Using Remote
Sensing to
Determine
Glacier’s Flow
Rate and
Direction
Pyper Dixon
Case Study 1: Satellite-derived volume loss rates and gla
The authors used high-resolution satellites to
calculate the change in elevation of individual
glaciers and the entire Juneau Icefield (JIF) over time
(dh/dt). They took elevation data from Advanced
Spaceborne Thermal Emission and Reflection
Radiometer (ASTER) and Shuttle Radar Topography
Mission (SRTM) (C-band) elevation data.
Fig 1 was created using L-band SAR pixel-tracking
from 5-46 day pairs of images. It has pixel resolution
of 3.3m (azimuth) by 8.3m (range). SAR images are
not limited by cloud cover and are perform well in
snow-covered, high-altitude zones, where optical
images lack trackable features.
Fig 1: Change in height (thickness) of the JIF. Blue
represents accumulation and red represents losses.
Fig 2 was created using synthetic aperture radar
(SAR) image pairs, georeferenced and down-sampled
to a resolution of 300 by 300m. This is operating
under the surface parallel-flow assumption, that all
motion is parallel to the surface gradient of the
glacier. Ground truthing of velocities was done by
taking repeated GPS measurements of over 1000
stakes twice in a given year (within 14 days).
Fig 2: Velocity of glaciers. Purple represents slow
speeds; red represents 1m/day or faster.
Fig 3 shows the speed of the Taku Glacier, a major
glacier flowing from the JIF. The speeds are shown at
different distances moving along a track from south
to north. The GPS recorded velocities are higher
because they were recorded in late July, when the
glacier would be flowing fastest due to melt water
lubricating the bedrock/glacier interface.
Fig 3: Speed of Taku Glacier as measured by GPS,
ASTER and ERS
Case Study 2: Ice surface morphology and
flow on Malaspina Glacier, Alaska:
Implications for regional tectonics in the
Saint Elias orogen
The authors
calculated
flow velocity
using
sequential
imagery and
SAR scenes
taken at
monthly
intervals.
They were
able to
identify
persistent
features on
the glacier by
using several
decades of
Landsat
images.
Persistent
objects on
the glacier
(such as icefall) or on land next to the glacier
(significant geologic feature) become objects of
which to measure glacier flow against.
Surface features were tracked through Landsat TM
images (30m) and Phased Array L-Band Synthetic
Aperture Radar (PALSAR) imagery. Displacements
of the glacier features with nearby stable ground
indicate the alignment of Landsat images and allow
for the calculation of a displacement field.
The velocity vector field was edited through visual
inspection to remove inaccurate velocities.
Fig 4: Movement of the Seward Lobe of the
Malaspina Glacier. The white flow areas represent
two prominent flow paths corresponding with
subglacial valleys.
Case Study 3: Estimation of surface ice
velocity of Chhota-Shigri glacier using subpixel ASTER image correlation
The ASTER images (resolution 30m) are combined
using the selection of tie points, or known points
from each image. Low signal to noise ration (SNR)
points are filtered out to remove poorly correlated
pixels. The ASTER images are paired from 2
sequential years to obtain a yearly velocity.
Fig 5: Overview of Methodology
Fi
Fig 7: Comparison of velocities from two years.
Velocities as calculated from remote sensing and
GPS field data.
Case Study 4: Glacier surface velocity estimation
in the West Kunlun Mountain range from L-band
ALOS/PALSAR images using modified synthetic
aperture radar offset-tracking procedure
The authors used 46 paired images, from 2007, 2008
and 2009 to calculate ice displacement and
subsequently flow velocity. The range resolution for
the pixels is approximately 8m (range) and 3m
(azimuthal).
Fig 7: Surface flow velocities shown in cm/day.
References
Cotton, Michelle M., Ronald L. Bruhn, Jeanne Sauber, Evan
Burgess, and Richard R. Forster. "Ice Surface Morphology and
Flow on Malaspina Glacier, Alaska: Implications for Regional
Tectonics in the Saint Elias Orogen." Tectonics 33.4 (2014): 58195. Web. 25 Nov. 2014.
Melkonian, Andrew K., Michael J. Willis, and Matthew E.
Pritchard. "Satellite-derived Volume Loss Rate and Glacier Speeds
for the Juneau Icefield, Alaska." Journal of Glaciology 60.222
(2014): 743-60. Web. 25 Nov. 2014.
Ruan, Zhixing, Huadong Guo, Guang Liu, and Shiyong Yan.
"Glacier Surface Velocity Estimation in the West Kunlun
Mountain Range from L-band ALOS/PALSAR Images Using
Modified Synthetic Aperture Radar Offset-tracking Procedure."
Journal of Applied Remote Sensing 8.1 (2014): 084595. Web. 25
Nov. 2014.
Tiwari, R. K., R. P. Gupta, and M. K. Arora. "Estimation of
Surface Ice Velocity of Chhota-Shigri Glacier Using Sub-pixel
ASTER Image Correlation." Current Science 106.6 (2014): 85359. Web. 25 Nov. 2014.