Retrieval of vegetation fluorescence from ground-based and airborne high resolution measurements

Sun-induced chlorophyll fluorescence (Fs) is a weak signal over imposed to the radiance reflected by vegetation. Several algorithms are currently available in literature to retrieve fluorescence from high spectral resolution data. This contribution shows a comparison of different Fs retrieval techniques exploiting: i) ground-based measurements at fine and ultrafine spectral resolution; ii) airborne hyperspectral imagery. Performance analysis of the different methods is done analyzing the coefficient of variation of diurnal measurements collected over a fixed sampled area. Fraunhofer Line Depth (FLD) and Spectral Fitting Methods (SFM) are evaluated using both fine and ultrafine resolution data. Results show that ultrafine resolution data coupled to advanced retrieval techniques, like SFM, strongly reduce errors in Fs. The Fs values calculated from hyperspectral airborne data are in agreement with ground measurements.