Glennie, Craig L.2019-11-132019-11-13December 22016-12December 2https://hdl.handle.net/10657/5416Using airborne and terrestrial LiDAR data from glaciers in Greenland and Antarctica, we compare three change detection methods for accuracy and performance. We focus in particular on one method, Coherent Point Drift (CPD). We find that CPD outperforms Iterative Closest Point (ICP) and Particle Imaging Velocimetry (PIV) when used on a terrestrial LiDAR dataset at the Helheim Glacier in southeast Greenland. At one representative location, CPD calculated an average glacier velocity of 20.11 m d−1 with Root-Mean Squared Error of 2.5 m d−1 when compared to a GNSS-derived measurement of 20.44md−1. All three change detection methods fail to fully capture the motion of the Canada Glacier in Antarctica, but do detect change in the fast-moving and crevassed portion of the glacier. We conclude that these change detection methods, and CPD in particular, are useful tools for measuring glacier velocity when the data have sufficient identifiable features in both epochs.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).LiDARGlaciersChange-detectionCoherent Point DriftIterative Closest PointParticle image velocimetryHelehim GlacierCanada GlacierGlacier velocity2019-11-13Thesisborn digital