Next Article in Journal / Special Issue
Quantification of Two-Dimensional Wave Breaking Dissipation in the Surf Zone from Remote Sensing Data
Previous Article in Journal
Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice
Previous Article in Special Issue
Automated Sensing of Wave Inundation across a Rocky Shore Platform Using a Low-Cost Camera System
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(1), 35; https://doi.org/10.3390/rs10010035

Gaussian Half-Wavelength Progressive Decomposition Method for Waveform Processing of Airborne Laser Bathymetry

1
School of Earth Sciences and Engineering, Hohai University, No. 8, Fo Cheng Xi Rd., Jiang Ning District, Nanjing 210098, China
2
The First Institute of Oceanography, State Oceanic Administration, No. 6, Xian Xia Ling Rd., Lao Shan District, Qingdao 266061, China
*
Author to whom correspondence should be addressed.
Received: 31 October 2017 / Revised: 19 December 2017 / Accepted: 22 December 2017 / Published: 26 December 2017
(This article belongs to the Special Issue Instruments and Methods for Ocean Observation and Monitoring)
Full-Text   |   PDF [10529 KB, uploaded 26 December 2017]   |  

Abstract

In an airborne laser bathymetry system, the full-waveform echo signal is usually recorded by discrete sampling. The accuracy of signal recognition and the amount of effective information that can be extracted by conventional methods are limited. To improve the validity and reliability of airborne laser bathymetry data and to extract more information to better understand the water reflection characteristics, we select the effective portion of the original waveform for further research, suppress random noise, and decompose the selected portion progressively using the half-wavelength Gaussian function with the time sequence of the received echo signals. After parameter optimization, a reasonable and effective reflection component selection mechanism is established to obtain accurate parameters for the reflected components. The processing strategy proposed in this paper reduces the problems of unreasonable decomposition and the reflected pulse peak-position shift caused by echo waveform superposition and offers good precision for waveform decomposition and peak detection. In another experiment, the regional processing result shows an obvious improvement in the shallow water area, and the bottom point cloud is as accurate as the intelligent waveform digitizer (IWD), a subsystem of airborne laser terrain mapping (ALTM). These findings confirm that the proposed method has high potential for application. View Full-Text
Keywords: airborne laser bathymetry; full-waveform data; waveform fitting; Gauss decomposition; parameter optimization airborne laser bathymetry; full-waveform data; waveform fitting; Gauss decomposition; parameter optimization
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Guo, K.; Xu, W.; Liu, Y.; He, X.; Tian, Z. Gaussian Half-Wavelength Progressive Decomposition Method for Waveform Processing of Airborne Laser Bathymetry. Remote Sens. 2018, 10, 35.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top