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Remote Sens. 2016, 8(9), 767; doi:10.3390/rs8090767

Evaluation of Single Photon and Geiger Mode Lidar for the 3D Elevation Program

1
U.S. Geological Survey, Reston, VA 20192, USA
2
Woolpert, Arlington, VA 22206, USA
3
Dewberry Consultants LLC, Fairfax, VA 22031, USA
4
U.S. Geological Survey, Lakewood, CO 80225, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Jie Shan, Juha Hyyppä, Lars T. Waser and Prasad S. Thenkabail
Received: 28 June 2016 / Revised: 19 August 2016 / Accepted: 8 September 2016 / Published: 19 September 2016
(This article belongs to the Special Issue Airborne Laser Scanning)
View Full-Text   |   Download PDF [6526 KB, uploaded 19 September 2016]   |  

Abstract

Data acquired by Harris Corporation’s (Melbourne, FL, USA) Geiger-mode IntelliEarth™ sensor and Sigma Space Corporation’s (Lanham-Seabrook, MD, USA) Single Photon HRQLS sensor were evaluated and compared to accepted 3D Elevation Program (3DEP) data and survey ground control to assess the suitability of these new technologies for the 3DEP. While not able to collect data currently to meet USGS lidar base specification, this is partially due to the fact that the specification was written for linear-mode systems specifically. With little effort on part of the manufacturers of the new lidar systems and the USGS Lidar specifications team, data from these systems could soon serve the 3DEP program and its users. Many of the shortcomings noted in this study have been reported to have been corrected or improved upon in the next generation sensors. View Full-Text
Keywords: lidar; Geiger-mode; single photon lidar; Geiger-mode; single photon
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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).

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MDPI and ACS Style

Stoker, J.M.; Abdullah, Q.A.; Nayegandhi, A.; Winehouse, J. Evaluation of Single Photon and Geiger Mode Lidar for the 3D Elevation Program. Remote Sens. 2016, 8, 767.

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