Zhou Zhang
Assistant Professor, Biological Systems Engineering, UW-Madison
Alfalfa Yield Prediction Using UAV-Based Hyperspectral Imagery and Ensemble Learning
Alfalfa is a valuable and intensively produced forage crop in the United States, and timely estimation of its yield can inform management decisions. However, traditional yield assessment approaches are laborious and time-consuming. Recently, unmanned aerial vehicles (UAVs) have gained attention due to their efficient data acquisition. In addition, compared with other imaging modalities, hyperspectral data can offer higher spectral fidelity for constructing narrow-band vegetation indices for yield modeling. In this study, we performed an in-season alfalfa yield prediction using UAV-based hyperspectral images.