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Abstract:

Remote spectroscopy is used to characterize the mineralogy and infer the history of planetary bodies. Carbonaceous asteroids, such as B‐type (101955) Bennu, represent the earliest stages of planet formation. B types have a blue (negative) spectral slope and comprise <5% of asteroids. Samples from Bennu returned by the OSIRIS‐REx spacecraft complement remote observations of this rare population. We show here, using laboratory spectra that are directly comparable to spacecraft data, that OSIRIS‐REx accurately determined Bennu's dust content and most of its surface composition. However, spectra of the asteroid exhibit stronger water absorptions than those of bulk samples, possibly due to hydrous, Mg‐rich phosphate or solar wind implantation at Bennu's uppermost surface. Bennu samples spectrally resemble the most aqueously altered carbonaceous meteorites and samples of (162173) Ryugu, indicating similarly pervasive aqueous alteration. However, one carbon‐enriched Bennu stone does not appear to have a spectral analog among Ryugu samples or meteorites. Our findings demonstrate the leverage obtained using a wide range of wavelengths and that sample analysis anchors the interpretations of remote sensing, leading to more robust characterization of planetary surface composition and evolution.

Abstract:

Plain Language Summary: We present laboratory tests of a new instrument, the High‐resolution Volatiles and Minerals Moon Mapper ( H V M 3 ${\mathrm{H}\mathrm{V}\mathrm{M}}^{3}$ ). H V M 3 ${\mathrm{H}\mathrm{V}\mathrm{M}}^{3}$ will launch onboard the National Aeronautics and Space Administration's Lunar Trailblazer mission. It is an imaging spectrometer that will measure the spectrum of reflected sunlight in visible and infrared wavelengths for every pixel of an image. Scientists will interpret these spectra with the goal of measuring how water and ice are distributed across the lunar surface. Our laboratory tests indicate that the instrument is sensitive enough to measure small changes in the content of water on the lunar surface. We find the instrument capable of measuring areas of the Moon that are in permanent shadow using light reflected from neighboring surfaces like crater walls.

Abstract:

The Lunar Trailblazer mission launched in February of 2025 with the goal of characterizing lunar surface water through a targeted campaign. One instrument on the mission, the Lunar Thermal Mapper (LTM), was tasked with measuring the surface temperature to compare with maps of the form and abundance of water on the lunar surface. LTM's secondary science goals were to identify regolith composition and thermophysical properties as exhibited by mid‐infrared spectral features. Here we show the utility of LTM in distinguishing lunar regolith composition with its 11 narrow bands. Five spectral parameter products were developed to aid in early identification of regions of interest for follow‐on spectral analyses. These products include the Christiansen feature (CF) value, weighted absorption center (WAC) value, WAC band depth, Transparency Roll‐off, and a Diviner CF value equivalent. These products would be used mainly to flag these regions for more detailed follow‐up study with the entire spectral capabilities of the mission instrumentation. The Lunar Thermal Mapper (LTM) is one of two instruments on the Lunar Trailblazer mission launched in February 2025. LTM's primary goal is to provide surface temperature measurements for the lunar surface, in particular for identifying and mapping water on the Moon. LTM is also capable of identifying the compositional and physical properties of different rocks on the surface. Here, we test those capabilities and determine five methods for quickly distinguishing bulk properties of the lunar rocks that can be used by the community to identify regions of interest for further investigation. Mid‐infrared compositional parameters were created and tested for the Lunar Trailblazer mission Spectral parameters can distinguish bulk silicate mineralogy, and identify regions of compositional interest The Christiansen feature roll‐off parameter can provide an initial identification of areas with distinct thermophysical properties Mid‐infrared compositional parameters were created and tested for the Lunar Trailblazer mission Spectral parameters can distinguish bulk silicate mineralogy, and identify regions of compositional interest The Christiansen feature roll‐off parameter can provide an initial identification of areas with distinct thermophysical properties

Abstract:

