Evaluation of Multispectral Data Acquired from UAV Platform in Olive Orchard

Precision agriculture is a management strategy to improve resource efficiency, production, quality, profitability and sustainability of the crops. In recent years, olive tree increasingly focused on determining correct health status plants in order distribute main using different technologies. grove, focus often use multispectral information from UAVs (Unmanned Aerial Vehicle), but it not known how important spectral biometric actually for agronomic grove. The aim this study was investigate ability data acquired UAV platform predict nutritional status, characteristics, vegetative condition production orchard as tool DSS. Data were collected characteristics closely related vigour such trunk cross-sectional area (TCSA), Nitrogen concentration leaves, canopy volume. each plant create an accurate yield map. flight carried out with equipped camera, at altitude 50 m RTK correction. made possible determine features through normalized difference vegetation index (NDVI). NDVI map allowed area. Structure Motion (SfM) algorithm allow 3D experiment showed that able high accuracy characteristic (r = 0.87 ***), TCSA 0.58 ***) 0.63 ***). parameters are correlated especially 0.75 clustering individual dependent leaf nitrogen status.