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Airborne multi-spectral imagery for mapping cruciferous weeds in cereal and legume crops

机译:机载多光谱图像,用于绘制谷物和豆类作物中的十字花科杂草

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Cruciferous weeds are competitive broad-leaved species that cause losses in winter crops. In the present study, research on remote sensing was conducted on seven naturally infested fields located in Crdoba and Seville, southern Spain. Multi-spectral aerial images (four bands, including blue (B), green (G), red (R) and near-infrared bands) taken in April 2007 were used to evaluate the feasibility of mapping cruciferous patches (Diplotaxis spp. and Sinapis spp.) in winter crops (wheat, broad bean and pea) and compare the accuracy of different supervised classification methods (vegetation indices, maximum likelihood and spectral angle mapper). The best classification method was selected to develop site-specific cruciferous treatment maps. Cruciferous patches were efficiently discriminated with red/blue (R/B) and blue/green (B/G) vegetation indices and the maximum likelihood classifier. At all of the locations, the accuracy of the results obtained from the spectral angler mapper was relatively low. The cruciferous weed-classified imagery of each location were created according to the method that provided the best discrimination results and were used to obtain site-specific treatment maps for in-season post-emergence control measures or herbicide applications for subsequent years. By applying the site-specific treatment maps, herbicide savings from 71.7 to 95.4% for the no-treatment areas and from 4.3 to 12% for the low-dose herbicide were obtained.
机译:十字花科杂草是竞争性阔叶树种,会导致冬季作物损失。在本研究中,对位于西班牙南部科尔多瓦和塞维利亚的七个自然出没地进行了遥感研究。 2007年4月拍摄的多光谱航空影像(四个波段,包括蓝色(B),绿色(G),红色(R)和近红外波段)用于评估绘制十字花科斑块(Diplotaxis spp。和Sinapis)的可行性。 spp。)(冬小麦,蚕豆和豌豆),并比较不同监督分类方法(植被指数,最大似然和光谱角度映射器)的准确性。选择最佳分类方法以开发特定地点的十字花科治疗图。利用红色/蓝色(R / B)和蓝色/绿色(B / G)植被指数以及最大似然分类器有效区分了十字花科斑块。在所有位置,从频谱垂角仪映射器获得的结果的准确性都相对较低。根据提供最佳判别结果的方法创建每个位置的十字花科杂草分类图像,并将其用于获得现场特定的处理图,以用于季节后的出苗后控制措施或随后几年的除草剂应用。通过应用特定地点的处理图,对于非处理区域,除草剂节省量可从71.7%降至95.4%,对于低剂量除草剂可节省4.3%至12%。

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