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Keywords = pixelated leaf wall area (PLWA)

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24 pages, 14042 KiB  
Article
Georeferenced Scanning System to Estimate the Leaf Wall Area in Tree Crops
by Ignacio Del-Moral-Martínez, Jaume Arnó, Alexandre Escolà, Ricardo Sanz, Joan Masip-Vilalta, Joaquim Company-Messa and Joan R. Rosell-Polo
Sensors 2015, 15(4), 8382-8405; https://doi.org/10.3390/s150408382 - 10 Apr 2015
Cited by 16 | Viewed by 9021
Abstract
This paper presents the use of a terrestrial light detection and ranging (LiDAR) system to scan the vegetation of tree crops to estimate the so-called pixelated leaf wall area (PLWA). Scanning rows laterally and considering only the half-canopy vegetation to the line of [...] Read more.
This paper presents the use of a terrestrial light detection and ranging (LiDAR) system to scan the vegetation of tree crops to estimate the so-called pixelated leaf wall area (PLWA). Scanning rows laterally and considering only the half-canopy vegetation to the line of the trunks, PLWA refers to the vertical projected area without gaps detected by LiDAR. As defined, PLWA may be different depending on the side from which the LiDAR is applied. The system is completed by a real-time kinematic global positioning system (RTK-GPS) sensor and an inertial measurement unit (IMU) sensor for positioning. At the end, a total leaf wall area (LWA) is computed and assigned to the X, Y position of each vertical scan. The final value of the area depends on the distance between two consecutive scans (or horizontal resolution), as well as the number of intercepted points within each scan, since PLWA is only computed when the laser beam detects vegetation. To verify system performance, tests were conducted related to the georeferencing task and synchronization problems between GPS time and central processing unit (CPU) time. Despite this, the overall accuracy of the system is generally acceptable. The Leaf Area Index (LAI) can then be estimated using PLWA as an explanatory variable in appropriate linear regression models. Full article
(This article belongs to the Collection Sensors in Agriculture and Forestry)
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