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dc.contributor.authorEscolà i Agustí, Alexandre
dc.contributor.authorBadia, N.
dc.contributor.authorArnó Satorra, Jaume
dc.contributor.authorMartínez Casasnovas, José Antonio
dc.date.accessioned2017-09-20T07:49:27Z
dc.date.issued2017-07-16
dc.identifier.issn2040-4700
dc.identifier.urihttp://hdl.handle.net/10459.1/60240
dc.descriptionProceedings of the 11th European Conference on Precision Agriculture
dc.description.abstractThis 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.
dc.description.sponsorshipThis work was funded by the Spanish Ministry of Economy and Competitiveness through the project AgVANCE (AGL2013-48297-C2-2-R)
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherThe Animal Consortium
dc.relationMINECO/PN2013-2016/AGL2013-48297-C2-2-R
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1017/S2040470017000784
dc.relation.ispartofAdvances in Animal Biosciences, 2017, vol. 8, núm.. 2, p. 377-382
dc.rights(c) The Animal Consortium, 2017
dc.subjectRemote sensing
dc.subjectYield
dc.subjectVegetation indices
dc.subjectCrop vigour
dc.subjectBarley
dc.titleUsing Sentinel-2 images to implement Precision Agriculture techniques in large arable fields: First results of a case study
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2017-09-20T07:49:27Z
dc.identifier.idgrec025834
dc.type.versionacceptedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1017/S2040470017000784


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