Abstract
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 weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.
Highlights
Current technologies, such as GISand new technical equipment, allow for the possibility of managing the spatial variability of weeds
The results showed a strong correlation between actual heights and light detection and ranging (LIDAR) heights, with an R2 = 0.75 (Figure 2)
Ultrasonic devices can measure plant heights with high accuracy, they are not able to create a plane in a single reading, because their output is a unique value corresponding to the field of view (FOV)
Summary
Current technologies, such as GISand new technical equipment, allow for the possibility of managing the spatial variability of weeds. The concept of site-specific weed management (SSWM) is an attempt to cope with the heterogeneity occurring within fields by treating only weed patches. Using SSWM may result in substantial herbicide savings, depending on the weed infestation and its distribution in the field. Gerhards and Christensen Gerhards and Christensen [2], in a four year study with various grass weeds in cereals, showed herbicide reduction higher than 75%. The final implementation of SSWM techniques at a commercial level needs to be seen from the standpoint of the overall prosperity of arable crop production: profitable crop production requires larger investment in new equipment and technologies
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