Bulletin of Surveying and Mapping ›› 2024, Vol. 0 ›› Issue (5): 115-120.doi: 10.13474/j.cnki.11-2246.2024.0520

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Key technologies of point cloud processing for light and small airborne LiDAR

HUANG Jiangxiong, CAO Qian, HU Xiang, CHEN Xiaojun   

  1. Changsha Planning & Design Survey Research Institute, Changsha 410007, China
  • Received:2023-09-04 Published:2024-06-12

Abstract: Aiming at the problem that the elevation accuracy of light and small airborne LiDAR point cloud data is difficult to meet the production requirements of 1∶500 large-scale topographic maps, this paper adopts a new hierarchical multi-model combined filtering method to classify and extract ground points. This paper systematically introduces the measurement principle of airborne LiDAR, the collection and processing methods of point cloud data, and focuses on the classification and extraction methods of ground points according to the characteristics of light and small LiDAR, such as large thickness of point cloud data and few ground points in dense vegetation areas. The new combination of multiple filtering models can effectively improve the elevation accuracy of ground points after classification. After resampling the ground points, the elevation points are extracted and used to draw contour lines of topographic maps. This method perfectly takes into account the accuracy and aesthetics of contour lines.

Key words: LiDAR, point cloud classification, combined filtering, topographic map production

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