1. Prediction of Olive Productivity Using Machine Learning Associated with Aerial Multispectral and Thermal Imagery

Accurate estimation of productivity in olive orchards is fundamental for agricultural planning, resource optimization, and timely decision-making. Conventional methods for assessing productivity are labor-intensive and limited in their ability to represent spatial variability at field scale. Remote sensing using unmanned aerial vehicles (UAVs) combined with machine learning techniques offers a scalable and non-destructive approach for predicting productivity at field scale. This study evaluated... M. Antônio, G. Koch, P.A. Moura, F. Silva, C.C. Santana