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dc.contributor.authorPinkas, Jaroslav
dc.contributor.authorToman, Přemysl
dc.contributor.authorSvoboda, Josef
dc.date.accessioned2025-04-01T09:29:03Z
dc.date.available2025-04-01T09:29:03Z
dc.date.issued2024
dc.identifier.citationActa Polytechnica. 2024, vol. 51, no. , p. 69-74.
dc.identifier.issn1210-2709 (print)
dc.identifier.issn1805-2363 (online)
dc.identifier.urihttp://hdl.handle.net/10467/121935
dc.description.abstractAgricultural machines nowadays use advanced satellite guidance systems that allow not only autonomous parallel guidance of machinery on the field but also enable the control of agriculture implements based on the geographical location of the field. By using aerial photogrammetry images, it is possible to identify the spots of land that require chemical protection. This information can be used to create prescription maps for the control of specialised implements, allowing the identification of weed outbreaks that require herbicide for their elimination. Using spot-spraying technologies, up to 80% of the active substance can be saved compared to the current common broadcast strategy of applying it to the entire field. This technology automatically controls the sprayer nozzles on the booms only in the spots where it is needed. Using an Unmanned Aerial Vehicle (UAV) allows us to take a detailed picture of the ground. Two main possibilities exist for collecting imagery data with an RGB or multispectral camera. One of the key requirements is the appropriate resolution of the picture, which could be controlled by flying altitude. This paper focuses on comparing RGB and multispectral gathered data toward affected spot identification.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherČeské vysoké učení technické v Prazecs
dc.publisherCzech Technical University in Pragueen
dc.relation.ispartofseriesActa Polytechnica
dc.relation.urihttps://ojs.cvut.cz/ojs/index.php/APP/article/view/10441
dc.rightsCreative Commons Attribution 4.0 International Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleComparison of RGB and multispectral cameras for targeted applications in agriculture
dc.typearticleen
dc.date.updated2025-04-01T09:29:03Z
dc.identifier.doi10.14311/APP.2024.51.0069
dc.rights.accessopenAccess
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International License