Glacier Image Velocimetry: an open-source toolbox for easy and rapid calculation of high-resolution glacier velocity fields

Maximillian Van Wyk De Vries,Andrew D Wickert

doi:10.5194/tc-15-2115-2021

Maximillian Van Wyk De Vries, Andrew D Wickert

Open Access

https://doi.org/10.5194/tc-15-2115-2021

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Abstract

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 (see https://doi.org/10.5281/zenodo.4624831, Van Wyk de Vries, 2021a).

Highlights

Satellite imagery revolutionized our ability to study changes in glacier extent, volume, and surface velocities and is an effective tool for communicating these changes to the broader public (Scambos et al, 1992; Rignot et al, 2011; Heid and Kääb, 2012a; Stocker et al, 2013; Howat et al, 2019)
Deriving glacier velocities from satellite imagery is possible through an image analysis technique known as “feature tracking”, “image cross correlation”, or “particle image ve
Nowadays full 2D flow-velocity maps may be readily calculated from a variety of optical- and radar-based satellite imagery (Heid and Kääb, 2012b; Fahnestock et al, 2016). For this toolbox we focus on optical imagery products due to their ease of access, limited need for pre-processing, and high spatial and temporal resolution (Drusch et al, 2012; Heid and Kääb, 2012b, a; Kääb et al, 2016; Darji et al, 2018)

Summary

Introduction

Satellite imagery revolutionized our ability to study changes in glacier extent, volume, and surface velocities and is an effective tool for communicating these changes to the broader public (Scambos et al, 1992; Rignot et al, 2011; Heid and Kääb, 2012a; Stocker et al, 2013; Howat et al, 2019). Even the earliest glaciologists identified that glaciers may flow as viscous fluids (Forbes, 1840, 1846; Bottomley, 1879; Nye, 1952) and later that glacier surface motions reflect a complex interplay between internal deformation, basal sliding, and deformation of subglacial sediments (Deeley and Parr, 1914; Weertman, 1957; Kamb and LaChapelle, 1964; Nye, 1970; Fowler, 2010) Such changes reflect a combination of glacier mass balance and basal conditions – including time-varying hydrology – both of which may respond to climate. Widespread measurement of glacier surface velocities, a key constraint on glacier dynamics, has only become possible with the advent of satellitebased remote sensing (e.g. Bindschadler and Scambos, 1991; Scambos et al, 1992).

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