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Abstract
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.
Acknowledgements
The work described in this article was carried out within the framework of the project entitled ‘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. We would like to express our gratitude to the staff from ‘La Poveda’ experimental farm of the Spanish National Research Council (CSIC), as well as the Environmental Remote Sensing research group from the Department of Geography at the University of Alcalá, for their support in obtaining the field data.
