We demonstrate a novel computational efficient method to classify tree species in LiDAR point clouds.

Our results can provide a wider scientific basis for the pulling test method. They help to validate risk assessments and studies based on static load tests and increase their credibility and acceptance, thereby contributing significantly to the efficacy of research experiments as well as to the prospects of conserving valuable trees.