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Using Sentinel-2 images to implement Precision Agriculture techniques in large arable fields: First results of a case study
- Source :
- Advances in Animal Biosciences; July 2017, Vol. 8 Issue: 2 p377-382, 6p
- Publication Year :
- 2017
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 20404700 and 20404719
- Volume :
- 8
- Issue :
- 2
- Database :
- Supplemental Index
- Journal :
- Advances in Animal Biosciences
- Publication Type :
- Periodical
- Accession number :
- ejs42155085
- Full Text :
- https://doi.org/10.1017/S2040470017000784