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*Corresponding author e-mail: jelinekzdenek@tf.czu.cz **This work was supported by Internal Grant Agency of the Faculty of Engineering, CZU Prague, internal grant number 31180/1312/3118. The support from project MZE-RO418 is also acknowledged (2018-2022). A b s t r a c t. The influence of climate and topography on crop condition and yield estimates is most effectively monitored by non-invasive satellite imagery. This paper evaluates the efficiency of free-access Sentinel 2 and Landsat 5, 7 and 8 satellite images scanned by different sensors on wheat growth and yield prediction. Five winter and spring wheat cultivars were grown between 2005 and 2017 in a relatively small 11.5 ha field with a 6% slope. The normalized difference vegetation index was derived from the satellite images acquired for later growth phases of the wheat crops (Biologische Bundesanstalt, Bundessorenamt and Chemical industry 55 – 70) and then compared with the topography wetness index, crop yields and yield frequency maps. The results showed a better correlation of data obtained over one day (R = 0.876) than data with a one-day delay (R = 0.689) using the Sentinel 2 B8 band instead of the B8A band for the near-infrared part of electromagnetic spectrum in the normalized difference vegetation index calculation. K e y w o r d s: satellite sensors, agriculture, satellite imagery, wheat varieties

Landsat and Sentinel-2 images as a tool for the effective estimation of winter and spring cultivar growth and yield prediction in the Czech Republic