A Method for Automatical Extraction of Typical Disaster-bearing Targets from LiDAR Point Cloud in Coastal Zone

DOI

10.2991/icsd-16.2017.98How to use a DOI?

Keywords

coastal zone;disaster bearing targets;LiDAR;object extraction

Abstract

This paper presents a method based on georeferenced feature image to automatically extract typical disaster-bearing targets from coastal LiDAR data. Firstly, the noise and the water surface of LiDAR point cloud are removed by using the elevation histogram. Secondly, by analyzing the spatial distribution of point cloud, the georeferenced feature image of point cloud is generated. Finally, the image processing method and the corresponding relationship between the three-dimensional point cloud and the two-dimensional feature image are used to realize the automatic extraction of the targets. In this paper, the LiDAR cloud data of Haidian Island acquired by ALS70, is used as experimental data to verify the feasibility and practicability of the proposed method.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Ping Wang
AU  - Zheng Wei
AU  - Yu-Chao Sun
AU  - Ji-Sheng Zeng
AU  - Fan Yang
AU  - Ling Tang
PY  - 2016/12
DA  - 2016/12
TI  - A Method for Automatical Extraction of Typical Disaster-bearing Targets from LiDAR Point Cloud in Coastal Zone
BT  - Proceedings of the 2nd 2016 International Conference on Sustainable Development (ICSD 2016)
PB  - Atlantis Press
SP  - 449
EP  - 452
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsd-16.2017.98
DO  - 10.2991/icsd-16.2017.98
ID  - Wang2016/12
ER  -