Abstract

Contributed Talk - Plenary

Advancing Lunar Ice Characterization with a Dual-Instrument CubeSat Constellation: Combining Neutron and Near-Infrared Spectroscopy

Ooh-Azlin, Winfred
Technische Universität Berlin

The Moon’s Permanently Shadowed Regions (PSRs) are critical targets for sustainable exploration due to potential water ice reservoirs, yet existing datasets lack the resolution and specificity to resolve ice form and distribution. Current datasets also suffer from ambiguities in distinguishing surface frost from buried ice or bound hydroxyl. To address these gaps, a mission outline of a concept employing a constellation of 4-6 6U CubeSats in low lunar polar orbit, each equipped with complementary miniaturized Neutron Spectrometer (NS) and Near-Infrared (NIR) Spectrometer payloads. This paper demonstrates the proposed data analysis approach using legacy LRO M3 and LEND CSETN data, augmented with LPNS maps. While standard correlations between M3-derived features and neutron data proved weak, spatial statistical analysis (LISA) successfully identified significant local clustering and spatial outliers in the M3 data, interpretable in the context of instrument limitations (e.g. shadowing) and regional hydrogen context. The proposed mission aims to leverage its dual NS/NIR measurements and high spatial/temporal resolution (tens of meters, daily-to-weekly revisits) to: (1) generate detailed hydrogen distribution maps, (2) fuse NS and NIR data to resolve compositional ambiguities, and (3) quantify volatile transport dynamics. By providing high-resolution, compositionally-aware data products, this mission, enabled by advancements in small satellite capabilities, can significantly inform future lunar science, ISRU prospecting, and landing site selection.