The application of LiDAR and machine learning in estimating crop traits and yield prediction

Canopy structure has profound effects in the final crop yield production. This project demonstrates novel methods for canola canopy estimations and early yield prediction from 3D LiDAR point clouds captured. LiDAR is an advanced remote sensor that has been widely used for 3D point cloud model construction. Machine learning classifier needs to recognise the ground and different plant parts within the point cloud prior to the estimation. Early yield prediction is the possible with LiDAR-derived parameters with the help of machine learning regression algorithms.