## 4 Ground Segment
### Data Products  
The EnMAP ground segment will distribute a series of data products with different processing levels as detailed in Table 3. In the first steps of the default processing chain, the acquired image files are complemented by auxiliary channel files (one for VNIR and one for SWIR) stored during imaging. These files are combined with refined orbit and attitude measurements, as well as sensor-specific spectral, radiometric and geometric calibration tables (see Figure 8, dotted lines) to generate internal Level 0 products, which are long-term archived. Next, standardized Earth observation products at several processing levels are created, termed Level 1B, Level 1C and Level 2A. Quality information is annotated at the end of each level. Level 0 processing (see Figure 8, dashed lines) comprises the following steps:  
1. Decompress image channel files, if files are (loss-less) compressed. 2. Check status, e.g., that values and standard deviations are in specified range of dark current measurements and determine dark signal information for each pixel. 3. Perform Level 1B processing for all channels. 4. Improve geometric accuracy by: 1. Coarsely registering (by affine transformation) the mono-chromatic VNIR channel closest in wavelength to the one of the reference image (RI) to be extracted from the Sentinel-2 global RI database. 2. Performing hierarchical intensity-based image matching with the RI, resulting in homologous points. 3. After a highly selective blunder detection and removal, three-dimensional ground control points are generated with a digital elevation model (DEM), which is intended to be extracted from the ASTER global DEM database. 4. Instrument mounting angles and attitude products are improved, and quality information is included. 5. Performing Level 1C processing for a subset of channels. Figure 8: Scheme of the processing chain for the generation of data products at the EnMAP ground segment. 5. Performing pixel classification, e.g., land-water and cloud-haze-cirrus-clear, and determining the visibility map (based on dark pixels for land) allowing the estimation of the aerosol optical thickness. 6. Generating quick looks and quality data with 8 bits. 7. Long-term archiving of the Level 0 product for all tiles. Level 1B processing comprises the following steps to correct for systematic effects and convert the image data into physical at-sensor radiance values:  
1. Flag dead pixels based on calibration tables, saturated (hot) and no-response (cold) pixels based on image data, as well as the first and last 12 pixels of each frame, which are dark current measurements used for quality control. 2. Correction for non-linearities, dark signal and response non-uniformity based on look-up tables. 3. Perform gain matching for the VNIR detector, since the low or high gain is automatically selected. 4. Correction for stray light for the spectral and spatial direction based on correction matrices. 5. Perform spectral referencing, through which center wavelength and the full width at half maximum are assigned to spectral channels, and radiometric referencing in order to convert 32-bit floating point values to 16-bit integers for storage. 6. Final data screening for striping and other remaining artifacts, generation of data quality flags and metadata. Level 1C processing converts Level 1B products into map-accurate forms. The map projection and resampling technique can be chosen by the user. Finally, Level 2A processing converts Level 1C products to surface reflectances, where separate algorithms for land and water applications are employed. The correction mode can be chosen by the user, namely land-water, land, water. Atmospheric correction involves the generation of sun glitter maps for water surfaces by identification of specular reflections, the detection (and correction) of haze and cirrus, the estimation of aerosol optical thickness and columnar water vapor and the retrieval of surface reflectance after adjacency correction.