Assessing Grapevine Canopy Health in the Texas Hill Country with Remote Sensing and GIS Techniques
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Vineyards are typically managed uniformly over space, although known spatial variation exists in the performance of vines within and across vineyard blocks. Identifying spatial variability in crop performance at a large scale (one or a few vineyard blocks) is useful to vineyard managers wishing to address such variation by enacting separate management plans for differing areas of performance. Zonal management and the institution of precision viticultural practices (i.e. use of GIS and remote sensing techniques to study this spatial variation) has proven profitable for a number of reasons, namely zonal harvesting based on zone performance. This dissertation implements cutting-edge, practical, and low-cost equipment and techniques, specifically an unmanned aerial vehicle (UAV), digital cameras, and Structure from Motion (SfM), to identify spatial variation in grapevine canopy vigor at a vineyard in the Texas Hill Country American Viticultural Area. Three research objectives were addressed in this dissertation including: (1) the setup and implementation of a practical imaging system and processing methodology (digital cameras and a UAV) to produce very high spatial resolution orthophotomosaics of vineyards with visible and near-infrared bands, (2) observation of spatial and temporal variation in grapevine canopy vigor that can aid in improving vineyard management practice, and (3) development of a three-dimensional method for visualizing and quantifying vineyard canopy density. Results concluded that the low-cost tools and techniques outlined in this study provided a practical means by which to identify spatial variation in canopy vigor at the study vineyard. Of the three methods used to identify this variation, spectrally-based (NDVI), planimetrically-based (canopy extent), and three-dimensionally-derived (SfM point clouds), the latter two were most successful and would be recommended for future use. Most importantly, due to the low cost of the technology used to capture data for this study, the methodologies developed in this dissertation would be practical for implementation in other vineyards as well as in other areas of agriculture.