2020/09/28 by Zdeněk Jelínek, Jitka Kumhálová, J. Chyba +4
Agricultural and Biological Sciences · Environmental Science · #Leaf Properties and Growth Measurement #Remote Sensing in Agriculture
paper · pdf · doi:10.31545/intagr/126593
openalex publication_date 2020/09/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/18
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 2 = 0.876) than data with a one-day delay (R 2 = 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.