The Cryosphere, 9, 1–11, 2015
www.the-cryosphere.net/9/1/2015/
doi:10.5194/tc-9-1-2015
© Author(s) 2015. CC Attribution 3.0 License.
UAV photogrammetry and structure from motion to assess calving
dynamics at Store Glacier, a large outlet draining the Greenland ice
sheet
J. C. Ryan1, A. L. Hubbard2, J. E. Box3, J. Todd4, P. Christoffersen4, J. R. Carr1, T. O. Holt1, and N. Snooke5
1Centre for Glaciology, Institute of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK
2Department of Geology, University of Tromsø, 9037 Tromsø, Norway
3Geological Survey of Denmark and Greenland, Copenhagen, Denmark
4Scott Polar Research Institute, University of Cambridge, Cambridge, UK
5Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK
Correspondence to: J. C. Ryan (jor44@aber.ac.uk)
Received: 29 March 2014 – Published in The Cryosphere Discuss.: 28 April 2014
Revised: 25 August 2014 – Accepted: 25 November 2014 – Published: 6 January 2015
Abstract. This study presents the application of a costeffective,
unmanned aerial vehicle (UAV) to investigate calving
dynamics at a major marine-terminating outlet glacier
draining the western sector of the Greenland ice sheet. The
UAV was ﬂown over Store Glacier on three sorties during
summer 2013 and acquired over 2000 overlapping, geotagged
images of the calving front at an ∼ 40 cm ground
sampling distance. Stereo-photogrammetry applied to these
images enabled the extraction of high-resolution digital elevation
models (DEMs) with vertical accuracies of ± 1.9 m
which were used to quantify glaciological processes from
early July to late August 2013. The central zone of the calving
front advanced by ∼ 500 m, whilst the lateral margins remained
stable. The orientation of crevasses and the surface
velocity ﬁeld derived from feature tracking indicates that lateral
drag is the primary resistive force and that ice ﬂow varies
across the calving front from 2.5 m d−1 at the margins to in
excess of 16 m d−1 at the centreline. Ice ﬂux through the
calving front is 3.8 × 107 m3 d−1, equivalent to 13.9 Gt a−1
and comparable to ﬂux-gate estimates of Store Glacier’s annual
discharge. Water-ﬁlled crevasses were present throughout
the observation period but covered a limited area of between
0.025 and 0.24 % of the terminus and did not appear
to exert any signiﬁcant control over fracture or calving. We
conclude that the use of repeat UAV surveys coupled with
the processing techniques outlined in this paper have great
potential for elucidating the complex frontal dynamics that
characterise large calving outlet glaciers.
1 Introduction
Observational and modelling studies have demonstrated that
Greenland’s marine outlet glaciers have a complex and potentially
non-linear response to both environmental forcing
(e.g. Vieli et al., 2000; Benn et al., 2007; Holland et al., 2008;
Howat et al., 2010; Hubbard, 2011; Joughin et al., 2012; Walter
et al., 2012; Carr et al., 2013) and to changes in front position
(Howat et al., 2007; Luckman et al., 2006; Joughin et
al., 2008). To quantify these processes and feedbacks, regular
and accurate high-resolution measurements are required to
capture the key spatio-temporal linkages between rates of ice
calving, ﬂow, surface lowering and frontal advance/retreat.
Despite signiﬁcant advances in satellite remote sensing, limitations
of spatial resolution (e.g. MODIS) and/or frequency
of repeat imagery (e.g. Landsat or TerraSar-X) render detailed,
day-to-day analysis of calving-front dynamics unfeasible.
On the other hand, acquisition of digital imagery
from unmanned aerial vehicles (UAVs) combined with the
development of stereo-photogrammetry software has enabled
the provision of high-resolution 3-D georeferenced
data on demand for geoscience applications (e.g. d’OleireOltmanns
et al., 2012; Hugenholtz et al., 2012, 2013; Whitehead
et al., 2013; Lucieer et al., 2014). This represents a
cost-effective technique technique for acquiring aerial data
in remote, hazardous and/or inaccessible regions and recent
applications for emerging snow and ice investigation
abound the web (e.g. see the highly informative site of Matt
Published by Copernicus Publications on behalf of the European Geosciences Union.
2 J. C. Ryan et al.: UAV photogrammetry and structure from motion
Table 1. Attributes of the ﬂight surveys and image acquisition of
the UAV.
Interval Glacier Resolution
Flight between No. coverage of DEM
no. Date pictures (s) images (km2) (cm/pixel)
1 1 July 1.55 611 3.17 40
2 2 July 1.51 1051 4.95 38
3 23 August 2.36 567 5.02 39
Nolan; http://www.drmattnolan.org/photography/2013/). To
date, published (peer-reviewed) application appears to be
limited to the investigation of inter-annual changes of a landterminating
glacier on Bylot Island, Canadian Arctic (Whitehead
et al., 2013).
Between July and August 2013, an off-the-shelf, ﬁxed
wing UAV equipped with a compact digital camera ﬂew three
sorties over the calving front of Store Glacier, West Greenland.
