Salt marsh vegetation radiometry: Data analysis and scaling

This paper aims to determine the optimal procedure for classifying salt marsh vegetation from hyperspectral data and to establish relationships between airborne and ground measurement properties. The study is carried out on data collected in the Lagoon of Venice (Italy). Spectral angle mapping proves to be a reliable classification procedure, and spectral differentiation is seen to improve separability of vegetation types. Further, scaling relationships are derived to link the value of the variance of data aggregated at different scales, allowing the determination of data variability at coarse resolution on the basis of ground measurements. The comparison between the theoretical, up-scaled, values of standard deviation and those computed from remote sensing data shows a good agreement supporting the derived relations. Finally, a scaling relationship is established for spectral angles, which may be useful in determining an optimal threshold angle from ground data.