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EXPLORING IN SITU SPECTRA FOR CHARACTERIZATION OF GLACIER SURFACES USING MULTISPECTRAL IMAGERY ANALYSIS TO INFER CLIMATE CHANGE (Remote sensing of glaciers)

Arctic snow cover is important to life on Earth from the micro-scale soil micro-arthropod population, to reindeer at local scale and even the global scale through its impact on the global climate. The Arctic Report Card for 2012 indicates that the rate of loss of June snow cover extent between 1979 and 2012 (-17.6% per decade relative to the 1979-2

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Project date

Starts
2014-09-01

Ends
2015-12-31

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Project Keywords

  • cryosphere / glaciers/ice sheets / glaciers

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Summary

Arctic snow cover is important to life on Earth from the micro-scale soil micro-arthropod population, to reindeer at local scale and even the global scale through its impact on the global climate. The Arctic Report Card for 2012 indicates that the rate of loss of June snow cover extent between 1979 and 2012 (-17.6% per decade relative to the 1979-2000 mean) is greater than the loss of September sea ice extent (-13.0% per decade) over the same period. This will influence the hydrology and snow cover in these regions, which in turn will provide a feedback to climate. The impacts to polar hydrology and snow cover are poorly understood. The gaps are even larger with respect to feedback mechanisms. Additionally, snow cover maps are important inputs for glaciological applications such as mass balance studies. We propose research by using data from various satellite-based multispectral sensors (Landsat ETM+, Landsat Data Continuity Mission, MODIS, and the recent DMCii) to classify surface of arctic glaciers and icecaps. These sensors vary in many ways including spatial resolution (potential 20-500 m), spectral bands, and repeat imaging time. Each of these factors has significant implications for the ability of the sensor to accurately delineate glacier surfaces. Our main goals are (1) to explore the use of in situ spectra to DMCii multispectral satellite image classification of glacier surfaces, (2) Spatial snow cover change detection studies using existing Landsat images (2005- 2010) and present DMCii images captured in 2013; (3) collection of ground spectra using spectroradiometer for calibration and atmospheric correction of DMCii data in order to improve digital classification truth. The novelity of the research is as follows: [1] Spectral reflectance measurement will be done for melt season (August/September) in the Vestre Broggerbreen and Midtre Lovenbreen. Field spectra will be compared with archival Landsat ETM+ imagery and newly received DMCii imagery. [2] A supervised ensemble classifier will be designed for glacier classification using in-situ spectra and DMCii imagery.

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