Application of Lidar Altimetry and Hyperspectral Imaging to Ice Sheet and Snow Monitoring ...
The Greenland Ice Sheet (GrIS) is of tremendous importance for climate change projections. The GrIS has contributed an estimated 10.8 mm to sea level rise since 1992, and that contribution is expected to increase in the coming decades. It is therefore essential to make routine measurements of ice, m...
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| Format: | Article in Journal/Newspaper |
| Language: | English |
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My University
2021
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| Online Access: | https://dx.doi.org/10.7302/2917 http://deepblue.lib.umich.edu/handle/2027.42/169872 |
| Summary: | The Greenland Ice Sheet (GrIS) is of tremendous importance for climate change projections. The GrIS has contributed an estimated 10.8 mm to sea level rise since 1992, and that contribution is expected to increase in the coming decades. It is therefore essential to make routine measurements of ice, meltwater, and snow over the GrIS using satellite and airborne observations. Two prominent methods for ice sheet monitoring include lidar altimetry and hyperspectral imaging. Lidar altimetry is typically used to make fine-scale estimates of ice sheet surface height, whereas hyperspectral imaging is commonly utilized to infer snow or ice surface composition. In this dissertation, I use data from the Ice, Clouds, and land Elevation Satellite-2 (ICESat-2) and the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) to examine light transmittance over the Greenland Ice Sheet. I first utilize ICESat-2 photon-counting data for the development of a retrieval algorithm for supraglacial lake depth, ... |
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