Influence of the scanned side of the row in terrestrial laser sensor applications in vineyards: practical consequences

Influence of the scanned side of the row in terrestrial laser sensor applications in vineyards:... Terrestrial laser scanners (TLS) have been used to estimate leaf area and optimise the site-specific management in vineyards. The tree area index (TAI) is a parameter that can be obtained from TLS measurements and has been highly successful in predicting the leaf area index (LAI) in vineyards using linear regression models. However, there are concerns about the possible variation of the models according to the row side on which the scan is performed. A field trial was performed in a North–South oriented vineyard using a tractor-mounted LiDAR system to determine the influence of this operational factor. Four vineyard blocks were scanned from both sides and then defoliated to obtain the real LAI values for 1 m row length sections. Specifically, LAI values were obtained considering the total canopy width and, after separation of the leaves of the right and left sides, LAI values of half canopy were also calculated. To estimate the LAI from the TAI, dummy-variable regression models were used which showed no differences with respect to the scanned side of the canopy. Two consequences are immediate. First, TLS made it possible the LAI mapping of two different rows by scanning from the alley-way with an appropriate laser scanner. Secondly, the same model can be used to estimate the LAI of half canopy (right or left) in operations that require going through all inter-rows (e.g., when applying plant protection products in a vineyard to estimate the vegetation exposed to the sprayer). Precision Agriculture Springer Journals

Influence of the scanned side of the row in terrestrial laser sensor applications in vineyards: practical consequences

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Springer US
Copyright © 2014 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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