Estimation of leaf area index of Beta vulgaris L. based on optical remote sensing data

Remote sensing and vegetation indices can be used to characterize the canopy of crops with a non-destructive method on a large scale. Leaf area formation of sugar beet in early summer is the most important variable for crop growth models. This study aimed at estimating whether differences in leaf area development of sugar beet resulting from different agronomic practices can be determined with remote sensing. The relationship between the normalized difference vegetation index (NDVI) and leaf area index (LAI) during the season and yield of the storage root in autumn was studied in six field trials in 2001 and nine field trials in 2002. The vegetation index NDVI gave a good impression of differences in leaf development of sugar beet in early summer. LAI increased with increasing NDVI up to an NDVI of 0.65. Above that the NDVI did not respond as distinctly to treatments as the LAI. An exponential function was developed to calculate sugar beet LAI from NDVI, so that remote sensing data can be used as input variable for crop growth models. The yield of the storage root in autumn did not show any relationship to LAI or NDVI during the season, regardless of whether it was measured in June or September. Therefore, it seems to be necessary to combine NDVI data with crop growth models to forecast a potential sugar beet yield in autumn. For this purpose the formula presented is a valuable tool.