Mathematics – Logic
Scientific paper
Sep 1999
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999dps....31.6003h&link_type=abstract
American Astronomical Society, DPS meeting #31, #60.03
Mathematics
Logic
Scientific paper
Visible and near-infrared spectra from the Imager for Mars Pathfinder (IMP) camera have been used to characterize the color and infer the composition and physical nature of the Pathfinder landing site. The range of colors and albedos of materials at the Pathfinder landing site is similar to that observed in Viking Orbiter and HST images of Mars, but precise comparisons are hampered by the effects of atmospheric scattering in these data sets and differences in the effective wavelengths of the images. Such comparisons will allow the spectral units observed at the Pathfinder landing site to be placed into a global geologic context, and the composition, physical properties, and origins of Martian surface units to be inferred. We will report on our progress toward achieving these objectives by calibrating, modeling, and analyzing IMP multispectral observations of various surface materials and comparing them to the color and albedo units observed by the Viking Orbiter cameras, the WF/PC2 on HST, and the MOC wide-angle cameras on MGS. In addition, our results will be compared with those of previous studies of the spectral reflectance of materials observed at the Viking landing sites. These analyses will help to determine the relative importance and timing of geologic processes that have affected the Pathfinder landing site, and therefore constrain the geologic history of the site. The relationships between various spectral units, as observed at the Pathfinder landing site, may be extrapolated to infer the stratigraphic relations between these units regionally and perhaps globally. This new information will show where various processes are currently or were recently active on Mars, and constrain the rates of aeolian deposition and erosion of surface materials. This research is supported by the NASA Mars Data Analysis Program.
Bell Jon F.
Herkenhoff Ken E.
Johnson Jay Robert
Lemmon Mark
Reid R. J.
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