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Assessing the potential of hyperspectral remote sensing for the discrimination of grassweeds in winter cereal crops
19 páginas, figuras y tablas estadĂsticas.This article explores the potential use of remote sensing to discriminate two grassweeds
(Avena sterilis and Lolium rigidum) from four cultivars (cvs) of winter wheat
and barley. Hyperspectral measurements, using a GER2600 spectroradiometer
(350 to 2500 nm), were conducted throughout the life cycle of the plants in order
to analyse spectral differences between weeds and crops at different phenological
stages. Specific techniques for hyperspectral data, such as the Spectral Angle
Mapper (SAM) were used to quantify the spectral separability between weeds
and crops, while stepwise discriminant analysis was applied to detect those wavelengths
providing the best discrimination ability. SAM results showed that spectral
differences were generally insufficient to discriminate weeds and crops. Only
during the first phenological stages were angular distances large enough to achieve
a good classification of the different species. This behaviour was related to the
different fraction cover of crops and weeds in this period. The wavebands that
provide the best discrimination ability according to the discriminant analysis were
pooled in eight spectral regions in order to determine their frequency of occurrence.
The four most frequently selected spectral regions were the Far Short-Wave
Infrared, Early Short-Wave Infrared, Blue and the Red Edge.Spatial Biology of cereal weed; detection and control approaches using local
herbicide applications’ AGL20020-4468-C030-3, which was financed by the Spanish
Ministry of Education and Science.Peer reviewe