Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners

Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners Mapping the leaf area index (LAI) by using mobile terrestrial laser scanners (MTLS) is of significance for viticulture. LAI is related to plant vigour and foliar development being an important parameter for many agricultural practices. Since it may present spatial variability within vineyards, it is very interesting monitoring it in an objective repeatable way. Considering the possibility of using on-the-go sensors such as MTLS within an agricultural plot, it is necessary to set a proper length of the row to be scanned at each sample point for a reliable operation of the scanner. Three different row length sections of 0.5, 1, and 2 m have been tested. Data analysis has shown that models required to estimate LAI differ significantly depending on the scanned length of the row; the model required to estimate LAI for short sections (0.5 m) is different from that required for longer sections (1 and 2 m). Of the two models obtained, we recommend using MTLS for scanning row length sections of 1 m because the practical use of the sensor in the field is simplified without compromising the results (there is little variation in the model when the row length section changes from 1 to 2 m). In addition, a sufficient number of sampling points is obtained to support a map of the LAI. Linear regression models using as explanatory variable the tree area index, obtained from the data provided by the scanner, are used to estimate the LAI. Precision Agriculture Springer Journals

Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners

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Springer US
Copyright © 2016 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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