The Lunar Trailblazer mission aimed to assess the presence of water on the lunar surface using imaging spectroscopy in visible shortwave infrared (VSWIR) coupled with high‐resolution multispectral imaging in thermal midwave‐infrared (MWIR), captured simultaneously over the same target from orbit around the Moon with two different instruments. Uncertainties in clock timing, instrument models, and instrument pointing knowledge manifest as geospatial offsets between the two data sets that must be corrected in post‐processing to enable co‐registration, tying the acquired images to their precise latitudes and longitudes on the Moon. This work describes an algorithmic approach to co‐registering and geolocalizing images after acquisition without high precision instrument and spacecraft pointing models, the Iterative Matching Pipeline for Post‐Acquisition Image Localization (IMPPAIL), utilizing previously acquired data for development. We use Lunar Orbiter Laser Altimetry (LOLA) and Kaguya data to make shaded relief maps as the basemap on which to project data. To test our processing pipeline prior to Lunar Trailblazer data collection, we use Moon Mineralogy Mapper (M3) data for VSWIR images and simulated MWIR images. When demonstrated on these data sets, IMPPAIL produces a 98% success rate registering VSWIR data to LOLA/Kaguya shaded relief maps and successfully co‐registered MWIR and VSWIR in all four simulation cases. We include a code package with software tools allowing this algorithm to be used for a variety of data sets across many other missions. The Lunar Trailblazer spacecraft was designed to map surface temperature and water content on the Moon via satellite imagery. Onboard are two imagers that measure thermal and visible light bands, which must be aligned to be used in conjunction with each other as well as located precisely relative to pre‐existing topography data. To do this, we develop an algorithm which iteratively matches key features between the images, allowing for the co‐registration of data points. We test the algorithm on topography and visible imagery data from a past satellite mission and simulated data for thermal images. We show 98% accuracy and success in both imagery wavelength bands. While this was originally created for use on the Lunar Trailblazer mission, the process is applicable to future missions requiring similar functionality, and we make the code available for other users. We present a process for post‐acquisition, image‐based data localization for satellite missions with use for the Lunar Trailblazer mission We demonstrate image matching success across short‐ and mid‐wave infrared image wavelength bands and topographic hillshade data sets This IMPPAIL procedure is applicable to future missions that require higher pointing accuracy than is possible with hardware solutions We present a process for post‐acquisition, image‐based data localization for satellite missions with use for the Lunar Trailblazer mission We demonstrate image matching success across short‐ and mid‐wave infrared image wavelength bands and topographic hillshade data sets This IMPPAIL procedure is applicable to future missions that require higher pointing accuracy than is possible with hardware solutions

Abstract:

Abstract The Lunar Thermal Mapper (LTM) instrument is a UK Space Agency funded infrared radiometer designed and built for the National Aeronautics and Space Administration Lunar Trailblazer mission launched in February 2025. LTM is a pushbroom imaging filter radiometer with 15 channels that cover the wavelength range from 6.25 to 100 μm with a 40–70 m/pixel ground sampling. Lunar Trailblazer's mission is to understand the form, abundance and distribution of water across the lunar surface. LTM provides an independent measure of temperature to investigate thermal effects on water's mapped distribution as well as an independent measure of surface mineralogy. The LTM instrument's 15 infrared channels include four broadband temperature sensing channels (6.25–12.5, 12.5–25, 25–50 and 50–100 μm) plus 11 additional narrow band (∼40 cm −1 ) filters from ∼7–10 μm to map and discriminate silicate composition. We review the LTM design and calibration campaign at the University of Oxford's Space Instrumentation facility and show that the instrument has sensitivity from 400 K with a Noise Equivalent Temperature Difference of <0.1 K to <1 K at 110 K for typical integration times (e.g., 30 Hz readout) from a nominal 70–130 km lunar orbit design altitude. Plain Language Summary This paper describes the Lunar Thermal Mapper instrument for NASA's Lunar Trailblazer mission. Lunar Thermal Mapper is a thermal imaging system designed to sense the temperature and composition of the lunar surface using the thermal infrared. By sensing the temperature environment of the Moon, Lunar Thermal Mapper supports the Trailblazer's mission to map water on the lunar surface. Key Points The Lunar Thermal Mapper (LTM) instrument will measure thermal infrared radiation from the Moon across from 400 K to <110 K The LTM instrument completed assembly, testing, calibration and integration on the Lunar Trailblazer spacecraft The LTM instrument demonstrated sensitives of <0.1 K at 400 K and <1 K at 110 K during ground testing and calibration