Testing the suitability of a terrestrial 2D LiDAR scanner for canopy characterization of greenhouse tomato crops

Llop, Jordi; Gil Moya, Emilio; Llorens Calveras, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

doi:https://doi.org/10.3390/s16091435

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2016

Author

Llop, Jordi

Gil Moya, Emilio

Llorens Calveras, Jordi

Miranda-Fuentes, Antonio

Gallart, Montserrat

Suggested citation

Llop, Jordi; Gil Moya, Emilio; Llorens Calveras, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat; . (2016) . Testing the suitability of a terrestrial 2D LiDAR scanner for canopy characterization of greenhouse tomato crops. Sensors, 2016, vol. 16, num. 9, p. 1435-1449. https://doi.org/10.3390/s16091435.

Abstract

Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps.

URI

http://hdl.handle.net/10459.1/59551

DOI

https://doi.org/10.3390/s16091435

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Sensors, 2016, vol. 16, num. 9, p. 1435-1449

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Except where otherwise noted, this item's license is described as cc-by (c) Jordi Llop et al., 2016