We apply integrated attribute analysis to extract more reliable quantitative information from processed GPR data, and obtain a better characterization of subsurface structures. A multi-attribute approach is used to characterize the subsurface through different attribute categories, including instantaneous, coherency, and textural attributes applied to quantities related not only to amplitude, phase, and frequency, but also to other parameters calculated from the original data. The different attributes can be integrated into a single view with composite displays (overlays and mixed displays). The proposed procedure is tested in different environments namely: archaeological areas to characterize cultural heritage buried in highly heterogeneous subsurface environments, and glaciers to image their inner structure and to monitor the seasonal changes of firn layers. The results from two case studies demonstrate that the proposed integrated attribute analysis can highlight zones characterized by different electromagnetic parameters, better visualize and quantify GPR features in an automatic and objective manner, and enhance GPR data interpretation in different application fields.
