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Inhalt:
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We describe a study using the ASIA-Eagle hyperspectral sensor to measure the spectral response of spring barley over an entire climate-controlled growing season and correlate those results with the results of 25 biophysical and biochemical parameters. The spectrum of each hyperspectral image was used to calculate a range of vegetation indices (VIs) that have been recorded in the literature. Furthermore, all combinations of the 252 spectral bands were tested to calculate a range of difference vegetation indices (VIs(xy)) and reflectance value indices (R(x)) at the central wavelength (x nm) of each band (R(x)). For all three index types we examined the relationship with the vegetation variables measured on the ground by using a cross-validation procedure. The relationship between the estimated and the measured canopy chlorophyll content (CCC) was R2CV ≤ 0.65 (CV, covariance of variation). An R2CV ≥ 0.65 was obtained when modelling leaf area index (LAI), chlorophyll content (Chl-SPAD) as well as leaf gravimetric water content (GWC). The prediction of Chl-SPAD with reflectance VIs leads to greater prediction accuracy compared with published VIs as well as difference VIs. Based on the literature, we used the DI1 vegetation index for extracting vegetation variables such as LAI and GWC. However, because of overlap effects, an explicit assignment of the spectral response to a particular vegetation parameter was not possible. The ascertained subtraction VIy = (565–779) nm also shows very good prediction accuracy compared with LAI. The investigated overlap effects for the published VIs did not result in an explicit responsiveness of the spectral response to the measured vegetation parameters. No index shows an explicit spectral signal for a single vegetation parameter. The optimisation tests show that when compared with univariate techniques, multivariate regressions improved the prediction accuracy of LAI, Chl, and CCC. |
Cottbus, Brandenburgische Technische Universität Cottbus - Senftenberg Universitätsbibliothek - Fernleihe - <DE-634>
