Beijing Surveying and Mapping

The complex surface coverage of overlapping features and the concealment of underground pipelines often result in severe occlusion and large measurement errors in the point clouds obtained by a single LiDAR platform. To improve the accuracy of real-world mapping of ground topography and underground pipelines， a real-world mapping method for ground topography and underground pipelines based on feature selection of 3D LiDAR point clouds was studied. By synchronously scanning with airborne LiDAR and ground LiDAR， point cloud scanning data of ground topography and underground pipelines were obtained， avoiding occlusion from a single perspective; a feature point selection algorithm based on local normal vector consistency was designed to identify the key mapping points of ground topography and underground pipelines， suppressing the redundancy and noise of multi-end perspective point clouds; a kd-tree was used to accelerate neighborhood search to construct a local projection coordinate system， and multiple source point clouds were fused in a unified coordinate system to achieve real-world mapping of ground topography and underground pipelines. Experimental results show that the measurement error of the plane position of ground topography and underground pipelines in severely occluded areas is less than ±5 cm in height measurement error， improving the accuracy of real-world mapping.