Estimating nutrient uptake of grasslands by assimilating remote sensing data in growth models, a first approach

Kurzfassung

The possibility will be explored to use a growth prediction model in order to get a clearer understanding of the nutrient uptake by vegetation within differently managed grasslands. A better insight in nutrient fluxes is required for estimating the influence of the different types of grassland use on the water quality of Lake Waging-Taching in the foreland of the Bavarian Alps, Germany. It will be tried to enhance the predictive power of the growth model LINGRA by calibrating it with leaf area index (LAI) values retrieved from multi- and hyperspectral imagery recorded at three time steps during the growing season of 2003. In a first step, LAI, together with other biophysical parameters such as leaf angle distribution and chlorophyll, will be retrieved from the atmospherically corrected imagery by the inversion of the leaf/canopy reflectance model PROSAIL. Ground measurements on three fields of dry biomass, canopy water content, specific leaf weight and soil reflection will be used to fix these parameters during the PROSAIL inversion so that the model is optimized for LAI estimates. After a validation with ground measurements, the LAI values will be used to update the LAI values as simulated by LINGRA. At this moment no concrete results can be presented yet.