The aerial photographs obtained during these ﬂights
were used to produce high-resolution (∼ 40 cm; Table 1) digital
elevation models (DEMs) and orthophotos of the glacier
terminus. These data allowed for the investigation of the spatially
complex and time-varying glaciological processes operating
at the glacier’s calving front. The aim of this paper is
to
1. detail the UAV, in terms of its payload and camera settings,
and its speciﬁc deployment to Store Glacier;
2. describe the techniques used for processing the aerial
images and quantifying glaciological processes;
3. discuss the signiﬁcance of the data we obtained which
includes calving events, the character, orientation and
morphology of crevasses, surface velocities, ice discharge
and changes in thickness and position of the
calving front.
2 Data and methods
2.1 Study site
Store Glacier is a large marine-terminating (tidewater) outlet
glacier located in the Uummannaq district of West Greenland
(Fig. 1). The calving front has a width of 5.3 km and an aerial
calving front (freeboard) of up to 110 m a.s.l. (Ahn and Box,
2010). Aerial photography from 1948 onwards reveals that
Store Glacier’s frontal position has remained stable over the
last 65 years (Weidick, 1995). Seasonally, the calving front
exhibits advance and retreat of up to 400 m (Howat et al.,
2010). The study here focuses speciﬁcally on glacier dynamics
during the melt season under open-water, tidal modulation
of ice ﬂow.
Figure 1. (a) A typical UAV sortie over Store Glacier. The background
map is a Landsat 8 true colour image from 12 June 2013.
The red line shows the UAV ﬂight path on the 2 July 2013. (b) Location
of Store Glacier in the Uummannaq region, West Greenland
on a MODIS mosaic image of Greenland (Kargel et al., 2012).
2.2 UAV platform
The UAV airframe is an off-the-self Skywalker X8 (www.
hobbyking.com) which has a wingspan of 2.12 m and is
made from expanded polypropylene (EPP) foam (Fig. 2). For
this deployment, the X8 was powered by two 5Ah four-cell
(14.8 V) lithium polymer batteries driving a 910 W brushless
electric motor turning an 11 × 7 foldable propeller. In this
conﬁguration, the X8 has a ﬂying mass of ∼ 3 kg (including
1 kg payload), which allows for a cruising speed of around
55–70 km per hour with a maximum range of ∼ 60 km in benign
conditions at constant altitude. A small propeller/highrevolution
motor combination was chosen to provide maximum
instantaneous thrust to ensure a clean launch (for
novice operators) and to handle the potentially strong katabatic
winds encountered during its 40 km sortie.
The autopilot is an open-source project called Ardupilot
(http://ardupilot.com/) based on an Atmel 2560 8 bit microcontroller
and standard radio control parts including 2.4 GHz
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J. C. Ryan et al.: UAV photogrammetry and structure from motion 3
Figure 2. Flowchart of the control set-up and picture of the UAV at
base camp with the relative novices.
radio control and pulse-width modulation (PWM) controlled
servos for aileron and elevon control (Fig. 2). Ardupilot implements
a dual-level proportional-integral-derivative (PID)
controller architecture. The lower level controls ﬂight stabilisation
and the higher level controls based navigation. Tuning
of the PID parameters is necessary to suit the mass and dynamics
of the airframe to ensure accurate stabilisation without
pitch/roll oscillation (lower-level controller) or ﬂightpath
weaving (higher-level controller). The autopilot allows
the UAV to ﬂy autonomously according to a pre-programmed
ﬂight path deﬁned by a series of 3-D waypoints chosen by
the user. The autopilot utilises a GPS for navigation, a triple
axis accelerometer and gyro for stabilisation and a barometric
pressure sensor for altitude control. These parameters are
logged to memory at 10 Hz throughout the ﬂight (Fig. 2).
The advantage of this package is that it can be assembled
within a day from off-the-shelf parts and is cost effective
at less than USD 2000. The X8 is also relatively straightforward
to ﬂy, robust, easily repairable and ﬂoats, all added
bonuses when being deployed in remote areas by potential
novices. Furthermore, the Ardupilot ﬁrmware is open source
and hence can be programmed for speciﬁc requirements, for
example camera triggering (see below).
Two lightweight digital cameras were tested at the ﬁeld
site: a Panasonic Lumix DMC-LX5 10.1 megapixel (MP)
camera with a 24 mm wide-angle zoom lens and a 16.1 MP
Sony NEX-5N with a 16 mm ﬁxed focal length lens though
results presented here are limited to the former. A SPOT GPS
tracking device was also included in the payload to facilitate
recovery should a mission fail (which it did). The focal length
of the Lumix lens was adjusted to 5.1 mm (35 mm equivalent)
to allow the widest possible coverage which gave the camera
a 73.7◦ horizontal and 53.1◦ vertical ﬁeld of view. A short
exposure time of 1 / 1600 and a focal ratio of 8 were chosen
to prevent overexposure and blurring of the ice surface. The
Ardupilot open-source code was amended to trigger the camera
automatically at user deﬁned time or distance intervals at
or between certain waypoints. The cameras were mounted
pointing downwards within the airframe using neoprene and
velcro straps to dampen vibration in a custom recessed aperture
cut in the bottom with a UV ﬁlter to protect the lens and
seal it.
