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Download Exercise sheet : Remote Sensing of the Cryosphere 1 1. Imaging
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Exercise sheet : Remote Sensing of the Cryosphere 1 1. Imaging geometry The image below shows Lowell Glacier in the Yukon, near the British Columbia border. Where are the glaciers in this image? What type of sensor does this image come from? Where does the sensor look from (look direction)? What is the flight direction (azimuth)? What might be the potential implications of this geometry for derivation of glaciological parameters? 2. Radar foreshortening The image above shows examples of radar foreshortening resulting from the imaging geometry of an unknown beam incidence angle (θi). This can be computed in percentages (Fp), according to the following formula: Fp = (1-‐sin θi)*100, where is θi is the local indicent angle of the slope. Fill out the following table, and briefly interpret the results. Local incident angle (θi) Radar foreshortening (Fp, %) 0° 30° 50° 70° 90° 3. Structural glaciological mapping The following two images show Byrd Glacier, Antarctica, passing through the Transantarctic Mountains and entering the western margin of the Ross Ice Shelf. The first (a) is an optical / VNIR false colour composite image acquired by Landsat 1 MSS. The second (b) is a SAR image acquired by Canada’s RADARSAT satellite. Identify and highlight glaciological structures that you can identify on either image. What differences can you identify due to sensor type? (a) (b) 4. Snow / ice facies The following image is a terrain-‐corrected, map-‐projected, multitemporal ERS-‐1 image segment of Mount Wrangell and the area to the east. The image is a false-‐ colour composite of C-‐band SAR data acquired at three time intervals (December 1992, June 1993, and September 1993). What do you see? Fill in the table by qualitatively assigning backscatter intensities (high / medium / low) and corresponding surface conditions (melt / freeze / bare) to the different time intervals. Which glacier zone / facies do the colours represent? [Hint, look for radar foreshortening, wet snow, percolation / wet snow, bare ice and vegetated zones]. Where do you think the snow line is located? Zone / facies Winter (blue colours) Early summer (red colours) Late summer Appearance in (green colours) figure White / grey Purple Blue Green Yellow-‐green 5. Feature tracking for ice velocity Part of the experimental design of a project to measure glacier velocities by feature tracking requires choosing satellite imagery at an appropriate time interval, given a sensor’s ground range resolution and the expected flow speed of the ice. Complete the following table to suggest appropriate time intervals in days for a robust velocity estimate, given different ground range resolutions and maximum glacier velocities. Ground range Maximum glacier resolution (m) velocity (m/yr) 3 15 30 50 300 2000 6. Elevation data horizontal offsets Horizontal (x,y) offsets between elevation products (DEMs) are common due to georeferencing errors. These offsets must usually be corrected for before elevation changes can be determined. a. If a glacier has a symmetric geometry, how will an erroneous horizontal offset between two DEMs acquired at times t1 and t2 affect the overall estimate of volume change? What about if the glacier is not symmetric? b. Would a 100 metre horizontal offset between DEMs have a large impact on the uncertainty estimate over a smooth ice cap or a steep icefield?
