UAV-based hyperspectral imaging for weed discrimination in maize
Creators
- 1. University of Tuscia
- 2. Institute of Methodologies for Environmental Analysis (IMAA)
- 3. University of Rome 'La Sapienza'
Description
This is the accepted manuscript of the paper "UAV-based hyperspectral imaging for weed discrimination in maize", published as final paper in "Precision agriculture'19, France. July 08 2019, Pages 365–371 https://doi.org/10.3920/978-90-8686-888-9_45”.
Timely weed mapping in crop post-emergence situations is a challenging task required for developing precision weed management solutions. It is necessary to discriminate the crop from the weeds and, if possible, to distinguish different weed species. The ability to map weeds using hyperspectral images acquired from an unmanned airborne vehicle (UAV) over a maize field was evaluated by comparing different classification strategies. The results were mainly affected by the variability in crop and weed spectral signatures. The discrimination between maize and weeds allowed the quantification of their relative ground cover, showing moderate relationship with their relative leaf area index.
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