Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks
10 pages, 4 tables
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| Format: | artículo biblioteca |
| Language: | English |
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Blackwell Publishing
2008-02
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| Subjects: | Patch dynamics, Real-time, Site-specific weed management, Spectral signature, Remote sensing, Avena sterilis, Lolium rigidum, Phalaris brachystachys., |
| Online Access: | http://hdl.handle.net/10261/25823 |
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dig-ias-es-10261-258232021-05-11T00:45:50Z Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks López Granados, Francisca Peña Barragán, José Manuel Jurado-Expósito, Montserrat Francisco-Fernández, Mario Cao, Ricardo Alonso-Betanzos, A. Fontela-Romero, Óscar Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. 10 pages, 4 tables Field studies were conducted to determine the potential of multispectral classification of late-season grass weeds in wheat. Several classification techniques have been used to discriminate differences in reflectance between wheat and Avena sterilis, Phalaris brachystachys, Lolium rigidum and Polypogon monspeliensis in the 400–900 nm spectrum, and to evaluate the accuracy of performance for a spectral signature classification into the plant species or group to which it belongs. Fisher's linear discriminant analysis, nonparametric functional discriminant analysis and several neural networks have been applied, either with a preliminary principal component analysis (PCA) or not and in different scenarios. Fisher's linear discriminant analysis, feedforward neural networks and one-layer neural network, all showed classification percentages between 90% and 100% with PCA. Generally, a preliminary computation of the most relevant principal components considerably improves the correct classification percentage. These results are promising because A. sterilis and L. rigidum, two of the most problematic, clearly patchy and expensive-to-control weeds in wheat, could be successfully discriminated from wheat in the 400–900 nm range. Our results suggest that mapping grass weed patches in wheat could be feasible with analysis of real-time and high-resolution satellite imagery acquired in mid-May under these conditions. Spanish Ministry of Education and Science through projects MTM2005-00429 and AGL2005-06180-CO3-02, and by the Xunta de Galicia by project PGIDT05TIC10502PR. Peer reviewed 2010-06-30T11:57:30Z 2010-06-30T11:57:30Z 2008-02 artículo http://purl.org/coar/resource_type/c_6501 Weed Research 48: 28-37 (2008) 0043-1737 http://hdl.handle.net/10261/25823 10.1111/j.1365-3180.2008.00598.x 1365-3180 en http://dx.doi.org/10.1111/j.1365-3180.2008.00598.x open 157338 bytes application/pdf Blackwell Publishing |
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biblioteca |
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Europa del Sur |
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Biblioteca del IAS España |
| language |
English |
| topic |
Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. |
| spellingShingle |
Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. López Granados, Francisca Peña Barragán, José Manuel Jurado-Expósito, Montserrat Francisco-Fernández, Mario Cao, Ricardo Alonso-Betanzos, A. Fontela-Romero, Óscar Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| description |
10 pages, 4 tables |
| format |
artículo |
| topic_facet |
Patch dynamics Real-time Site-specific weed management Spectral signature Remote sensing Avena sterilis Lolium rigidum Phalaris brachystachys. |
| author |
López Granados, Francisca Peña Barragán, José Manuel Jurado-Expósito, Montserrat Francisco-Fernández, Mario Cao, Ricardo Alonso-Betanzos, A. Fontela-Romero, Óscar |
| author_facet |
López Granados, Francisca Peña Barragán, José Manuel Jurado-Expósito, Montserrat Francisco-Fernández, Mario Cao, Ricardo Alonso-Betanzos, A. Fontela-Romero, Óscar |
| author_sort |
López Granados, Francisca |
| title |
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| title_short |
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| title_full |
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| title_fullStr |
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| title_full_unstemmed |
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| title_sort |
multispectral classification of grass weeds and wheat (triticum durum) using linear and nonparametric functional discriminant analysis and neural networks |
| publisher |
Blackwell Publishing |
| publishDate |
2008-02 |
| url |
http://hdl.handle.net/10261/25823 |
| work_keys_str_mv |
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| _version_ |
1777662938929168384 |