This contribution evaluates the accuracy of salt-marsh vegetation classifications obtained from remote sensing observations with specific application to the Lagoon of Venice (Italy). Observation and classification schemes are evaluated on the basis of several applications including the use of 3 airborne hyperspectral sensors (ROSIS; CASI; MIVIS) and 2 satellite multispectral sensors (IKONOS; QuickBird). We show that spatiallydetailed and quantitatively reliable vegetation maps may be derived from remote sensing in tidal environments through unsupervised and supervised algorithms. Statistical analyses applied to the vegetation maps obtained allowed the quantitative characterization of vegetation biodiversity distributions.
Belluco, E., Camuffo, M., Ferrari, S., Modenese, L., Silvestri, S., Marani, A., et al. (2006). Remote sensing of salt-marsh ecogeomorphology.
Remote sensing of salt-marsh ecogeomorphology
Silvestri S.;
2006
Abstract
This contribution evaluates the accuracy of salt-marsh vegetation classifications obtained from remote sensing observations with specific application to the Lagoon of Venice (Italy). Observation and classification schemes are evaluated on the basis of several applications including the use of 3 airborne hyperspectral sensors (ROSIS; CASI; MIVIS) and 2 satellite multispectral sensors (IKONOS; QuickBird). We show that spatiallydetailed and quantitatively reliable vegetation maps may be derived from remote sensing in tidal environments through unsupervised and supervised algorithms. Statistical analyses applied to the vegetation maps obtained allowed the quantitative characterization of vegetation biodiversity distributions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