2.3 Flight planning
The open-source software APM Mission Planner (http://
plane.ardupilot.com/) was used for ﬂight waypoint manipulation
and planning in conjunction with the 30 m Greenland
Mapping Project (GIMP) DEM (Howat et al., 2014). To optimise
spatial coverage against required resolution, ﬂight endurance
and stability, the UAV was programmed to ﬂy at a
constant altitude of 500 m a.s.l. (Fig. 1). Based on the camera’s
focal length and ﬁeld of view (53.1◦ by 73.7◦), the
ground (sea-level) footprint at 500 m a.s.l. for each photo was
∼ 450 × 750 m. To ensure coverage of the entire glacier terminus
and overlap for successful photogrammetric processing,
the four transects broadly parallel to the calving front
were ﬂown with ∼ 250 m separation yielding a side overlap
between photos of 70 % (Fig. 1). The mean ground speed
of the UAV was ∼ 70 km h−1 and the camera trigger interval
was adjusted between surveys. On ﬂights 1 and 2, the
interval between camera triggers was 1.5 s corresponding to
a forward overlap of 94 % and over 1000 geotagged images
acquired. Flight 3 had a 2.4 s interval yielding a 90 % forward
overlap and 581 images (Table 1).
UAV operations were based out of a ﬁeld camp with the
advantage of a 50 m area of ﬂat alluvial terrace with relatively
boulder and bedrock free ground for manual remotecontrol
take-off and landing. This location did, however, require
a ∼ 10 km transit to the calving front over a 450 m high
peninsula which signiﬁcantly reduced the useful endurance
over the target. Of the six sorties ﬂown over outlet glaciers in
the region during July and August 2013, the three over Store
Glacier were most successful. Each sortie was 40 km long
and ∼ 35 min in duration after the UAV had attained its operating
altitude at the start of the mission and was passed from
manual remote-control mode into autopilot mode (Fig. 1).
Visual and remote-control contact is lost within a few kilometres
of the UAV being placed in autopilot mode; hence,
validation of the mission plan is essential.
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4 J. C. Ryan et al.: UAV photogrammetry and structure from motion
Figure 3. (a) Surface elevation difference between two DEMs collected
on 1 July and 2 July. Red areas show elevation loss whilst
blue areas show elevation gain. White circles highlight the calving
events that occurred between the two UAV surveys. (b) The position
of the calving front of Store Glacier during the summer of 2013. (c)
Calving-front retreat observed between 12 June and 1 July. Inset
is an orthorectiﬁed image of the water-ﬁlled crevasses observed on
1 July with a pixel resolution of 30 cm. (d) Calving-front advance
observed between 1 July and 23 August. Inset is an orthorectiﬁed
image showing water-ﬁlled crevasses observed on 23 August. The
coverage and size of water-ﬁlled crevasses is smaller.
2.4 Three-dimensional model generation
Three-dimensional data were extracted from the aerial photos
using Agisoft PhotoScan Pro software (Agisoft LLC,
2013). This software’s strength lies in its ability to fully automate
workﬂow and enables non-specialists to process aerial
images and produce 3-D models which can be exported as
georeferenced orthophotos and DEMs (e.g. Figs. 3 and 6).
The ﬁrst stage of processing is image alignment using the
structure-from-motion (SfM) technique. SfM allows for the
reconstruction of 3-D geometry and camera position from a
sequence of two-dimensional images captured from multiple
viewpoints (Ullman, 1979). PhotoScan implements SfM
algorithms to monitor the movement of features through a
sequence of multiple images and is used to estimate the location
of high-contrast features (e.g. edges), obtain the relative
location of the acquisition positions and produce a sparse 3D
point cloud of those features. The Ardupilot ﬂight logs of
the onboard navigation sensors allow the camera positions
and the 3-D point cloud to be georeferenced within instrument
precision. SfM also enables the camera calibration parameters
(e.g. focal length and distortion coefﬁcients) to be
automatically reﬁned; hence, there is no need to pre-calibrate
the cameras and lens optics (Verhoeven, 2011).
Once the photos have been aligned, a multi-view reconstruction
algorithm is applied to produce a 3-D polygon mesh
which operates on pixel values rather than features and enables
the ﬁne details of the 3-D geometry to be constructed
(Verhoeven, 2011). The user determines the precision of the
ﬁnal 3-D model based on image resolution and pixel footprint.
A medium quality setting was chosen yielding DEMs
with between 38 and 40 cm/pixel ground sampling resolution
(GSD), which were resampled to a Cartesian 50 cm
grid to enable intercomparison (Table 1). Higher resolutions
(< 30 cm GSD) are attainable but the increase in computational
time and the accuracy of georeferencing limits the beneﬁts
of such apparent precision.
Two problems of accuracy were encountered in DEM production:
(1) PhotoScan failed to reconstruct a ﬂat sea level
of constant elevation, and (2) relative positional errors between
the DEMs constructed from different sorties were up
to 17.12 m horizontally and 11.38 m vertically. Positional errors
were due to the speciﬁed limits of the onboard L1 GPS
of ± 5.0 m horizontally and, when combined with the barometric
sensor, to a similar accuracy vertically. These were
compounded by the time lag between the camera triggering
and actual photograph acquisition. Hence, a secondary
stage of processing was carried out which involved 3-D coregistration
of the DEMs. To do this, the horizontal and vertical
coordinates of common control points (CPs) based on distinct
features such as cliff bases, large boulders and promontories
were extracted from the georeferenced orthoimages.
