A directional data set of bare soil and Alfalfa acquired using the Field GOniometer System (FIGOS) during the DAIS Experiment 1999 (DAISEX'99) campaign is preprocessed and analyzed for its quality. Two different normalization methods to derive anisotropy factors, i.e., dividing by nadir reflectance and by spectral albedo, are tested and discussed. The effect of varying reflectances on the prediction of vegetation variables due to changing Sun and viewing geometries is demonstrated by the derivation of the weighted difference vegetation index (WDVI) for Alfalfa multiangular data and proves to be significant. The results described in this work are a contribution to the preprocessing and validation of ground-based directional remote sensing data, with a special emphasis on the spectral component and the diurnal dynamics of multiangular ground-based observations of soil and an Alfalfa canopy. The study is a step towards the generation of BRDF databases for the validation and calibration of air- and spaceborne remote sensing data.
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