A new filtering approach of lidar data based on topographic change detection

Xiaodong Zhang; Peng Chen; Biao Sun; Yao Wang

doi:10.1117/12.2031162

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26 October 2013 A new filtering approach of lidar data based on topographic change detection

Xiaodong Zhang, Peng Chen, Biao Sun, Yao Wang

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Proceedings Volume 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis; 89170R (2013) https://doi.org/10.1117/12.2031162
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

Filtering is a key way to classify ground and non-ground points from LiDAR data. Current LiDAR filtering methods, implemented mostly through single LiDAR point cloud only, lack real data source references, subsequently there may be many errors. In view of this situation, this paper presents a new approach based on topographic change detection for airborne LiDAR filtering. In this method, LiDAR point cloud data are accurately registered with existing DEM data and harmonization to the same coordinate system. Then, we implement grid-based organization of LiDAR point cloud data to make corresponding regions of LiDAR point cloud data and existing DEM data correspond to each other. Finally, we filter LiDAR data based on topographic change detection. In order to verify the algorithm, two types of data with different terrain characteristics-urban and mountain were tested. The experimental results indicate that the approach put forward in this paper is effective in filtering out non-ground points from both urban and mountainous areas, while retaining topographic details.

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Xiaodong Zhang, Peng Chen, Biao Sun, and Yao Wang "A new filtering approach of lidar data based on topographic change detection", Proc. SPIE 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis, 89170R (26 October 2013); https://doi.org/10.1117/12.2031162

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KEYWORDS

LIDAR

Clouds

Error analysis

Remote sensing

Optical filters

Tin

Associative arrays

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