The CPs that were at sea level were nominally given elevation
values of zero, re-imported into PhotoScan and subsequently
reprocessed along with a geodetic GPS ground
CP located at 70.401◦ N, −50.665◦ E and 335.85 m altitude
on the bedrock headland overlooking the glacier’s northern
ﬂank. During this secondary stage of processing, PhotoScan’s
optimisation procedure was run to correct for possible
distortions. After processing with the CPs, a ﬂat sea level
across the glacier front was produced and the relative errors
between the three DEMs were reduced to ± 1.41 m horizontally
and ± 1.90 m vertically. The georeferenced 3-D DEMs
and orthophotos were then exported at 50 cm pixel size for
further analysis in ArcGIS and ENVI software packages.
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J. C. Ryan et al.: UAV photogrammetry and structure from motion 5
2.5 Analysis
Changes in calving-front positions were obtained from these
data combined with a Landsat 8 panchromatic image obtained
on 12 June (Fig. 3b). Each calving-front position was
digitised according to the procedure outlined by Moon and
Joughin (2008), whereby a polygon of the calving-front retreat
or advance is digitised and divided by the width of the
glacier. This method has been used in previous studies (e.g.
Howat et al., 2010; Schild and Hamilton, 2013) and enables
intercomparison of results. Surface elevation change was calculated
from the residual difference of the DEMs (Fig. 3a).
Ice ﬂow across the terminus region was calculated by
feature tracking performed on successive DEMs using the
ENVI Cosi-CORR software module (Fig. 4b). These velocities
were then used to estimate ice ﬂux through the calving
front for the same period under the assumption of plug ﬂow
(uniform velocity proﬁle with depth) and using a calvingfront
cross section obtained from Xu et al. (2013) and modiﬁed
by single and multi-beam echo sounder bathymetry obtained
by S/V Gambo in 2010 and 2012 (Chauché, unpublished).
The frontal cross section was divided into 10 m vertical
strips and under the plug-ﬂow assumption, each was assigned
its corresponding horizontal velocity (Fig. 4a). The
ﬂoatation depth and buoyancy ratio across the calving front
was calculated using the ice surface (freeboard) elevation
and total ice thickness with a value for the density of ice of
917 kg m−3 and for sea water of 1028 kg m−3 (Fig. 5a).
To investigate the distribution and patterns of crevassing,
each DEM was Gaussian ﬁltered at 200 pixels (100 m) in
ArcGIS and subtracted from the original DEM to yield the
pattern of negative surface anomalies. These anomalies were
converted into polygons to map and hence quantify crevasse
distribution and character (Fig. 6a). The resulting polygons
were enclosed by a minimum bounding rectangle, which allowed
the orientation, width, length and depth of crevasses
to be extracted (Fig. 6a, Table 2). Water-ﬁlled crevasses were
automatically located in the ENVI package using the supervised
maximum likelihood classiﬁcation (MLC) method.
Representative training samples for water-ﬁlled areas were
chosen from the colour composite orthophoto (Fig. 6b). The
trained tool then classiﬁes pixels that are interpreted as water
into the desired class. The resulting raster image was converted
into a shapeﬁle and used to mask and deﬁne the area of
the water-ﬁlled crevasses across the terminus. These procedures
allow thousands of crevasses in multiple orthoimages
and DEMs to be quantiﬁed easily without the difﬁculties and
dangers associated with direct ﬁeld measurements.
2.6 Uncertainties and limitations
The relative horizontal uncertainties between the DEMs were
investigated by feature tracking the stationary bedrock at the
sides of the glacier. The root mean square (rms) horizontal
displacement was ± 1.41 m which provides us with an
Figure 4. (a) Surface elevation changes between 2 July and 23 August.
An average thinning of 0.12 m d−1 was estimated for the surveyed
area. (b) The ice-ﬂow speed structure of the terminus of Store
Glacier between 1 and 2 July 2013. The centre of the glacier ﬂows at
approximately 16 m d−1 whilst the margins ﬂow less than 5 m d−1.
Dotted white lines show the lateral margins of the glacier. The black
line represents the locations of the horizontal velocity and surface
elevation values that were used to estimate ice ﬂux. The white line
represents the location of the depth values used to estimate ice ﬂux.
The cross section of the calving front derived from these proﬁles is
displayed in (a).
approximate error estimate. The relative vertical uncertainties
between the DEMs were estimated by calculating elevation
differences between bedrock areas, which revealed an
error estimate of ± 1.9 m. The two-stage procedure outlined
in Sect. 2.4 therefore enabled us to improve the relative positional
uncertainties from nearly 20 m to less than 2 m. For
future studies, it is thought that several CPs on the bedrock
either side of the glacier front would further reduce these uncertainties.
A telemetric differential GPS deployed on or near
the calving front, which is sufﬁciently large/bright to identify
within the aerial imagery would allow further ground control
in the centre of DEMs, away from bedrock CPs.
Due to the lack of reﬂected light from deep crevasse recesses,
the DEM generation process cannot quantify the narrowest
sections of all fractures and resultant crevasse depths
are therefore a minimum estimate. The technique is also
clearly limited to line of sight precluding narrow fractures
which extend for tens of centimetres horizontally and potentially
up to a few metres vertically (Hambrey and Lawson,
2000; Mottram and Benn, 2009).
Finally, there are a number of practical difﬁculties when
operating an autonomous aircraft in remote and inaccessible
environments. Mission planning is critical; knowledge of the
local weather conditions, as well as up-to-date satellite imagery
and DEMs are a prerequisite.
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6 J. C. Ryan et al.: UAV photogrammetry and structure from motion
Table 2. Attributes of mean crevasse width, length and orientation
in each zone labelled in Fig. 5. Orientations are measured along
the long axis of each crevasse with respect to the direction of ﬂow
which is 0◦.
