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dc.contributor.authorMerz, Quirina Noëmi
dc.contributor.authorWalter, Achim
dc.contributor.authorAasen, Helge
dc.contributor.editorGandorfer, Markus
dc.contributor.editorHoffmann, Christa
dc.contributor.editorEl Benni, Nadja
dc.contributor.editorCockburn, Marianne
dc.contributor.editorAnken, Thomas
dc.contributor.editorFloto, Helga
dc.date.accessioned2022-02-24T13:34:45Z
dc.date.available2022-02-24T13:34:45Z
dc.date.issued2022
dc.identifier.isbn978-3-88579-711-1
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/38396
dc.description.abstractFertilizer distribution can be improved by the use of variable rate technology with which plants only receive the amount of fertilizer they actually need. This amount is often calculated with vegetations indexes, such as the NDVI. The NDVI can be derived from drones or satellites. Drones offer more high-resolution imagery than satellites, but satellite data is more readily available. This study focuses on the spatio-temporal difference of apparent field heterogeneity at different spatial resolutions, resampled to 0.5 m and 20 m from high-resolution drone data, throughout the vegetation period and the error induced by low-resolution image data.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof42. GIL-Jahrestagung, Künstliche Intelligenz in der Agrar- und Ernährungswirtschaft
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-317
dc.subjectspectral imaging
dc.subjectdrone-based systems
dc.subjectlow-altitude remote sensing
dc.subjectfield heterogeneity
dc.subjectvariable rate technology
dc.subjectreturn of investment
dc.titleUsing high-resolution drone data to assess apparent agricultural field heterogeneity at different spatial resolutionsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages195-200
mci.conference.locationTänikon, Online
mci.conference.date21.-22. Februar 2022


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