TY - JOUR T1 - Characterization of <em>Vitis vinifera</em> L. Canopy Using Unmanned Aerial Vehicle-Based Remote Sensing and Photogrammetry Techniques JF - American Journal of Enology and Viticulture JO - Am. J. Enol. Vitic. DO - 10.5344/ajev.2014.14070 SP - ajev.2014.14070 AU - Rocío Ballesteros AU - José Fernandez Ortega AU - David Hernández AU - Miguel Ángel Moreno Y1 - 2015/01/16 UR - http://www.ajevonline.org/content/early/2015/01/12/ajev.2014.14070.abstract N2 - Leaf area index, green canopy cover, and canopy volume (LAI, GCC and V) are related with grape vigor, quality and yield. Thus, analyzing these parameters throughout the growing season contributes to optimizing site-specific management. Direct measurements of LAI are destructive and tedious and cannot be repeated for the same vine. Thus, it is necessary to develop and validate non-destructive methods to estimate this indicator in the field. Canopy pattern can be characterized by GCC and V. Aerial observation can be a useful tool to determine both parameters. The main purpose of this study was to characterize growth parameters, such as LAI, GCC and V of irrigated and rain-fed Vitis vinifera L. under semiarid conditions using aerial images from unmanned aerial vehicle (UAV). The relationships of LAI with GCC and V were calibrated and validated. Depending on canopy management, training system and pruning practices, the relationships between LAI and the other parameters would require adjustments. Relationships between LAI and growing degree days (GDD), and V and GDD were also obtained to determine a reliable canopy structure pattern during the growing season. ER -