Potential of a terrestrial LiDAR-based system to characterise weed vegetation in maize crops
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LiDAR (Light Detection And Ranging) is a remote-sensing technique for the measurement of the distance between the sensor and a target. A LiDAR-based detection procedure was tested for characterisation of the weed vegetation present in the inter-row area of a maize field. This procedure was based on
the hypothesis that weed species with different heights can be precisely detected and discriminated using non-contact ranging sensors such as LiDAR. The sensor was placed in the front of an all-terrain vehicle, scanning downwards in a vertical plane, perpendicular to the ground, in order to detect the profile of the vegetation (crop and weeds) above the ground. Measurements were taken on a maize field on 3 m wide (0.45 m2) plots at the time of post-emergence herbicide treatments. Four replications were assessed for each of the four major weed species: Sorghum halepense, Cyperus rotundus, Datura ferox and Xanthium strumarium. The sensor readings were correlated with actual, manually determined, height values (r2 = 0.88). With canonical discriminant analysis the high capabilities of the system to discriminate tall weeds (S. halepense) from shorter ones were quantified. The classification table showed 77.7% of the original grouped cases (i.e., 4800 sampling units) correctly classified for S. halepense. These results indicate that LiDAR sensors are a promising tool for weed detection and discrimination, presenting significant advantages over other types of non-contact ranging sensors such as a higher sampling resolution and its ability to scan at high sampling rates.
Is part ofComputers and Electronics in Agriculture, 2013, vol. 92, p. 11-15
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Andújar, Dionisio; Rueda-Ayala, Victor; Moreno, Hugo; Rosell Polo, Joan Ramon; Escolà i Agustí, Alexandre; Valero, Constantino; Gerhards, Roland; Fernández-Quintanilla, César; Dorado, José; Griepentrog, Hans-Werner (Molecular Diversity Preservation International (MDPI), 2013)In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and ...
Andújar, Dionisio; Escolà i Agustí, Alexandre; Rosell Polo, Joan Ramon; Sanz Cortiella, Ricardo; Rueda-Ayala, Victor; Fernandez Quintanilla, C.; Ribeiro, Angela; Dorado, José (Springer-Verlag, 2016-06-21)This study evaluated the capabilities of a LiDAR-based system to characterize poplar trees for biomass production. The precision of the system was assessed by analyzing the relationship between the distance records and ...
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