We evaluate the applicability and the effectiveness ofGPR attribute analysis for high-resolution
glacier imaging and characterization, testing this approach on 4-D GPR multifrequency data
collected in a small glacier in the Eastern Alps, by repeating the acquisition along the same
profiles in four different periods of the year 2013. The main objectives are to image and
characterize the glacier’s inner structure and to quantitatively monitor the seasonal thawing
of near-surface frozen materials (snow/firn). A multiattribute approach is used to characterize
the subsurface through different attribute categories, including instantaneous and textural
attributes considering not only amplitude-, phase- and frequency-related attributes, but also
other more complex and integrated parameters. We combine information from more than
one attribute into a single image with composite displays, using overlays or mixed displays.
The results demonstrate that the developed GPR attribute analysis can provide significant
improvements in the discrimination of GPR signals, and obtain enhanced and more constrained
data interpretations.
