Abstract
This paper proposes a novel approach for living and missing vine identification and vine characterization in goblet-trained vine plots using aerial images. Given the periodic structure of goblet vineyards, the RGB color coded parcel image is analyzed using proper processing techniques in order to determine the locations of living and missing vines. Vine characterization is achieved by implementing the marker-controlled watershed transform where the centers of the living vines serve as object markers. As a result, a precise mortality rate is calculated for each parcel. Moreover, all vines, even the overlapping ones, are fully recognized providing information about their size, shape, and green color intensity. The presented approach is fully automated and yields accuracy values exceeding 95% when the obtained results are assessed with ground-truth data. This unsupervised and automated approach can be applied to any type of plots presenting similar spatial patterns requiring only the image as input.
Highlights
The rapid evolution of new technologies in precision viticulture allows better vineyard management, monitoring and control of spatio-temporal crop variability; helps increasing their oenological potential [1,2]
Remote sensing data and image processing techniques are used to fully characterize vineyards starting from automatic parcel delimitation to plant identification
The approach presented in this paper addresses the problem of living and missing vine identification, as well as vine characterization in goblet trained parcels using high resolution aerial images
Summary
The rapid evolution of new technologies in precision viticulture allows better vineyard management, monitoring and control of spatio-temporal crop variability; helps increasing their oenological potential [1,2]. Remote sensing data and image processing techniques are used to fully characterize vineyards starting from automatic parcel delimitation to plant identification. Missing plant detection has been the subject of many studies. There is a permanent need to identify vine mortality in a vineyard in order to detect the presence of diseases causing damage and, more importantly, as a way of estimating productivity and return on investment (ROI) for each plot. The lower the mortality rate, the higher the ROI. Mortality rate can help management take better informed decisions for each plot
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