Next Article in Journal
Hyperspectral REE (Rare Earth Element) Mapping of Outcrops—Applications for Neodymium Detection
Previous Article in Journal
Monitoring the Distribution and Dynamics of an Invasive Grass in Tropical Savanna Using Airborne LiDAR
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(5), 5133-5159; doi:10.3390/rs70505133

Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

1
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA
2
National Center for Airborne Laser Mapping, University of Houston, 5000 Gulf Freeway Building 4 Room 216, Houston, TX 77204, USA
3
Department of Geography, University of Wyoming, 1000 E University Ave, Laramie, WY 82071, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Wagner and Prasad S. Thenkabail
Received: 17 February 2015 / Revised: 13 April 2015 / Accepted: 20 April 2015 / Published: 24 April 2015
View Full-Text   |   Download PDF [9086 KB, uploaded 24 April 2015]   |  

Abstract

We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water. View Full-Text
Keywords: LiDAR; full waveform; bathymetry; wavelet transformation LiDAR; full waveform; bathymetry; wavelet transformation
Figures

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 alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Pan, Z.; Glennie, C.; Hartzell, P.; Fernandez-Diaz, J.C.; Legleiter, C.; Overstreet, B. Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry. Remote Sens. 2015, 7, 5133-5159.

Show more citation formats Show less citations formats

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