Surface and Spectral Characteristics of Desert Fans of Different Ages

As desert pavements mature, their surface characteristics change, especially clast size, varnish development, and frequency of overturned clasts (rubified bottom exposed). Together, these properties define the overall spectral signature of the surface. This study was designed to (1) identify/quantify the physical characteristics of desert pavements of different ages that define the spectral signature, and (2) determine if spectral variation can enhance remote sensing mapping of fans. This improves on past approaches that rely primarily on total varnish development to map relative ages using remote sensing. Typically, spectra are measured of a small number of individual/group of clasts that is then extrapolated to larger scales (10's of meters). Although useful, this approach misses other fine-scale changes that are necessary for understanding the variability and progression of changes that occur in the development of pavements.

Surface characteristics studied included: (1) the abundance of overturned clasts , (2) exposure of underlying AV horizon, (3) clast size, and (4) roughness at the 1-10cm scale. Alluvial fans near Yuma, AZ were studied with ages ranging ~10-25 ka (2A) and ~125-400 ka (3B). Grid point-counts were made to characterize the size distribution as well as frequency of overturned clasts. High-resolution spectral measurements were made at a range of heights above the surface (1-500cm) to determine the scale of spectral variability.

Approximately 20-40% of the pavement clasts had been overturned at some time after varnish formation. The older the fan, the greater the potential for increased rubification (overturned clasts) exposed on the surface. Also, younger fans have larger mean clast sizes (higher variability) resulting in an increase of cast shadows, and a higher spatial scale of variability 60-80 cm (vs 10-20 cm for the 3B surface). These result in different spectral signatures that may be used to map different age pavements using remote sensing data.