INFERENCE OF SURFACE VELOCITIES FROM OBLIQUE TIME LAPSE PHOTOS AND TERRESTRIAL BASED LIDAR AT THE HELHEIM GLACIER

• Main Author: Dunbar, Franklyn T, II
• Format: Thesis
• Language: unknown
• Published: University of Montana 2021
• Subjects: computer science; glaciology; geophysics; bayesian statistics; climate science; computer vision; machine learning; Artificial Intelligence and Robotics; Climate; Data Science; Hydrology; Numerical Analysis and Computation; Numerical Analysis and Scientific Computing; Partial Differential Equations; Greenland; glacier; Ice Sheet
• Online Access: https://scholarworks.umt.edu/etd/11836; https://scholarworks.umt.edu/context/etd/article/12948/viewcontent/Thesis.pdf

Using time dependent observations derived from terrestrial LiDAR and obliquetime-lapse imagery, we demonstrate that a Bayesian approach to glacial motion es-timation provides a concise way to incorporate multiple data products into a singlemotion estimation procedure effectively producing surface velocity estimates withan associated uncertainty. This approach brings both improved computational effi-ciency, and greater scalability across observational time-frames when compared toexisting methods. To gauge efficacy, we apply these methods to a set of observa-tions from the Helheim Glacier, a critical actor in contemporary mass loss trendsobserved in the Greenland Ice Sheet. We find that the Helheim glacier exhibitsa mean velocity of approximately 19md−1 and discuss the implications of thesemethods as they pertain to ongoing efforts to characterize the Greenland Ice Sheetand its contributions to global mean sea level rise.