A novel multispectral glacier mapping method and its performance in Greenland

Abstract:

Multispectral land surface classification methods are widely used for mapping glacier outlines. Significant post-classification manual editing is typically required, and mapping glacier outlines over larger regions remains a rather labour intensive task. In this contribution we introduce a novel method for mapping glacier outlines from multispectral satellite imagery, requiring only minor manual editing.
Over the last decade GLIMS (Global Land Ice Measurements from Space) improved the availability of glacier outlines, and in 2012 the Randolph Glacier Inventory (RGI) attained global coverage by compiling existing and new data sources in the wake of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). With the launch of Landsat 8 in 2013 and the upcoming ESA (European Space Agency) Sentinel 2 missions, the availability of multispectral imagery may grow faster than our ability to process it into timely and reliable glacier outline products. Improved automatic classification methods would enable a full exploitation of these new data sources.
We outline the theoretical basis of the proposed classification algorithm, provide a step by step walk-through from raw imagery to finished ice cover grids and vector glacier outlines, and evaluate the performance of the new method in mapping the outlines of glaciers, ice caps and the Greenland Ice Sheet from Landsat 8 OLI imagery. The classification output is compared against manually digitized ice margin positions, the RGI vectors, and the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) aerophotogrammetric map of Greenland ice masses over a sector of the Disko Island surge cluster in West Greenland, the Qassimiut ice sheet lobe in South Greenland, and the A.P. Olsen ice cap in NE Greenland.