Analysis of tree obstacle prediction technology for power lines based on laser point cloud

In order to solve the problem of incomplete tree hazard inspection in UAV laser ranging, it is proposed to use laser point cloud data to predict tree hazard of power line. This paper uses the improved KDTree to automatically extract and classify the power line point cloud data and complete the single tree segmentation and classification management. Finally, a model is established to predict the data growth trend, which can solve the problem of tree hazard inspection caused by tree growth. The research results show that the use of theoretical models to scientifically predict the growth trend of trees and accurately assess the risk of tree hazard according to the distance between trees and ground wires can provide an effective technical solution for solving the problem of tree hazard inspection.