polarimetric SAR to discriminate among nine vegetation classes is demonstrated using both experimental data and model simulations. The experimental data were collected by the multifrequency polarimetric SAR at the Dutch Flevoland site and the Italian Montespertoli site. Simulations are carried out using the vegetation model developed at Tor Vergata University.
Key concepts: Vegetation (pathology), Remote sensing, Polarimetry, Synthetic aperture radar, Vegetation classification, Environmental science, Computer science, Geology