Mean Mean Mean
Zone width (m) length (m) orientation (◦)
Zone 1 3.6 9.4 9.2
Zone 2 4.8 14.0 36.7
Zone 3 10.5 32.6 85.1
Zone 4 6.5 17.8 60.4
Zone 5 3.5 8.5 10.8
3 Results
Three successful UAV sorties were ﬂown over Store Glacier
calving front providing imagery, orthophotos and DEMs on
1 and 2 July and the 23 August, herein referred to as ﬂights
and associated products 1 to 3, respectively (Table 1). The
interval between ﬂights 1 and 2 was 19 hours and comparison
between these outputs enables identiﬁcation of processes
operating over a daily (short) timescale, be it a very speciﬁc
snapshot. The third sortie was ﬂown 52 days later and comparison
between these outputs enables investigation of lateseasonal
change. The footprint of the four cross-glacier transects
ﬂown extends just over 1 km upstream from the calving
front and herein is referred to as the terminus.
3.1 Short timescale calving and surface elevation
change
Residual elevation change between 1 and 2 July (Fig. 3a) reveals
that the front retreated in two sections by up to 50 and
80 m, respectively. The more northerly calving event (A) resulted
in a 450 m wide section of the terminus retreating by
between 20 and 50 m, whilst event B produced between 20
and 80 m of retreat across a 400 m section (Fig. 3a). In addition
to these two calving events (which are discussed in section
3.6), the central 4.5 km frontal section advanced between
12 to 16 m (Fig. 3a). At its lateral margins, the calving front
shows no discernible systematic change though there are isolated,
small calving events, for example, within 50 m of the
southern ﬂank (Fig. 3a). Upstream of the calving front, there
is no net change in mean surface elevation away from the
front and the dappled pattern of residual elevation change is
a result of the advection of crevasses and seracs. Successive
long proﬁles of the terminus between the 1 and 2 July reveal
speciﬁc down-glacier crevasse advection with ﬂow (Fig. 6)
at a rate of 5 and 16 m d−1 on proﬁle 1 and 2, respectively.
These results provide corroboration for the surface velocities
derived by feature tracking in Sect. 3.4.
3.2 Seasonal timescale calving-front position and
surface elevation change
Over the entire melt season, larger ﬂuctuations in calvingfront
position are observed (Fig. 3b). Over the 19-day period
from 12 June to 1 July, mean frontal retreat was 160 m
(Fig. 3c) and between 2 July and 23 August, the calving
front advanced by an average of ∼ 110 m to a position similar
to that in 12 June (Fig. 3d). These mean values, however,
do not convey the full extent and detail of the changes observed
in the calving front. For example, the central section
of the calving front retreated by up to 525 m between the
12 June and 1 July and advanced by up to 450 m between
2 July and 23 August (Fig. 3b). Furthermore, the lateral margins
of Store Glacier (the southern 850 m and the northern
1.5 km) are relatively stable with < 50 m change in position.
Over the 52-day period between 2 July (Flight 2) and
23 August (Flight 3) widespread surface lowering of 6.1 m
(or 0.12 m d−1) was observed across Store Glacier terminus
(Fig. 4a), which is signiﬁcantly larger than the estimated vertical
uncertainties of the DEMs (± 1.9 m). Despite the same
dappled patterns caused by local advection of crevasses and
seracs, we infer this to be associated with dynamic thinning
1 km upstream of the calving front, which is discussed in
Sect. 4.2.
3.3 Bathymetry
The deepest sector of the calving front is located 1 km south
of the centreline and exceeds 540 m below sea level (Fig. 5a).
This 200 m wide sector also corresponds to the greatest thickness
of ∼ 600 m. To the south of this deepest point, the bottom
rises rapidly to a 200 m deep shelf located 500 m from
the ﬂank. To the north of the deepest point, the bottom shallows
more gently to within 400 m where it becomes steeper
towards the fjord wall.
3.4 Surface velocities
Maximum surface-ﬂow velocities of 16 m d−1 between 1
and 2 July are consistent with results obtained in previous
studies using other techniques, such as feature tracking images
from a land-based time-lapse camera (between 11 and
15 m d−1) (Ahn and Box, 2010; Walter et al., 2012). The
spatial pattern of surface ﬂow from feature tracking of images
between the 1 and 2 July varies considerably across
the terminus of Store Glacier (Fig. 4b) attaining velocities
of 16 m d−1 (5.8 km a−1) near the centre of the glacier down
to 2.5 m d−1 at the lateral ﬂanks. Surface velocities are related
to slope, depth, thickness and distance from the lateral
margins (Fig. 5c, d). As would be expected, maximum velocities
correlate with maximum depth and towards the northern
ﬂank are linearly correlated (R2 = 0.90) with frontal depth
(Fig. 5c). Towards the southern ﬂank the relationship is less
apparent especially between 200 and 350 m depths. There
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J. C. Ryan et al.: UAV photogrammetry and structure from motion 7
Figure 5. (a) Proﬁles showing the sea ﬂoor bathymetry and ice surface
elevation at the calving front. These data were combined with
surface velocities to estimate the ice ﬂux of Store Glacier. Where the
ﬂoatation percentage is over 100 %, it is assumed that the ice is not
thick enough to be fully grounded in hydrostatic equilibrium. (b)
The relationship between effective basal shear stress and velocity.
