Lunar Science Support Activities for 'Volatile and Mineralogy Mapping Orbiter (VMMO)' Mission

Introduction: Lunar exploration is driven by a number of science and exploration goals (e.g., LEAG, 2016, 2017) [1]. One is determining the presence of water ice deposits in permanently shadowed regions (PSRs) [e.g., 2-5]. They are of scientific interest because past lunar exospheric conditions may be preserved in the ice [6], as well as for in-situ resource utilization. Multiple lines of evidence indicate that water ice is or may be present within some PSRs [e.g., 2, 6,7]. However, its areal distribution is largely unknown, particularly at sub-km spatial scales. Detecting surficial water ice within these PSRs could be achieved through active reflectance spectroscopy [e.g., 8]. The VMMO Remote Sensing Payload: The proposed VMMO mission, which recently completed a CSA-funded Phase 0 and ESA-funded Phase A study, is intended to probe PSRs at spatial scales of metres to tens of metres. Active sensing will be accomplished via a three-band lidar system using wavelengths of 532, 1064, and 1560 nm [9]. The selection of these wavelengths was designed to enable discrimination of water ice from mare and highlands. Highland regolith spectra are generally moderately bright in the visible region, flat to red-sloped beyond the visible region, usually with a weak plagioclase feldspar absorption band in the 1300 nm region, and sometimes with weak mafic silicate absorption bands in the 1000 and 2000 nm regions [10] (Figure 1). Mare regolith spectra are darker in the visible region, red-sloped beyond the visible region, and with weak to moderate mafic silicate absorption bands in the 1000 and 2000 nm regions (Figure 2). Water ice spectra are bright in the visible region, with blue sloped spectra beyond this region, and increasingly strong water ice absorption bands in the 1000, 1500, and 2000 nm regions [11] (Figure 3). At the VMMO wavelengths, these types of materials can be discriminated using both absolute reflectance and reflectance ratios for these three wavelengths. However, dust cover, percentage of ice covered by regolith, and regolith: ice ratio, and how dust and ice are mixed together could all influence the efficiency of detecting water ice. We have conducted laboratory experiments to test for how physical properties of ice + powdered lunar rock affect our ability to detect water ice using the three-band lidar system. We considered the following parameters: (1) different water ice: lunar material ratios in both intimate and areal mixtures; (2) local slope; and (3) different thicknesses of dust cover over water ice. Methods: Reflectance spectra (350-2500 nm) were acquired with an ASD Fieldspec Pro HR spectrometer. To simulate a lidar, we used a bifurcated fiber optic bundle, which provided co-aligned incidence and emission (i=e=0°). To measure the effects of local slope on lidar return, the samples were positioned at 10˚, 20˚, 30˚ and 40˚ off normal. All spectra were measured relative to a calibrated Spectralon panel. Results: Ice detection is possible using reflectance spectroscopy at 532, 1064, and 1530 nm for water ice abundances as low as 1 wt.%. We can determine or constrain whether water ice is exposed at the lunar surface, or covered by a thin dust layer. Both absolute and reflectance ratios using all three bands are required to fully detect and discriminate mare, highland, and water ice and to derive water ice surficial abundance. Water ice detection and discrimination is reliant on reflectance of the 1560 nm band, as this is where a strong water ice O-H overtone occurs, and reflectance in this region rapidly decreases with increasing ice abundance. In all cases, lunar regolith spectra are red-sloped (reflectance increasing toward longer wavelengths), and absolute reflectance varies with factors such as maturity and ilmenite abundance. Detection of water ice will be enhanced by comparing spectra acquired during a scan across a PSR, where mineralogical variations inside and immediately outside a PSR should be similar but vary in temperature [12, 13]. Ilmenite detection: VMMO can also operate in passive reflectance mode. A portion of the detector will be equipped with a bandpass filter to measure reflected light in the ultraviolet (~290 nm) region. Ilmenite discrimination is best accomplished using an ultraviolet: visible reflectance ratio [14] (Fig. 4). Summary: VMMO provides an opportunity to search for surficial water ice at high sensitivity and spatial resolution useful for targeting locations for investigation by surface landers with precision guidance capabilities. Acknowledgements: This study has been supported by ESA, CSA, CFI, MRIF, NSERC, and UWinnipeg. References: [1] LEAG, (2016, 2017). https://www.lpi.usra.edu/leag/. [2] Nozette S. et al. (2001) JGR, 106, 23253–23266. [3] Lawrence, D.J. (2011). Nature Geosci., 4, 586-588. [4] Lawrence, D.J. (2017) JGR, 122, 21-52. [5] Lucey, P.G. (2009) Elements, 5, 41-46. [6] Feldman W. C. et al. (2001) JGR, 106, 23231–23251. [7] Colaprete, A., et al. (2010) Science, 330, 463-468. [8] Yoldi Z. et al. (2018) LPSC 49, # 2083. [9] Kruzelecky R. V. et al. (2018) ICES, 227, 1–20. [10] Pieters, C.M. (1986) Rev. Geophys.. 44, 557-578. [11] Clark, R.N. (1981) JGR, 86, 3087-3096. [12] Watson, K., et al. (1961) JGR, 66, 1598–1600. [13] Vasavada, A. R., et al. (1999) Icarus, 141, 179–193. [14] Robinson, M.S., et al. (2007) GRL, 34, L13203. [14] C. Pitcher, et al. (2016) ASR, 57(5), 1197–1208. Figure 1. Reflectance spectra of two Apollo 16 highland regolith samples ( Figure 2. Reflectance spectra of some Apollo mare regolith samples ( Figure 3. Reflectance spectra of glacial ice and snow, showing the effects of grain size variations on reflectance. The locations of the VMMO lidar bands are shown. Figure 4. Reflectance spectra of