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1 results

  • Using Sentinel-2 images to implement Precision Agriculture techniques in large arable fields: First results of a case study

  • A. Escolà, N. Badia, J. Arnó, J. A. Martínez-Casasnovas
  • Journal:
    Advances in Animal Biosciences / Volume 8 / Issue 2 / July 2017
    Published online by Cambridge University Press:
    01 June 2017, pp. 377-382
    Print publication:
    July 2017

  • This work assesses the potential of Sentinel-2A images in precision agriculture for Barley production in a case study. Two workflows are proposed: 1) images were acquired with a relatively simple methodology to follow the crop development; 2) two images around harvest time were downloaded and processed using a more complex and accurate methodology to calculate four vegetation indices (NDVI, WDRVI, GRVI and GNDVI) to be correlated to yield with linear regression models. Yield data were acquired with a yield monitor installed in a combine harvester. Green-based vegetation indices performed slightly better. However, the highest correlation coefficient was 0.48. Better results may be achieved with earlier imagery and other vegetation indices. Sentinel-2 is a promising tool for precision agriculture in large arable crop fields.