See the British Society for Geomorphology Geomorphological Techniques chapter on Glacier Movement for more information on how glacier movement is monitored.
Manual survey: Glacier velocity can be determined manually, using a total station, theodolite, or a dGPS for example, to survey stakes inserted into the glacier surface. This produces accurate measurements that also quantify vertical as well as horizontal movement, which is important for debris-covered glaciers which can be responding to climatic change through surface lowering, rather than terminus retreat.
Manual surveys require repeat travel and access to the galcier surface, which is time consuming, likely to be expensive, and may not be possible in certain areas of the glacier where crevasses are numerous. The spatial and temporal coverage of the survey therefore requires consideration.
Remotely sensed: Semi-automatic workflows using optical and radar imagery can be used to quantify glacier velocity by tracking the displacement between two images of a known time separation (see diagram). This requires that surface features are preserved between the images so the technique performs well on slow moving debris-covered glaciers. The spatial coverage of measurements is also likely to be increased compared to that achievable in a manual survey, including hazardous crevassed areas.
Typical feature tracking workflow for optical imagery.
Velocity of Khumbu Glacier in the Everest region derived from feature tracking on Sentinel-2 imagery.
Velocity field derived for the Batura Glacier using Landsat 7 ETM+ panchromatic scenes and CIAS software, available from: http://www.mn.uio.no/geo/english/research/projects/icemass/cias
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Glacier mass balance studies derive and compare net mass loss and gain over an entire glaciers surface during a given time period. Field-based mass balance surveys require substantial amounts of time and logistical effort to complete, so the geodetic approach is now more commonly used and applied to wide areas. The geodetic method calculates glacier mass balance through glacier wide surface elevation comparisons (Nuth et al., 2007), typically over the period of a few years to decades, using digital elevation models (DEMs). DEMs of very high resolution can be generated using close-range remote sensing techniques, such as laser scanning, or of moderate resolution using satellite imagery. DEMs generated using satellite imagery cover can cover thousands of km2, and so are excellent data sources for assessing glacier mass loss at the catchment scale. Stereoscopic DEMs are generated considering photogrammetric principles (Nuth and Kaab, 2011) using overlapping imagery from sensors such as ASTER, ALOS PRISM, the SPOT satellites and, most recently, the Worldview and Pleiades sensors.
DEM differencing to show surface elevation change over glaciers in the Everest region of the Himalaya, between 2000 and 2015. DEMs of the 2015 land surface were generated from ASTER and Worldview imagery and differenced from the Shuttle Radar Topographic Mission (SRTM) DEM generated in 2000. Elevation difference data have been converted to annual rates of surface elevation change.
When glacier surface DEMs are available for different time periods, the analysis of the difference between them can yield ice-surface elevation change data. The differencing of glacier surface DEMs on a pixel by pixel basis and the subsequent multiplication of elevation differences by pixel area can also give estimates of volumetric changes over the study period. This volume change can then be converted to mass change, a more relevant quantity for climate impact assessments of sea level rise contributions and mountain hydrology (Huss, 2013), through the multiplication with the density of glacier/ firn ice (Racoviteanu et al., 2008; Huss, 2013).
The accuracy of mass-change estimates from DEM-differencing work can be estimated through the analysis of elevation change data over ground thought to be stable over the study period- i.e. off-glacier. When the difference between DEMs used over the study period is minimised in these stable areas, we can be more certain in any more substantial changes over glacier surfaces.
HUSS, M. 2013. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere, 7, 877-887.
NUTH, C., KOHLER, J., AAS, H. F., BRANDT, O. & HAGEN, J. O. 2007. Glacier geometry and elevation changes on Svalbard (1936-90): a baseline dataset. In: SHARP, M. (ed.) Annals of Glaciology, Vol 46, 2007. Cambridge: Int Glaciological Soc.
NUTH, C. & KAAB, A. 2011. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere, 5, 271-290.
RACOVITEANU, A. E., WILLIAMS, M. W. & BARRY, R. G. 2008. Optical remote sensing of glacier characteristics: A review with focus on the Himalaya. Sensors, 8, 3355-3383.
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Satellite sensors can be used to derive ground surface temperature at the time of the overpass. Processing steps to derive the temperature include corrections for atmospheric effects land cover emissivity.
Surface temperature in the Everest region observed from the Landsat 8 Thermal Infrared Sensor.
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Glacial lake/ pond
Glacial lakes can be mapped manually using remotely sensed imagery if sufficient spectral contrast is observable between the surrounding terrain. To permit a standardised comparison between imagery of different times, the Normalised Difference Water Index (NDWI) is commonly applied to multi-spectral imagery (e.g. Landsat). The NDWI uses the difference between high water reflectance at green or blue wavelengths and low reflectance at near infrared wavelengths to distinguish water from the surrounding land. The accuracy is dependent upon this contrast and the threshold selected to separate water from land, and also the resolution of the imagery, which determines the size of lake that can be mapped and the area of mixed pixels that are included. Mixed pixels cross the water-shore boundary so have a spectral signature incorporating both land and water. Coarser resolution data increases this overlap, which increases the uncertainty when delineating the lake-shore boundary.
Landsat imagery is commonly used to delineate large proglacial lakes and has also been used to map smaller supraglacial lakes. The variable size of supraglacial water bodies means the 30 m pixel size of the Landsat imagery leads to increased uncertainty for smaller lakes, whereas finer resolution ASTER (15 m) or ALOS ANVIR (10 m) imagery can improve this classification accuracy.
Application of the Normalised Difference Water Index (NDWI) to Sentinel-2 imagery on Khumbu Glacier in Nepal.
Quantifying the expansion of Chubda glacial lake in Bhutan using multi-temporal Landsat imagery.
Object based image analysis (OBIA) in another tool used to map lake areas and offers several advantages over pixel-based approaches. The technique detects edges at multiple scales, providing a set of connected curves delineating the boundaries of water (and other features). OBIA also makes use of non-spectral metrics (e.g. image texture) to classify segments.
OBIA applied on Ngozumpa Glacier to classify supraglacial ponds.
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Knowledge of the bathymetry of glacial lakes is important when estimating the volume of water contained in the lake and how this changes through time. Deepening bathymetry over time indicates the depth of the lake is increasing, which suggests the lake bed is underlain by remnant glacier ice. This ice melts due to the thermal energy transmitted by the water above which means the volume of the lake can expand over time. A thick debris cover on the lake bed can restrict this melting by insulating the ice beneath.
The simplest means of measuring lake depth is to use a weighted line (plumb line) deployed from a boat. This survey can be conducted in a regular grid across the lake so that the lake bathymetry can be interpolated between measurements. Each measurement of depth therefore requires a GPS position fix. Measurements are limited by the length of the line: proglacial lakes are typically < 200 m in depth and supraglacial lakes may be ~ 10 m. The technique is therefore time-consuming over a large lake area. If a lake is frozen sufficiently to walk on, holes can be drilled through the ice to insert the plumb line.
Echosounding with a sonar device uses sound pulses transmitted vertically into water and uses the time between the transmission and return of the pulse to calculate lake depth. These devices can produce an accuracy on the order of centimetres to metres and may also have an integrated GPS device. ‘Fish-finders’ have successfully been used to map lake depth and can even work through ice in some circumstances. An echosounder mounted on an uncrewed surface vessel (USV) allows safer access to areas of the lake susceptible to falling ice or debris.
Bathymetry mapping using echo sounding. U.S. Navy Graphic Illustration.
Surveying a surpaglacial pond with an uncrewed surface vessel (USV) 'BathyBot'.
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