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Mapping compositional diversity on the surface of Mars: The Spectral Variance Index

Authors :
Sara Martínez-Alonso
Bruce C. Kindel
Bruce M. Jakosky
Michael T. Mellon
Source :
Journal of Geophysical Research. 111
Publication Year :
2006
Publisher :
American Geophysical Union (AGU), 2006.

Abstract

[1] The advent of high spatial resolution instruments onboard orbiting Mars missions entails the need for identification of critical regions to be analyzed in further detail. We present the Spectral Variance Index (SVI), a method to detect regions of large surface materials diversity compared to the average of the planet. Such diversity may be indicative of significant active and past geological processes, such as hydrothermal activity, chemical and mechanical sedimentation, pyroclastic volcanism, erosion unveiling layering of diverse composition, and weathering, among others. The SVI was derived from statistical analysis of the Mars Global Surveyor Thermal Emission Spectrometer spectral data set for 5 × 5 degree cells covering the entire planet; global SVI maps depicting surface materials diversity were produced. Regions of elevated SVI occur clustered in low-albedo, high-thermal inertia regions, indicative of rock-dominated surfaces. The surface geology of two regions of anomalously high SVI (Nili Fossae and Mare Tyrrhenum), and one region of low SVI (Amazonis Planitia), was investigated utilizing spectroscopic, thermophysical, and morphological data. The following data-derived spectral end-members were identified in all three regions: atmospheric water-ice, surface dust (both in close spatial relationship), and instrument noise. The high SVI regions show also signatures characteristic of surfaces type 1 and 2, forsterite (Nili), phyllosilicates and/or high-Si glass (Nili), and another end-member most consistent with fayalite (or, alternatively, high-Ca pyroxene) in volcanic materials (Tyrrhenum). The SVI method effectively identifies regions, both previously known and new ones, of surface material diversity on Mars; spectroscopic data of higher spatial resolution will improve our understanding of their compositional diversity.

Details

ISSN :
01480227
Volume :
111
Database :
OpenAIRE
Journal :
Journal of Geophysical Research
Accession number :
edsair.doi...........73299b153e877a54dd1141d29d374fc2
Full Text :
https://doi.org/10.1029/2005je002492