(c) The relationship between depth and velocity. At depths deeper
than 400 m, velocities are fairly constant. The two differing relationships
between 150 and 350 m represent velocities from different
sides of the glacier. (d) Relationship between velocity and distance
from the lateral margins. The positive correlation demonstrates the
importance of the resistance provided by the fjord walls.
is a strong correlation between velocities and distance from
the lateral margins which can be approximated by a power
function (R2 = 0.90) (Fig. 5d). Although application of the
ﬂoatation criteria reveals parts of calving front to be buoyant
(Fig. 5a), side-scan sonar observations reveal that the glacier
toe was resting on the fjord bed (Chauché, unpublished).
When the surface ﬂow pattern is combined with frontal
bathymetric data we estimated that the mass ﬂux through the
calving front of Store Glacier was 3.8 × 107 m3 d−1, equivalent
to ∼ 13.9 Gt a−1.
Seasonal ﬂow patterns were not obtainable between 2 July
and 23 August as the majority of any matching features
within the study area required for tracking had already calved
into the ocean. Furthermore, it is likely that the morphology
of many crevasses and seracs will have changed signiﬁcantly
through melt and deformation and would not be recognised
by the cross-correlation procedure.
3.5 Crevassing
The morphology and orientation of crevasses varies
markedly across the terminus (Fig. 6). The largest crevasses
occur in a sector south of the glacier centre line in zone 4
(Fig. 6, Table 2). Here, crevasses have mean minimum depths
of 18 m, lengths of 68 m and widths of 31 m. The largest
crevasses are up to 30 m deep, over 500 m long and nearly
200 m wide but no crevasses that penetrated below sea level
were identiﬁed. Most crevasses in this region are arcuate with
limbs pointing towards the calving front and are orientated
obliquely to the direction of ice ﬂow (Fig. 6). This arcuate
morphology of crevasses continues across the central 3 km of
the terminus in zone 3 (Fig. 6). Here, crevasses have mean a
depth of 10.5 m, length of 50 m and widths of 18 m (Table 2).
In zone 2, 300 to 500 m from the northern ﬂank, crevasses are
aligned obliquely to the direction of ice ﬂow (30–45◦). Up to
the fjord walls in zones 1 and 5, crevasses are generally orientated
parallel to the ice ﬂow (> 15◦) (Fig. 6, Table 2) and
are much smaller with a mean lengths of 22 m and width of
8 m (Table 2). No discernible difference in average crevasse
depths, lengths or widths was observed between early July
and late August and the pattern and character of crevassing
was also similar.
Water-ﬁlled crevasses were clustered in zone 4, coinciding
with the sector of larger crevasses (Fig. 6b). Water-ﬁlled
crevasses covered 12 000 m2 or 0.24 % of the survey area (to
∼ 1 km from the calving front) on 2 July (Table 1). Some
42 individual water-ﬁlled crevasses were identiﬁed with the
largest having an area of 1200 m2. By 23 August, the number,
size and total area of water-ﬁlled crevasses were lower: only
10 water-ﬁlled crevasses could be identiﬁed, the largest of
which was 400 m2 and with a total area of 1230 m2 (0.025 %
of the survey area). We were not able to ascertain the depth of
water in the crevasses as no common crevasses could be identiﬁed
which drained or ﬁlled between ﬂights but this would
be a speciﬁc aim of future studies which, with regular sorties,
could potentially determine the depth of a crevasse before
ﬁlling or after drainage or otherwise exploit the light
reﬂectance relationship with water depth (e.g. Fitzpatrick et
al., 2014).
Successive proﬁles of the terminus from 1 and 2 July
demonstrate how the UAV surveys are capable of capturing
the displacement of crevasses, which advect downstream
at a rate of 5 and 16 m d−1 in proﬁles 1 and 2, respectively
(Fig. 6). The techniques used in this study are therefore capable
of identifying changes in crevasses geometry, particularly
width and depth through time.
3.6 Calving events
The two calving events identiﬁed between 1 and 2 July appear
to take place under contrasting conditions. Event A consisted
of the calving of multiple, relatively small ice blocks
with the glacier failing along two main crevasses located 30
and 50 m behind the calving front. These crevasses were between
8 and 10 m deep, respectively, and in this instance,
the crevasses located closest to the front were the ones that
failed. Event B appears to be a single large event caused by
the fracturing of a series of parallel crevasses which were
up to 14 m deep and 60 m behind the calving front. Unlike,
calving event A, the crevasses that failed in event B were
not the closest to the calving front. Indeed, there were other
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8 J. C. Ryan et al.: UAV photogrammetry and structure from motion
crevasses that were deeper and located nearer to the front, yet
did not calve. Water was not observed in any of the crevasses
along which calving took place.
4 Discussion
4.1 Changes occurring over a daily timescale
The orientation of crevasses suggests that lateral drag is an
important resistive stress on Store Glacier. The lateral margins
of Store Glacier are characterised by crevasses that are
orientated parallel to the direction of ﬂow which suggests that
they have formed in response to simple shear stresses associated
with the drag of the fjord walls (Fig. 6) (Benn and Evans,
2010). The importance of lateral drag is further demonstrated
by the morphology of crevasses found near the glacier ﬂow
line (Fig. 6). Their arcuate nature indicates that the principal
tensile stresses operating on the ice have been rotated by
lateral gradients in ice velocity. These gradients are caused
by the simple shear stress between the fjord walls and the
margins of the glacier which cause the ice to ﬂow slower
(Fig. 4b) (Benn and Evans, 2010).
