Spectroscopy and hyperspectral imagery for monitoring summer barley

Abstract

The potential of field spectroscopy is shown by the quantitative assessment of summer barley canopy properties. A data set was acquired, comprising top of canopy reflectance (0.4-2.4m) and the corresponding canopy parameters of summer barley stands for two phenological stages. Canopy variables (leaf area index, canopy chlorophyll, water, and fresh matter contents) were predicted by partial least squares regression (PLSR) from field spectra resampled to HyMap spectral resolution with very high accuracy (r(2) (cv)>0.88). PLSR models obtained from field spectra were applied to HyMap data to allow spatial prediction of summer barley canopy properties. Subsequently, to assess accuracy of the spatially distributed estimates, predictions obtained from the image data were validated with reference to the vegetation samples taken in the field. The predicted values reflect the spatial conditions of the investigated plot. The results indicate the potential of this method as a quick screening tool for spatial assessment of canopy variables.