Planetary Surface Texture Laboratory: Polarimetric Investigation of Lunar Regolith Simulants
Notice bibliographique
Résumé
Photometry measures the intensity of light from a source, most commonly used in optics and remote sensing, in order to analyze planetary surfaces and measure brightness, also known as reflectance. Reflectance is particularly important in lunar surface analysis because it offers valuable insights into surface composition and properties. The Planetary Surface Texture Laboratory (PSTL) is a facility at Johns Hopkins Applied Physics Laboratory that houses a goniometer system designed to improve the understanding of the polarization and photometric characterizations of planetary surface analog materials. This large arc system, (~1.5 meter radius), includes a sample stage and 2 caddies; one holds the polarimetric camera while the other holds the semi-collimated, unpolarized light. The phase angles range between 20° (at i = 40°) to 120° (at i = -60°) for this study; the camera (viewing angle) remains constant as the light source moves throughout the data collection. The reflectance of a material varies with the photometric conditions and is a function of properties such as particle size, porosity, roughness, and internal particle scattering behavior. The overall albedo and color of a surface may vary with the phase geometry (angles between the light source and the detecting optics). This is of particular importance because of the extreme viewing geometries encountered at the lunar south pole.Lunar Simulant Evaluation The availability and use of lunar regolith simulants is crucial for future lunar missions and understanding how to support a sustainable presence on the surface. When using lunar simulants, we have to keep in mind that the simulants are approximations and do not possess all the same characteristics of lunar regolith. However, understanding how lunar simulants differ spectrally from lunar regolith by observing the optical properties is important for providing crucial information about the composition, application, and formation history of the Moon. We assessed 12 different lunar regolith simulants from 5 different simulant provider companies; Colorado School of Mines (CSM), Off Planet Research, Space Resource Technologies (previously Exolith), NASA/United States Geological Survey (USGS) and Deltion, (4 based in the United States, 1 based in Canada, respectively). These simulants included representation for dust, mare, nearside and farside highland regolith. Our preliminary analysis shows that the composition of these simulants has an effect on the reflectance behavior. All of the highland simulants have a higher overall reflectance than the mare simulants. This is because the majority of minerals that make up the lunar highland simulants is largely plagioclase, which absorb little light, causing a higher reflectance. While the majority of minerals that make up the lunar mare simulants is largely olivine and pyroxene, which absorbs more light, causing a lower reflectance. Any variation in reflectance as a function of phase angle can be attributed to several factors such as albedo, composition, and physical properties including the scattering behavior of the individual particles, and porosity. We also collected measurements of samples that were prepped differently in order to show similarities to actual lunar terrains (as viewed from an Earth-based telescope or from orbit). Typically, to understand the full reflectance range of the material, our samples are prepped with a smooth surface. We also prepared a textured sample that was randomly chopped until it had the same depth as the sample holder. As expected, the contrasting degree of shadowing between a smooth and a rough surface can be seen. The textured sample has a rougher surface, therefore, has more micro-shadowing, causing the textured surface to be darker than the smooth surface. The effect is most pronounced in forward scattering conditions (i.e., large phase angles, >90°). Overall, our initial findings produced expected results, although a more detailed study is underway. In general, these simulants can provide a means for developing in-situ resource utilization technologies, lunar soil testing, extraction, construction, and astronaut trainings. We can also use this data to improve remote sensing techniques and calibrate upcoming mission instruments to refine photometric simulations. Being able to provide a framework for improved interpretations of phase and polarimetric observations of planetary surfaces would ultimately be beneficial for future planetary studies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».