- Tytuł:
- 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
- Autorzy:
-
Jelinek, Z.
Kumhalova, J.
Chyba, J.
Wohlmuthova, M.
Madaras, M.
Kumhala, F. - Powiązania:
- https://bibliotekanauki.pl/articles/2082908.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Instytut Agrofizyki PAN
- Tematy:
-
satellite sensors
agriculture
satellite imagery
wheat varieties - Opis:
- 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.
- Źródło:
-
International Agrophysics; 2020, 34, 3; 391-406
0236-8722 - Pojawia się w:
- International Agrophysics
- Dostawca treści:
- Biblioteka Nauki
Artykuł