Abstract
The 3D digital characterization of vegetation is a growing practice in the agronomy sector. Precision agriculture is sustained, among other methods, by variables that remote sensing techniques can digitize. At present, laser scanners make it possible to digitize three-dimensional crop geometry in the form of point clouds. In this work, we developed several methods for calculating the volume of vine wood, with the final intention of using these values as indicators of vegetative vigor on a thematic map. For this, we used a static terrestrial laser scanner (TLS), a mobile scanning system (MMS), and six algorithms that were implemented and adapted to the data captured and to the proposed objective. The results show that, with TLS equipment and the algorithm called convex hull cluster, the volumes of a vine trunk can be obtained with a relative error lower than 7%. Although the accuracy and detail of the cloud obtained with TLS are very high, the cost per unit for the scanned area limits the application of this system for large areas. In contrast to the inoperability of the TLS in large areas of terrain, the MMS and the algorithm based on the L1-medial skeleton and the modelling of cylinders of a certain height and diameter have solved the estimation of volumes with a relative error better than 3%. To conclude, the vigor map elaborated represents the estimated volume of each vine by this method.
Highlights
Precision agriculture strategies that apply remote sensing techniques are widely used, in viticulture [1]
The density of the points attained with mobile mapping system (MMS) does not allow us to calculate the volume of the vines with the convex hull cluster (CHC) algorithm, since the dimensions of some parts exceed the mean density of the cloud; its precision is low and it lacks the geometric definition of the figure due to occlusions or a lack of perspective when scanning, as in [60]
It should be noted that the technical limitations of each piece of equipment have guided this work in its two subobjectives: to test the possibility of calculating the volume occupied by the trunks of vines in a vineyard using clouds from points taken with terrestrial laser scanner (TLS) equipment, and to extrapolate the best possibility to a real case study scanned with MMS, where it would be feasible to elaborate a vine size map based on the volume of each vine
Summary
Precision agriculture strategies that apply remote sensing techniques are widely used, in viticulture [1]. Information obtained from satellites, airborne cameras, and ground-based sensors (among others) over the earth’s surface is a trend in research and innovation activities that has been applied to precision agriculture. With these techniques, can we obtain the spectral response of the surface of crop from a determined point of view (aerial or ground-based), but we can obtain the approximate crop geometry [2]. Canopy characterization and monitoring help improve crop management through the estimation of water stress, the affection by pests and weeds, nutritional requirements, and final yield This monitoring could be performed with a network of ground sensors [14,15] and/or remote sensing techniques at any scale
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