The simple shearing caused by velocity gradients is further
demonstrated by the differing relationship between velocity
and depths between the north and south side of the
glacier (Fig. 5c, d). On the north side, the velocity increases
gradually from the fjord wall to the centre of the glacier,
reﬂecting the gradual deepening of bathymetry and the resulting
decrease of basal and lateral drag. On the south side,
the velocities are higher than the north side for given depths
and distances from the lateral margins (Fig. 5c, d). We hypothesise
that, because the deepest part of the glacier is situated
1 km south of the centreline, the ice on south side is
more inﬂuenced by faster ﬂowing ice which exerts a simple
shear stress on the shallower, adjacent ice (250–400 m thick).
This causes the shallow ice to ﬂow faster than ice with similar
thicknesses and distance from the lateral margins on the
north side (Fig. 5c).
The mass ﬂux through the calving front was calculated at
3.8 × 107 m3 d−1 which needs to be balanced by three main
frontal processes: calving, submarine melting and advective
advance. Both calving and advance were observed in this
study but it is likely that submarine melting also has a large
role in ice output at a daily timescale. For example, Xu et
al. (2013) used oceanographic data to calculate a melt water
ﬂux of between 0.5 and 1.1 × 107 m3 d−1 from Store Glacier
in August 2010 equivalent to 13–29 % of the mass ﬂux calculated
by our study. For comparison, Rink glacier has an
ice ﬂux of 3.0 × 107 m3 d−1 of which 27 % is estimated to
be lost through submarine melting each day (Enderlin and
Howat, 2013).
Figure 6. (a) Distribution and patterns of crevasses on Store Glacier.
Dry crevasses, which are large structural features, are shown in orange.
Narrower crevasses that are observed in the orthorectiﬁed images
but whose 3-D geometry is not constructed are shown in black.
The areas of water-ﬁlled crevasses are shown in blue and occur almost
exclusively in zone 4. The regions of the terminus discussed
are designated by the dotted red lines and are referred to as the
black numbers. Transects 1 and 2 shown in the inset demonstrate
how crevasses adverted downstream between 1 and 2 July. In T1,
a series of calving events occurred which are discussed as calving
event A. In T2, the calving front advanced 16 m. (b) Illustration of
the terminus of Store Glacier with ellipsoids proportional to the average
length, width and orientation of crevasses shown in (a) for the
respective zones. The colour of the ellipsoids represents the proportion
of crevasses that are water ﬁlled in each zone where WF refers
to water ﬁlled in the legend. The italicised numbers denote the density
of crevasses per 10 m2 in each zone. Arrows illustrate inferred
direction of principal strain.
4.2 Changes occurring over a seasonal timescale
The lack of variation in the position of the lateral margins
of the glacier shows that a balance is maintained between
the ice ﬂux input and submarine melting and calving output
in this zone throughout the melt season. The balance
could be explained by the mechanism of calving events. At
the lateral margins calving is characterised by small, reguThe
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J. C. Ryan et al.: UAV photogrammetry and structure from motion 9
lar events such as calving event A (Fig. 3a). The regularity
of these small events means that any small advance or retreat
is regulated almost instantly by changes in calving rate
which returns the lateral margins of the glacier to the same
position. Calving rate could also be moderated by changes in
the bathymetry. When the lateral margins advance, calving
rates increase due to the abrupt deepening of the bathymetry
seaward of the lateral margins of the glacier which cause
basal drag to be reduced. Ice-ﬂow acceleration can lead
to increased longitudinal stretching and deeper crevassing,
thereby increasing calving rate and leading to retreat to its
original, bathymetrically pinned position.
The centre of the calving front is much more active with
calving and submarine melt rates that vary on a seasonal
timescale. We propose that the main cause of variability is
due to calving rates which are highly irregular throughout
the melt season (Jung et al., 2010). Our observations also
support the suggestion that calving rates are dominated by
major calving events which have a time interval of around
28 days (e.g. Jung et al., 2010). If the calving front advances
for 28 days at 16 m d−1, it will advance ∼ 448 m. A large,
single calving event can therefore yield a retreat of ∼ 448 m
and would explain the variation in the position of the calving
front during the melt season (Fig. 3b). On 25 August 2013,
a tabular iceberg with a length of ∼ 500 m was observed to
calve from the central zone of Store Glacier.
Towards the end of the melt season (23 August), a
widespread surface deﬂation of 0.12 m d−1 was observed
(Fig. 4a). Application of a simple degree-day model reveals
that part of this lowering can be attributed to ablation. Average
daily air temperatures were recorded at an automated
weather station (AWS) located near the UAV launch site
(Fig. 1) and, using a melt factor of 6–10 mm per degree
per day (Hock et al., 2005), surface lowering due to ablation
is estimated between 0.038 and 0.064 m d−1. It follows
that ablation alone cannot account for the entire lowering
rate observed and, hence, we infer an additional component
of dynamic thinning due to relative strain extension across
this zone, related to reduced upstream delivery of ﬂux and/or
frontal kinematics associated with enhanced late-season submarine
melting and/or calving rates. GPS measurements by
Ahlstrom et al. (2013) tentatively support the former interpretation
and reveal that surface velocities 8 km upstream of
Store’s calving front tend to decrease between July and August.
