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.

UAV-based hyperspectral imaging for weed discrimination in maize / Casa, R.; Pascucci, S.; Pignatti, S.; Palombo, A.; Nanni, U.; Harfouche, A.; Laura, L.; Di Rocco, M.; Fantozzi, P.. - (2019), pp. 365-371. (Intervento presentato al convegno 12th European Conference on Precision Agriculture, ECPA 2019 tenutosi a Montpellier, France) [10.3920/978-90-8686-888-9_45].

UAV-based hyperspectral imaging for weed discrimination in maize

Nanni U.;Laura L.;Di Rocco M.;Fantozzi P.
2019

Abstract

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.
2019
12th European Conference on Precision Agriculture, ECPA 2019
drones; image classification; Imaging spectroscopy; machine learning; weed maps
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
UAV-based hyperspectral imaging for weed discrimination in maize / Casa, R.; Pascucci, S.; Pignatti, S.; Palombo, A.; Nanni, U.; Harfouche, A.; Laura, L.; Di Rocco, M.; Fantozzi, P.. - (2019), pp. 365-371. (Intervento presentato al convegno 12th European Conference on Precision Agriculture, ECPA 2019 tenutosi a Montpellier, France) [10.3920/978-90-8686-888-9_45].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1349195
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