Articles | Volume 11, issue 2
https://doi.org/10.5194/tc-11-681-2017
https://doi.org/10.5194/tc-11-681-2017
Research article
 | 
08 Mar 2017
Research article |  | 08 Mar 2017

Assessment of NASA airborne laser altimetry data using ground-based GPS data near Summit Station, Greenland

Kelly M. Brunt, Robert L. Hawley, Eric R. Lutz, Michael Studinger, John G. Sonntag, Michelle A. Hofton, Lauren C. Andrews, and Thomas A. Neumann

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Cited articles

Bisnath, S. and Gao, Y.: Current state of precise point positioning and future prospects and limitations, in: Observing our changing Earth, Springer Berlin Heidelberg, 615–623, 2009.
Blair, J. and Hofton, M.: Pre-IceBridge LVIS L2 Geolocated Ground Elevation and Return Energy Quartiles, Version 1, NASA NSIDC DAAC, Boulder, Colorado, USA, 2011.
Blair, J. and Hofton, M.: IceBridge LVIS-GH L2 Geolocated Surface Elevation Product, NASA NSIDC DAAC, Boulder, Colorado, USA, 2015.
Blair, J., Rabine, D., and Hofton, M.: The laser vegetation imaging sensor (LVIS): A medium-altitude, digitation-only, airborne laser altimeter for mapping vegetation and topography, ISPRS J. Photogramm., 54, 115–122, 1999.
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Short summary
This manuscript presents an analysis of NASA airborne lidar data based on in situ GPS measurements from the interior of the Greenland Ice Sheet. Results show that for two airborne altimeters, surface elevation biases are less than 0.12 m and measurement precisions are 0.09 m or better. The study concludes that two NASA airborne lidars are sufficiently characterized to form part of a satellite data validation strategy, specifically for ICESat-2, scheduled to launch in 2018.