Abstract
We present Glacier Image Velocimetry (GIV), an open-source and easy-to-use software toolkit for rapidly calculating high-spatial-resolution glacier velocity fields. Glacier ice velocity fields reveal flow dynamics, ice-flux changes, and (with additional data and modelling) ice thickness. Obtaining glacier velocity measurements over wide areas with field techniques is labour intensive and often associated with safety risks. The recent increased availability of high-resolution, short-repeat-time optical imagery allows us to obtain ice displacement fields using "feature tracking"based on matching persistent irregularities on the ice surface between images and hence, surface velocity over time. GIV is fully parallelized and automatically detects, filters, and extracts velocities from large datasets of images. Through this coupled toolchain and an easy-to-use GUI, GIV can rapidly analyse hundreds to thousands of image pairs on a laptop or desktop computer. We present four example applications of the GIV toolkit in which we complement a glaciology field campaign (Glaciar Perito Moreno, Argentina) and calculate the velocity fields of small mid-latitude (Glacier d'Argentière, France) and tropical glaciers (Volcán Chimborazo, Ecuador), as well as very large glaciers (Vavilov Ice Cap, Russia). Fully commented MATLAB code and a stand-alone app for GIV are available from GitHub and Zenodo Van Wyk de Vries.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2115-2132 |
| Number of pages | 18 |
| Journal | Cryosphere |
| Volume | 15 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 28 2021 |
Bibliographical note
Funding Information:Financial support. This research has been supported by the United
Funding Information:
Acknowledgements. Maximillian Van Wyk de Vries was supported by a University of Minnesota College of Science and Engineering fellowship. Ben Popken assisted with early testing of GIV. Emi Ito, Kelly MacGregor, Jeff La Frenierre, Matias Romero, Shanti B. Pen-prase, Jabari Jones, and Kerry L. Callaghan provided comments on this manuscript. David Carchipulla helped improve image-download workflows. Conversations about feature tracking with Whyjay Zheng, Shashank Bhushan, Will Kochtitzky, and David Shean have helped refine the ideas in this paper and in GIV’s code. We acknowledge Ted Scambos and two anonymous referees for thoughtful reviews which improved both the manuscript and the associated toolbox. We further thank editor Harry Zekollari for detailed suggestions which were valuable for fine-tuning our text and figures. This material is based upon work supported by the National Science Foundation under grant no. EAR-1714614, coordinated by lead PI Maria Beatrice Magnani.
Publisher Copyright:
© 2021 Author(s).
