Bulletin of Surveying and Mapping ›› 2021, Vol. 0 ›› Issue (7): 1-5.doi: 10.13474/j.cnki.11-2246.2021.0199

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LiDAR point cloud ground filtering algorithm in dense and low vegetation area

YAN Yueguan, CHEN Zhongzhang, SUN Yang, LI Zezheng, YAO Chengzhi   

  1. Geoscience and Surveying Engineering College, China University of Mining & Technology-Beijing, Beijing 100083, China
  • Received:2021-05-11 Revised:2021-05-21 Online:2021-07-25 Published:2021-08-04

Abstract: Aiming at the characteristics of LiDAR point cloud in mining areas with complex terrain and dense low vegetation, this paper proposes a ground filtering algorithm based on slope information combined with plane fitting. This method uses the second-level grid method to select ground seed points by hierarchical extraction, and uses the ground seed points in each first-level grid to construct a ground model by plane fitting through the least squares fitting method. Finally, ground point and non-ground point can be distinguished. Through comparative experiments with the traditional slope filter and cloth simulation filter, it is concluded that this method can effectively filter out dense and low shrubs and can better retain the larger slope terrain.

Key words: LiDAR, dense low shrubs, slope, ground filtering algorithm

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