研究目的
To assess vine biomass differences using aerial imagery as the primary source of data for vine analysis, automatically identify vineyards blocks, vine rows, and individual vines within rows, and determine the correlation of image data with the biophysical data (yield and pruning mass) of each vine.
研究成果
The segmentation technique developed in this study reliably detects vine rows in aerial imagery, improving previous classification methods and leading to better estimators of vine biophysical measures. The method can detect curved vine rows and uses both RGB and NIR images, offering advantages over other techniques. Future work will explore the correlation between vegetation indices and vine biophysical measures in more detail and apply the techniques to different vineyards.
研究不足
The method is sensitive to shadows cast by trees and overhanging trees, which can cause adjacent vine rows to be combined into the same segment. The segmentation does not account for the spatial and spectral features of a vine, leading to poor correlations in some cases. Future work will focus on using RGB images for better discrimination of overgrown inter-rows and implementing a hierarchical segmentation approach.