Table of Contents
Remote Sens., Volume 9, Issue 2 (February 2017)
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Cover Story An algorithm, based on RGB imagery, acquired with a UAV is proposed to characterize the 3D [...] Read more. An algorithm, based on RGB imagery, acquired with a UAV is proposed to characterize the 3D macro-structure of vineyards. We apply a photogrammetric technique on the overlapping RGB images to derive the canopy height model. By applying a threshold, we separate the rows from the inter-rows to estimate the row orientation, height, width and spacing, the cover fraction and the percentage of missing segments along the rows. Comparison with ground measurements provides a root mean square error of 9.8 cm for row height, 8.7 cm for row width, and 7 cm for row spacing. Conversely to height and spacing, the ability of the algorithm to accurately estimate row width, cover fraction and percentage of missing row segments, depends on the success of the photogrammetric technique. It is therefore mandatory to combine optimal flight configuration and camera settings to get good quality images with a high overlapping percentage. View the paper.