Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region: Applications in Planetary Sciences

• Published in: Earth and space science (Hoboken, N.J.) Vol. 11; no. 8
• Main Authors: Pérez‐López, S. A., Kremer, C. H., Mustard, J. F.
• Format: Journal Article
• Language: English
• Published: Hoboken John Wiley & Sons, Inc 01.08.2024; American Geophysical Union (AGU)
• Subjects: Algorithms; Datasets; feature fitting; infrared; Libraries; Magnesium; Mars; Minerals; Moon; signal‐to‐noise ratio; Space telescopes; spectral resolution; Spectrometers; spectroscopy; Trends
• ISSN: 2333-5084; 2333-5084
• DOI: 10.1029/2023EA003476

Spectral features of olivine across the intermediate infrared region (IMIR, 4–8 μm) shift systematically with iron‐magnesium content, enabling determination of olivine composition. Previous IMIR studies have used laboratory data with signal‐to‐noise ratios (SNRs) and spectral resolutions potentially greater than those of data derived from planetary missions. Here we employ a feature fitting algorithm to quantitatively assess the influence of data quality on olivine detection and compositional interpretation from IMIR data of 29 spectra of pure olivine of synthetic, terrestrial, lunar, and Martian origins, as well as 5 spectra of lunar pyroclastic beads measured as bulk samples. First, we demonstrate the effectiveness of the feature fitting algorithm in the interpretation of IMIR olivine spectra, predicting olivine composition with an average error of 6.4 mol% forsterite across all test spectra using laboratory‐quality data. We then extend this analysis to degraded test spectra with reduced SNRs and sampling rates and find a range of data qualities required to predict olivine composition within ±11 Mg# (molar Mg/[Mg + Fe] × 100) for the test spectra explored here. Spectra for the sample most relevant to lunar exploration, an Apollo 74002 drive tube consisting of microcrystalline olivine and glass‐rich pyroclastics, required SNRs ≥ 200 for sampling rates ≤25 nm to predict composition within ±11 Mg# of the sample's true composition. Derived limits on SNRs and sampling rates will serve as valuable inputs for the development of IMIR spectrometers, enabling comprehensive knowledge of olivine composition on the lunar surface. Plain Language Summary An understanding of olivine composition can reveal the history of large‐ and small‐scale magmatic processes, offering key insights into a planet's thermal and chemical evolution. Here we explore olivine spectra in the intermediate infrared region (IMIR), where systematic trends in olivine's absorption bands are indicative of composition. We degrade laboratory olivine spectra to data qualities that are more realistic of spectrometers used in planetary exploration and derive constraints on the signal‐to‐noise ratio and sampling rates required to accurately predict olivine composition. These constraints will be useful in the development of IMIR spectrometers. Key Points We use a feature fitting routine to predict olivine composition from degraded spectral data in the intermediate infrared region (4–8 μm) Accurate prediction of olivine composition is observed at data qualities expected of spectrometers designed for space exploration