RESEARCH ON POWER TRANSMISSION CHANNEL CHANGE DETECTION BASED ON MULTI-TEMPORAL POINT CLOUD DATA

Abstract. Airborne LiDAR can directly obtain 3D information of ground objects. By comparing the multi-temporal LiDAR data, ground objects change information of power transmission channel can be detected, providing data support for transmission line operation and maintenance. In this paper, an improved ICP algorithm based on multi-temporal LiDAR point cloud data power transmission channel ground object change detection method is proposed. Firstly, based on the classification of point cloud data, a two-level matching method of multi-temporal point cloud data considering the characteristics of power transmission channel was proposed to achieve accurate registration of point cloud data. Then, change detection and analysis of different types of ground feature point cloud data were carried out through elevation difference. Finally, cluster analysis was carried out on the changed ground feature points to generate multi-temporal relative ratio analysis report. Experimental results show that the proposed method can effectively detect power transmission channel changes.