Multisensoral approach for the determination of plant parameters of corn

Procedures to determine plant parameters from optical remote sensing data are presented using corn as an example. These procedures are applied and verified on a multisensoral and multitemporal dataset acquired between 1989 and 1991 in the test area Freiburg in the Upper Rhine valley. The dataset consists of airborne hyperspectral data from AVIRIS, CASI and GER, as well as from spaceborne multispectral TM-data. Semiempirical approaches using different spectral ranges are chosen to determine regressions between remote sensing data and plant parameters. For the determination of the leaf area index, the arNDVI (NDVI based on absolute reflectance values) is used. A strong correlation between the wavelength position of-the red edge and the vegetation height as well as the biomass of corn is found. A method for modelling the water absorption features in plant spectra to identify the amount of liquid water was developed. It is shown, that this method applied to AVIRIS-spectra of corn can determine the water content of plants