UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras

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dc.bibliographicCitation.endpage212es_ES
dc.bibliographicCitation.stpage206es_ES
dc.bibliographicCitation.titleAgriEngineeringen
dc.bibliographicCitation.volume2(2)es_ES
dc.contributor.authorSánchez Sastre, Luis Fernandoes_ES
dc.contributor.authorCasterad Seral, María Auxiliadoraes_ES
dc.contributor.authorGuillén Castillo, Mónicaes_ES
dc.contributor.authorRuiz Potosme, Norlan Migueles_ES
dc.contributor.authorAlte da Veiga, Nuno M.S.es_ES
dc.contributor.authorNavas Gracia, Luis Manueles_ES
dc.contributor.authorMartín Ramos, Pabloes_ES
dc.coverage.spatialSuelos y riegoses_ES
dc.date.accessioned2020-04-17T06:31:19Z
dc.date.available2020-04-17T06:31:19Z
dc.date.issued2020es_ES
dc.description.abstractUnmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.en
dc.description.otherVehículos aéreos no tripuladosen
dc.description.otherAgricultura de precisiónes_ES
dc.description.statusPublishedes_ES
dc.identifier.citationAgriEngineering, vol. 2, num. 2, pp. 206-212, (2020)
dc.identifier.urihttp://hdl.handle.net/10532/4976
dc.language.isoenes_ES
dc.relation.doi10.3390/agriengineering2020012es_ES
dc.relation.urihttps://www.mdpi.com/2624-7402/2/2/12es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.agrovocSensoreses
dc.subject.agrovocMalezases
dc.titleUAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Camerasen
dc.typeJournal Contribution*
dc.type.refereedRefereedes_ES
dc.type.specifiedArticlees_ES

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