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dc.contributor.advisorRunesson, Ulf
dc.contributor.authorGraham, Alexander James
dc.date.accessioned2018-08-02T19:52:14Z
dc.date.available2018-08-02T19:52:14Z
dc.date.created2017
dc.date.issued2017
dc.identifier.urihttp://knowledgecommons.lakeheadu.ca:7070/handle/2453/4242
dc.description.abstractTo date, no studies exist exploring the multispectral detection of fungal diseases in barley (H Vulgare L.) with UAV imagery. The purpose of this work was to determine if the spectral response (VI) of barley fungicide treatment levels (Control, Stratego, Stratego + Prosaro) could be distinguished between two farmers’ fields and four growth stages (Feekes 8 to Feekes 11.4), when evaluating UAV multispectral imagery (Blue- 475 nm +/- 20 nm, Green- 560 nm +/- 20 nm, Red- 668 nm +/- 10 nm, Red Edge- 717 nm +/- 10 nm, Near Infrared-840 nm +/- 40 nm) of 6.7 cm/pixel spatial resolution. Radiometrically and geometrically corrected orthomosaics were generated and intrusive features such as weeds and crop damage were classified and extracted before the analyses of canopy level barley. Each photo was registered with RTK accuracy to ensure the analysis of identical pixelated areas between dates. A randomized complete block design was performed for 5 separate VIs: NDVI, RE-NDVI, RDVI, RE-RDVI, and TGI. 3-way interactions (Field x Growth Stage x Treatment) were found to be non-significant for NDVI (p=0.415), RE-NDVI (p=0.383) and TGI (p=0.780), with RDVI (p=0.003) and RE-RDVI (p=0.005) being significant. Despite some differences, a consistent trend in the spectral separability of fungal intensity by treatment type was observed regardless of field, from Feekes 10.51 onwards. With ground truthing, the mapping of fungicide intensity is possible with potential towards savings and environmental benefits from reduced fungicide use.en_US
dc.language.isoen_USen_US
dc.subjectRemote sensing applications in agricultureen_US
dc.subjectPrecision agricultureen_US
dc.subjectMultispectral detection of fungal diseases in barleyen_US
dc.titleDeploying an unmanned aerial vehicle (UAV) equipped with a multispectral sensor for detecting between differing levels of barley (H vulgare L.) fungal diseases in Northern Ontarioen_US
dc.typeThesisen_US
etd.degree.nameMaster of Scienceen_US
etd.degree.levelMasteren_US
etd.degree.disciplineNatural Resources Managementen_US
etd.degree.grantorLakehead Universityen_US


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