*2.3. Satellite Data*

Satellite Sentinel-2 (2A and 2B) images of Level-1C with a spatial resolution of 10 to 20 m in the range of visible and near-infrared (NIR—band 8 at central wavelength 833 nm) light were downloaded from the Copernicus Open Access Hub [20]. Level-1C processing includes radiometric and geometric corrections, namely ortho-rectification and spatial registration, on a global reference system with a sub-pixel accuracy. Then, the acquired Level 1C products were subjected to atmospheric correction using the Dark Object Subtraction (DOS1) method in Semi-Automatic Classification Plugin documentation (SCP), developed by Luca Congedo (2016) [21].

Vegetation indices were derived for the representative soil and plant sampling points established within fields and imported together with the coordinates of these points. Then, they were compiled into tables and subjected to regression analyses. Depending on the location, despite the revisit time of about 5 days, it was only possible to acquire cloudless satellite images during the intensive growth of cereals in spring and early summer for 4–6 dates (Table 2).


**Table 2.** Dates for which satellite-based vegetation indices were derived from Sentinel images for three locations and two seasons.
