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A coupled multitemporal UAV-based LiDAR and multispectral data approach to model dry biomass of maize

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dc.contributor.authorRettig, Robert
dc.contributor.authorStorch, Marcel
dc.contributor.authorWittstruck, Lucas
dc.contributor.authorAnsah, Christabel
dc.contributor.authorBald, Richard Janis
dc.contributor.authorRichard, David
dc.contributor.authorTrautz, Dieter
dc.contributor.authorJarmer, Thomas
dc.contributor.editorHoffmann, Christa
dc.contributor.editorStein, Anthony
dc.contributor.editorRuckelshausen, Arno
dc.contributor.editorMüller, Henning
dc.contributor.editorSteckel, Thilo
dc.contributor.editorFloto, Helga
dc.date.accessioned2023-02-21T15:14:17Z
dc.date.available2023-02-21T15:14:17Z
dc.date.issued2023
dc.description.abstractThe presented approach attempts to highlight the capabilities of a data fusion approach that combines UAV LiDAR (RIEGL – miniVUX-1UAV) and multispectral data (Micasense – Altum) to assess the dry above ground biomass (AGB) for maize. The combined acquisition of both LiDAR and multispectral data not only supports estimates of AGB when fusing them, but also helps to evaluate phenological stage-specific modelling differences on the individual sensor data. A multiple linear regression was applied on the multisensorial UAV data from two appointments in 2021. The resulting R² of 0.87 and RMSE of 14.35 g/plant for AGB was then transferred to AGB in dt/ha.en
dc.identifier.isbn978-3-88579-724-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40296
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-330
dc.subjectLiDAR
dc.subjectmultispectral
dc.subjectmultisensorial
dc.subjectmaize
dc.subjectbiomass
dc.subjectMLR
dc.titleA coupled multitemporal UAV-based LiDAR and multispectral data approach to model dry biomass of maizeen
dc.typeText/Conference Paper
gi.citation.endPage488
gi.citation.publisherPlaceBonn
gi.citation.startPage483
gi.conference.date13.-14. Februar 2023
gi.conference.locationOsnabrück

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P330 - 43. GIL-Jahrestagung 2023 - Fokus: Resiliente Agri-Food-Systeme