A New Approach for Mapping Minerals on Mars With TES Data

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5464 Remote Sensing, 6225 Mars

Scientific paper

TES emissivity data were analyzed relative to laboratory measurements from the ASU mineral library using a multiple endmember demixing approach. This analysis technique attempts to identify the minimum number of components required to independently model the spectra of each pixel in an image through iterative comparisons to a larger spectral library. The demixing algorithm initially compares hundreds of different five-endmember combinations for each pixel based on an initial spectral library of 35 mineral and atmospheric endmembers and a blackbody. The best model for each pixel is based on the error computed for each combination. If an error threshold is not satisfied by any of the five-endmember combinations, additional endmembers are added from a larger library (175 spectra) based on the residual error spectrum of the best starting model. Reducing the number of variables used to unmix spectral data by eliminating endmembers that are not present provides a more accurate identification of minor mineral components than techniques that apply large fixed libraries. As a result, TES data can be examined for mineral components whose abundance may occur below the confidence level of other analysis techniques. We tested this approach with TES data of West Candor Chasma. Previous studies have mapped relatively young, dark materials within the chasma floors that may be of volcanic origin. Regional enrichment of hematite may also exist within the canyon and represent the products of aqueous or hydrothermal alteration processes. For our study, emissivity images were created for the West Candor region using nadir TES observations (e < 10 degrees). A seasonal constraint (Ls < 200) was used to eliminate orbits that were likely to have the highest dust opacities due to annual dust storm activity. TES data were then binned into emissivity image cubes at resolutions of 16 pixels per degree for analysis. Results of the spectral mixture model were merged with high spatial resolution Viking images for interpretation. Initial results indicate the presence of high-calcium pyroxenes, olivine and some plagioclase minerals in association with previously mapped dark materials and canyon walls. Demixing results also predicted the presence of iron-rich materials within the canyon including nontronite, Fe-Smectite and hematite.

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