A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats
AbstractTo obtain the mudflat topography when existing measuring systems and data processing methods are impracticable under special conditions, this paper presents a hovercraft-borne LiDAR (light detection and ranging) system and a novel comprehensive filtering method. The system is based on a hovercraft and equipped with a laser scanner and a POS (position and orientation system). The filtering method firstly segments the point cloud into different segments by combining the geometric and intensity information, then fitting the ground surface by cloth simulation method, and finally synthetically extracts the ground points with three constraints. These constraints are the distance of the point to the fitting surface, the normal difference between the point and the fitting surface, and the proportion of the possible ground points in the total points of each segment. The effectiveness of the measurement system and the development of the post-processing results were verified on the basis of field measurements, in which a total filtering error of 0.3% and the elevation accuracy of 6.4 cm were obtained. The proposed system and methods provide a new way for efficient and accurate topographic survey on mudflats. View Full-Text
Share & Cite This Article
Zhao, J.; Chen, M.; Zhang, H.; Zheng, G. A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats. Remote Sens. 2019, 11, 1646.
Zhao J, Chen M, Zhang H, Zheng G. A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats. Remote Sensing. 2019; 11(14):1646.Chicago/Turabian Style
Zhao, Jianhu; Chen, Mingyi; Zhang, Hongmei; Zheng, Gen. 2019. "A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats." Remote Sens. 11, no. 14: 1646.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.