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dc.contributor.authorvan der Heijden, Geertje
dc.contributor.authorCutler, Mark
dc.contributor.authorCosta, Hugo
dc.contributor.authorNilus, Reuben
dc.contributor.authorBoyd, Doreen
dc.contributor.authorFoody, Giles
dc.date.accessioned2021-01-19T14:01:23Z
dc.date.available2021-01-19T14:01:23Z
dc.date.issued2021-01-19
dc.identifier.urihttps://rdmc.nottingham.ac.uk/handle/internal/9117
dc.description.abstractAll data and R scripts for the processing of airborne hyperspectral/lidar data and modelling of the spatial distribution of liana infestation in Sabah, Malaysia.en_UK
dc.language.isoenen_UK
dc.publisherThe University of Nottinghamen_UK
dc.rightsCC-BY*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.lcshRemote sensingen_UK
dc.subject.lcshHyperspectral imagingen_UK
dc.subject.lcshForests and forestry -- Remote sensingen_UK
dc.subject.lcshNeural networks (Computer science)en_UK
dc.titleRemote sensing liana infestation in an a seasonal tropical forest: addressing mismatch in spatial units of analysesen_UK
dc.identifier.doihttp://doi.org/10.17639/nott.7092
dc.subject.freeLiDAR, hyperspectral imaging, neural network, pixel-based soft classification, segmentationen_UK
dc.subject.jacsTechnologiesen_UK
dc.subject.lcG Geography. Anthropology. Recreationen_UK
uon.divisionUniversity of Nottingham, UK Campusen_UK
uon.funder.controlledNatural Environment Research Councilen_UK
uon.datatypeSpectral data and R scriptsen_UK
uon.grantNE/P004806/1en_UK
uon.grantNE/I528477/1en_UK
uon.grantNE/L002604/1en_UK
uon.collectionmethodairborne spectrometeren_UK
uon.preservation.rarelyaccessedtrue
dc.relation.doi10.1002/RSE2.197en_UK


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