The Normalized Vegetation Difference Index (NDVI) as a measure of crop status has a number of limitations. When plant canopies are very dense and vigorous, the NDVI tends to saturate, i.e. differences in vegetation status under these kinds of conditions can hardly be distinguished. When plant canopies are light and the soil background strongly influences the spectral signal the NDVI is unsuitable to characterize the condition of the plants. The NDVI tends to mix structural parameters (like LAI and biomass) of the plants with their chlorophyll status, which makes it difficult to derive reliable information about just one of those factors with a high level of certainty. RapidEye is offering map products based on data from its 5 satellites that have a number of advantages in relation to these NDVI related weaknesses. Maps showing the ground cover, i.e. the fraction of the surface area covered with green vegetation, allow for a better characterization of crops when the canopy is still light since the spectral effect of the spoil background is compensated for in the production process. They also allow for a better differentiation of structural parameters in heavy crops than NDVI maps. RapidEye data have a red-edge spectral band that is more sensitive to the chlorophyll content of a canopy than the blue, green or red bands of most other image data sources. Using this red-edge band, RapidEye produces chlorophyll maps that show relative differences from low to high in chlorophyll content per unit surface area within fields. Farmers, agronomists and crop consultants use chlorophyll and ground cover maps to assess the nutrition or health status of crops, to create management zones and to generate prescription maps.