Many traditional techniques in viticulture are generally based upon field observation, but despite their success, these approaches can be limited by time, spatial extent and a lack of repeat temporal monitoring. We propose to deploy a sUAS approach to capture time series high resolution imagery of vineyard sites presenting data on vines (vigour, bud fruitfulness and leaf area) and associated inter-row and headland vegetation (diversity, abundance and biomass). These data will be used to investigate the relationship between wider vineyard biodiversity and wine quality.
In addition, detailed field sampling of vegetation will be undertaken at multiple points in the growth cycle to assess site based biodiversity potential and its influence on vine growth and yield. These data will be used to investigate the relationship between wider vineyard biodiversity and wine quality. The project will build upon the use of the Enhanced Normalised Difference Vegetation Index (see Strong et al., 2017) which indicated the potential of this index to identify and describe the growth, extent, and dynamics of semi-natural and diverse vegetation at a community level. Furthermore, the project will build upon current research on invasive species that has shown the potential for vegetation and species discrimination using very high spatial resolution multispectral sensors.
Development of multi-spectral sUAS applications for viticulture will ensure that UK-based vineyards maintain their position at the forefront of industrial and scientific research and application through the use of geospatial and remote sensing technologies (particularly unmanned aircraft systems). The project aims to establish relationships between spectral properties and wine quality in the vines while seeking to investigate the relationship between wine quality and biodiversity potential within vineyards located in south-east England.