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Enregistrement W4205494891 · doi:10.5194/epsc2021-99

Comparison of photometric phase curves resulting from various observation scenes

2021· preprint· en· W4205494891 sur OpenAlexaff
S. Potin, S. Douté

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineEngineering
ThématiqueCalibration and Measurement Techniques
Établissements canadiensUniversity of Winnipeg
Organismes subventionnairesnon disponible
Mots-clésReflectivityChemistryPhysicsGeometryOpticsMathematics

Résumé

récupéré en direct d'OpenAlex

Introduction Reflectance spectroscopy is a common tool used to retrieve physical and mineralogical information on Solar System planetary bodies. However, the reflectance spectrum of a surface depends on several parameters, including the illumination condition and observing geometry [1]. The observed reflectance of small bodies is generally compared to laboratory measurements of meteoritic samples or terrestrial analogues to assess the composition and alteration history of the target’s surface. Laboratory measurements are performed in a controlled environment, where the composition and texture of the sample are known and the illumination and observing geometry is fixed. However, if the spectroscopic observations of the small body are unresolved, its reflectance is integrated over the whole observed surface, which averages spatial compositional and textural heterogeneities and changes in the illumination and observation geometries due to both the shape of the object and the topography of its surface (slopes, craters, …).Here we use spectral bidirectional reflectance of terrestrial analogues measured in the laboratory and applied on 3D model of the small body (4)Vesta. We simulate the observation of these bodies by a spacecraft during a spot-pointing manoeuvre and two different fly-bys, and compare them with the spectroscopic results obtained in the laboratory.Sample, measurements and inversion models We consider a fine powder of howardite as a reference sample for the surface of Vesta. The laboratory Bidirectional Reflectance Distribution Function (BRDF) measurement, and inversion procedure used to model the reflectance of the surface under any triplet of incidence, emergence, and phase angles are described in [2, 3]. Two generic models are considered: parametric RTLSR and physical Hapke.Simulation of the observations We apply the BRDF model of the howardite on each facet of the shape model of Vesta. This results in a simulated body homogeneously covered with the surface studied in the laboratory. We then simulate image acquisition by a simple pinhole camera under various illumination and observation conditions to recreate a spot-pointing manoeuvre and two fly-bys: one following the equator (hereafter called “equatorial fly-by”), the other following a meridian line (hereafter called “polar fly-by”). As an example, Figure 1 presents the images resulting from the simulation of the equatorial fly-by with a phase angle ranging from 6 to 135°. For comparison purposes, the spot-pointing and equatorial fly-by scenarios at phase angle 30° point toward the same spot on the surface and present identical illumination and observation conditions.Comparison of the phase curves Unresolved reflectance spectroscopy of the simulated Vesta is calculated for each image with comparison to a Lambertian sphere of similar size. We define, as a function of the phase angle, the photometry as the value of reflectance measured at 740 nm. We also compare the spectral parameters derived from the observations to those derived from the laboratory measurements and their RTLSR modeling. Figure 2 presents the evolution of the reflectance, spectral slope and 3µm band depth with increasing phase angle for each simulated observation.We observe that the photometric phase curve of Vesta strongly depends on the type of observations. The phase curve resulting from the spot-pointing presents roughly the same evolution as what has been measured in the laboratory. The reflectance measured on the spot-pointing differs from the reference for phase angles wider than 90°. The phase curve resulting from the polar fly-by present the same concave evolution with increasing phase angle, but its reflectance value differs from the reference for phase angles wider than 60°. Finally, the phase curve resulting from the equatorial fly-by presents the most differences from the reference surface. With increasing phase angle, the unresolved reflectance of the simulated Vesta only decreases until reaching a plateau around 0.35. The composition of the observed small body being constant between each experiment, the variations detected here on the phase curves are only due to the variation of shape and topography of the surface, resulting in various local incidence and emergence angles on the surface of the simulated Vesta. As an example, Figure 3 presents the distribution of the local emergence angles at phase angle 90° on each simulated observation.The global shape of the small body and topography of its surface induce variations in local incidence and emergence angles, leading to differences between the observed reflectance and the values measured in the laboratory on the reference surface. Moreover, the different simulations presented here induce a variation of the illumination and observation conditions, observed areas on the surfaces and projected shape of the body. These thus create the differences observed when analysing the photometric phase curves.Conclusion We compared the photometric phase curves resulting from simulated non-resolved observation of Vesta under various scenarios. We observed that the evolution of the reflectance strongly depends on the illumination and viewing conditions. Moreover, the projected shape and topography of the surface will lead to the observed reflectance differing from the direct measurement on the reference surface.References [1] Potin et al. (2019) Icarus, 333, 415-428 [2] W. Lucht et al. (2000), IEEE Trans. Geosci. Remote Sens., 38, 977-998. [3] Z. Jiao et al. (2019) Remote Sens. Env., 221, 198-209.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,284
Score d'incertitude au seuil0,828

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,135
Tête enseignante GPT0,366
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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