2017/11/15 by Douglas Brinkerhoff, Brinkerhoff, Douglas, S. O’Neel +2 · 4 citations
Computer Science · Earth and Planetary Sciences · Environmental Science · Medicine · Physics and Astronomy · #Artificial intelligence #Climatology #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Cryospheric studies and observations #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Forcing (mathematics) #Geodesy #Geography #Geology #Geomorphology #Glacier #Landslides and related hazards #Meteorology #Oblique case #Probabilistic logic #Statistics and Probability (physics.data-an) #Tracking (education) #Winter Sports Injuries and Performance #cs.CV #physics.data-an #physics.flu-dyn
paper · pdf · doi:10.48550/arxiv.1711.05366
published in arXiv (Cornell University) (Cornell University) · 24 pages, 8 figures
arxiv created 2017/11/15 · openalex publication_date 2017/11/15 · arxiv updated 2017/11/16 · openalex created_date 2017/12/04 · openalex updated_date 2026/07/28
We develop a probabilistic method for tracking glacier surface motion based on time-lapse imagery, which works by sequentially resampling a stochastic state-space model according to a likelihood determined through correlation between reference and test images. The method is robust due to its natural handling of periodic occlusion and its capacity to follow multiple hypothesis displacements between images, and can improve estimates of velocity magnitude and direction through the inclusion of observations from an arbitrary number of cameras. We apply the method to an annual record of images from two cameras near the terminus of Columbia Glacier. While the method produces velocities at daily resolution, we verify our results by comparing eleven-day means to TerraSar-X. We find that Columbia Glacier transitions between a winter state characterized by moderate velocities and little temporal variability, to an early summer speed-up in which velocities are sensitive to increases in melt- and rainwater, to a fall slowdown, where velocities drop to below their winter mean and become insensitive to external forcing, a pattern consistent with the development and collapse of efficient and inefficient subglacial hydrologic networks throughout the year.