Enhanced Vineyard Descriptors combining UAV 2D and 3D Crop Models

Precision viticulture has been assumed as an essential approach to optimise crop-managing practices and to improve the quality of food products. To deploy proper site-specific management, addressing the intrinsic variability within a vineyard or a parcel, reliable methods for features extraction and mapping of crops must be developed. The introduction in agriculture of Unmanned Aerial Vehicle (UAV), equipped with sensors able to acquire fields planar images at several wavelengths, makes available huge amount of data with high-resolution, in terms of both spatial and temporal dimension. Recently, in addition to well-known 2D mosaicked images, innovative features leaded by modern photogrammetry allowed accurate three-dimensional models of crops (ex. 3D point cloud datasets) to be generated. The approach presented in this work is aimed at defining enhanced crop descriptors by exploiting information provided by both 2D and 3D crop models. Crucial phases of the procedure are the proper management of data provided by several sources, in order to achieve high consistency of the obtained huge dataset. In addition, the detection of vine rows, discriminating them from all the other elements of rural areas, plays a crucial role. The proposed methodology does not require the straightness of vine rows and it can be profitably applied to models of vineyards with curvilinear rows, also on steep terrains. Specific computing optimisation have been defined in order to reduce big data complexity. A set of 24 portion of vine rows, each made by 4 plants, has been used to validate the effectiveness of the evaluated crop canopy descriptors. The 2D maps and 3D point-cloud models have been generated by using aerial images acquired during UAV flights at 35 meters high, in a study vineyard located in Serralunga d’Alba (Piedmont, Northwest of Italy). The integration of 2D-3D information allowed to obtain good performance also in the presence of dense inter-row grassing which, usually, slightly differs from vine canopies in terms of reflectance.