Mapping of spatial spreading and infestation level of plant diseases and/or animal pests on a practical scale using cereal and sugar beet fields
multispectral imaging, plant diseases, remote sensing, site-specific crop protection, wheat, sugar beet
Today multi-spectral remote sensing allows a wide range of application in precision farming. Remote sensing provides growers with yield assessments, shows yield variations across fields and give information about the growth rate at important development stages. This includes detection of stress due to drought and nutrient deficiency as well as a result of plant diseases or animal pests. In this study the focus is on the spatial distribution of fungal infestations in winter wheat and nematodes in sugar beet at different crop growth stages. Of particular interest is the detection of fungal diseases in early grwowth states by the use of very high resolution remote sensing (VHRRS) imagery. These images will be taken from the QuickBird, the satellite with the highest available resolution up to 0,6 m in the panchromatic mode and 2,4 m in the multispectral mode. Due to the rare availability of the QuickBird images, alternatives to the satellite images will be tested. These alternatives are aerial hyperspectral images (HyMap-sensor with 126 spectral channels), images taken by a NIR digital camera, which is carried by a model helicopter for aerial view or fixed to a stand to take images in close-up range. With Image analysis, interpretation in relation to ground truth data and statistical analysis with GIS software the spatial spreading and infestation level of the fungal diseases in wheat and nematodes in sugar beet will be mapped.
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