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
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Department of Machinery Utilization, Faculty of Engineering, Czech University of Life Sciences, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic
Department of Agricultural Machines, Faculty of Engineering, Czech University of Life Sciences, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic
Department of Mathematics, Faculty of Engineering, Czech University of Life Sciences, Kamýcká 129, 165 21 Prague 6 – Suchdol, Czech Republic
Division of Crop Management Systems, Crop Research Institute, Drnovská 507, 161 00 Prague 6 – Ruzyně, Czech Republic
Final revision date: 2020-08-14
Acceptance date: 2020-08-20
Publication date: 2020-09-28
Corresponding author
Zdeněk Jelínek   

Department of Machinery Utilization, Czech University of Life Sciences, Kamýcká 129, 16521, Prague, Czech Republic
Int. Agrophys. 2020, 34(3): 391-406
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 (R2 = 0.876) than data with a one-day delay (R2 = 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.
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