An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth SimulationReportar como inadecuado

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State Key Laboratory of Remote Sensing Science, Beijing Key Laboratory of Environmental Remote Sensing and Digital City, School of Geography, Beijing Normal University, Beijing 100875, China


School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China


Author to whom correspondence should be addressed.

Academic Editors: Jie Shan, Juha Hyyppä, Lars T. Waser and Prasad S. Thenkabail

Abstract Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models DTMs from airborne LiDAR light detection and ranging data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS International Society for Photogrammetry and Remote Sensing working Group III-3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily. View Full-Text

Keywords: LiDAR point cloud; ground filtering algorithm; cloth simulation LiDAR point cloud; ground filtering algorithm; cloth simulation

Autor: Wuming Zhang 1, Jianbo Qi 1,* , Peng Wan 1, Hongtao Wang 2, Donghui Xie 1, Xiaoyan Wang 1 and Guangjian Yan 1



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