Real-time approaches for characterization of fully and partially scanned canopies in groves

• Characterization of orchards enhances agricultural processes and resource management.
• Four computational geometry methods to estimate tree canopy volumes were evaluated.
• The methodologies were validated using real agricultural scenarios 3D LiDAR data.
• The methodologies have shown to converge to steady state estimations of the volume.
• Resources can be saved when partially scanning canopies.

Efficient information management in orchard characterization leads to more efficient agricultural processes. In this brief, a set of computational geometry methods are presented and evaluated for orchard characterization; in particular, for the estimation of canopy volume and shape in groves and orchards using a LiDAR (Light Detection And Ranging) sensor mounted on an agricultural service unit. The proposed approaches were evaluated and validated in the field, showing they are convergent in the estimation process and that they are able to estimate the crown volume for fully scanned canopies in real time; for partially observed tree crowns, accuracy decreases up to 30% (the worst case). The latter is the major contribution of this brief since it implies that the automated service unit does not need to cover all alley-ways for an accurate modeling of the orchard, thus saving valuable resources.