However, this raises questions regarding the timescales
over which dynamic thinning and surface melt occur and
whether or not the ﬂow regime across the terminus is, to
some extent, isolated or operating independent from processes
upstream supplying mass. Either way, these questions
are beyond the scope of the data sets presented here and require
a study of greater areal extent and temporal coverage.
Another important observation is the order of magnitude
reduction of the area of water-ﬁlled crevasses between early
July and late August (Fig. 6). Surface air temperatures directly
inﬂuence the extent of water-ﬁlled crevasses. AWS
data reveal that mean daily air temperature was ∼ 6 ◦C during
the 4 days prior to the UAV sortie on the 2 July. In contrast,
mean temperature was ∼ 3.5 ◦C on the 4 days prior to
the UAV sortie on 23 August. Water-ﬁlled crevasses have
been hypothesised to penetrate deeper than crevasses without
water (Weertman, 1973; van der Veen, 1998) and hence
act as mechanism for calving (Benn et al., 2007). The calving
events observed in this study did not speciﬁcally fail at waterﬁlled
crevasses and hence our limited results show no support
for this mechanism. However, studies of greater scope with
daily coverage will be required to determine deﬁnitively if
water-ﬁlled crevasses have any appreciable impact on calving
dynamics at Store Glacier or elsewhere.
5 Conclusions and future directions
A UAV equipped with a commercial digital camera enabled
us to obtain high-resolution DEMs and orthophotos of the
calving front of a major tidewater glacier at an affordable
price. Airborne lidar currently presents the only alternative
method for acquiring DEMs with comparable accuracy and
precision. However, to ﬂy consecutive sorties in a remote environment
is likely to be prohibitively expensive and with
sufﬁcient ground control points the digital photogrammetry
approach may also exceed the accuracy of this technique.
The three sorties ﬂown enabled key glaciological parameters
to be quantiﬁed at sufﬁcient detail to reveal that the
terminus of Store Glacier is a complex system with large
variations in crevasse patterns surface velocities, calving processes,
surface elevations and front positions at a daily and
seasonal timescale. Surface velocities vary across the terminus
and are inﬂuenced by both basal and lateral drag (Figs. 4b
and 5c, d). The oblique orientation and arcuate nature of
crevasses suggests that the principal extending strain rate is
orientated obliquely to the direction of ﬂow and we therefore
propose that resistive stresses at the terminus of Store
Glacier are dominated by lateral drag (Fig. 6). With this in
mind, the retreat of Store Glacier into a wider trough could
signiﬁcantly increase the ice discharge. We estimated that
the ice ﬂux through the calving front of Store Glacier was
13.9 Gt a−1 and we observed a small terminus advance between
1 and 2 July (Figs. 3a and 5a). This advance reveals
that, during this period, the sum of calving and submarine
melt rates are less than the ice ﬂux. Calving is an irregular
process and that the position of the calving front returned
to its 12 June position by 23 August suggests that over this
timescale calving and submarine melting balance ice ﬂux
(Fig. 3b). Water-ﬁlled crevasses covered 0.24 % of the survey
area on 2 July but this fell to 0.025 % on 23 August (Fig. 6).
It remains to be seen whether water-ﬁlled crevasses are more
likely to initiate calving events but our tentative results here
indicate no support for this mechanism.
Future studies, with more frequent sorties could be used to
compare and investigate further glaciological changes over
www.the-cryosphere.net/9/1/2015/ The Cryosphere, 9, 1–11, 2015
10 J. C. Ryan et al.: UAV photogrammetry and structure from motion
a more continuous timespan. There is also the possibility of
more sophisticated payloads with radiation, albedo and other
multi-band sensors as well as radar and laser altimetry. There
are many potential cryospheric applications for investigation,
such as sea ice, marine and terrestrial-terminating glaciers
and, with increased range, ice sheets, that can be achieved
with the use of repeat UAV surveys. We have demonstrated
that for calving outlet glaciers, a UAV carrying a highresolution
digital camera would be sufﬁcient to investigate
the following projects:
– analysis of the thickness and back stress exerted by the
ice mélange during the winter and the effect of its break
out on glacier ﬂow, calving rate and character;
– seasonal changes in the depth, density, orientation and
nature of crevassing and their impact on calving rate and
character;
– the inﬂuence of daily to seasonal melt and supraglacial
lake drainage on downstream dynamics and calving;
– analysis of daily to seasonal ﬂuctuations in calving ﬂux,
terminus position and impact on upstream dynamics and
thinning.
Acknowledgements. We thank Matt Nolan, Doug Benn and
Mauri Pelto for their thorough and insightful reviews, and Anders
Damsgaard for his short comments: all of which greatly improved
the manuscript. Funding for the ﬁeldwork was made possible
by the UK Natural Environmental Research Council (NERC)
grant NE/K005871/1 (Subglacial Access and Fast Ice Research
Experiment (SAFIRE): Resolving the Basal Control on Ice Flow
and Calving in Greenland). NERC also funded The Cryosphere
page charges. J. C. Ryan is funded by an Aberystwyth University
Doctoral Career Development Scholarship (DCDS). We are also
indebted to the crew of S/V Gambo who worked tirelessly to provide
logistical support, and to the Uummannaq Polar Institute and
Children’s Home who provided accommodation in Uummannaq.
Edited by: A. Kääb
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