Scalloped Cliff Formations and Association with Radar Reflectors, a Radar - Imagery Integrated Approach
Notice bibliographique
Résumé
The North Polar Layered Deposits (NPLD) of Mars preserve a valuable record of the planet’s climatic history through stacked layers of water ice and dust [1]. These layers are exposed at the surface and can be observed in the optical imagery [2], while subsurface stratigraphy is revealed through radar sounding data [3]. Our study aims to integrate these datasets, to gain a more complete understanding of the geomorphology of NPLD.We identify and catalog 98 Scalloped Cliffs (SC) across the NPLD using optical imagery (Fig.1), exposed by the troughs using the High-Resolution Imaging Experiment (HiRISE) and Context Camera (CTX) imagery. We use a three-dimensional Shallow Radar (SHARAD) dataset [4] to understand the subsurface stratigraphy of the NPLD. After mapping the scalloped cliffs in JMARS, they are converted as shapefiles to a SeisWare format for comparison with a 3D SHARAD data volume for integrating the topography features with the subsurface stratigraphy. We compared the elevation of the outcropping reflections to exposures at the same elevations and found unique surface morphology of cliffs that immediately overlie angular unconformities.A SC is a geomorphological feature formed by the protrusion of layers tens of meters tall along several kilometers with a unique wavy appearance. SCs may be isolated or appear in multiples at the same NPLD outcrop and most are associated with identifiable stratigraphic unconformities. The spatial distribution of the identified cliff's location suggests that the scalloped cliffs are more concentrated in the Gemini Scopuli region of Planum Boreum, Mars. We observe that, in some locations, SHARAD reflectors of NPLD reach the surface coinciding with a SC location (Fig. 2), providing an opportunity to investigate if any stratigraphic anomalies like lag deposits can make a bright reflection . Some bright reflections may indicate the presence of relatively erodible beds, possibly at lag deposits, between resistant units [5].In this study, we examine radar profiles corresponding to the cliffs to assess whether these cliffs coincide in x,y,z with bright subsurface reflectors, and/or a stratigraphic angular unconformity. Some cliffs are not associated with any identifiable unconformities in the imagery, possibly because they manifest as disconformities at the surface, so we examine in the radar data to investigate any subsurface unconformities at the same stratigraphic level. Our technique is to identify the elevation of SCs from MOLA data and unconformities or bright reflectors in SHARAD data with the intent of testing the hypothesis that there is a connection between the exposed bright reflector in the NPLD outcrop and the unconformities. Most SCs are associated with the reflector 15 (R15, counting from the top) located in the upper NPLD and previously identified as an unconformity and reveals a major climatic shift [6]. A few cliffs are associated with R40, another unconformity in the lower NPLD. Some cliffs are found to be associated with R35, it could be a simple rich deposition layer. Alternate deposition and erosion can lead to unconformities and unconformities can make a lag. These associations between scallop cliffs, unconformity, and bright radar reflectors give strong evidence that the reflectors in the radar are caused by lag deposits. It is not a coincidence that these correspond in position to SHARAD-observed reflections. Our analysis highlights a consistent spatial association between scalloped cliff locations, angular unconformities and strong subsurface reflections, providing a better insight into the erosional and depositional history of the NPLD and is consistent with the findings of Smith et al 2025 [6].Fig. 1: Optical imagery showing a scalloped cliff directly associated with an exposed outcrop in the NPLD. Location and Image details are highlighted.Fig. 2: The radar profile shows the scalloped cliff (Fig. 1) associated with a bright reflector (R35) within the exposed outcrop of the NPLD.References: [1] Phillips, R.J., Zuber, M.T., Smrekar, S.E., Mellon, M.T., Head, J.W., Tanaka, K.L., Putzig, N.E., Milkovich, S.M., Campbell, B.A., Plaut, J.J., others, 2008. Mars north polar deposits: Stratigraphy, age, and geodynamical response. Science 320, 1182.[2] Smith, I.B., Holt, J.W., 2015. Spiral trough diversity on the north pole of Mars, as seen by Shallow Radar (SHARAD). J. Geophys. Res. Planets 120, 2014JE004720. https://doi.org/10.1002/2014JE004720[3] Smith, I.B., Putzig, N.E., Holt, J.W., Phillips, R.J., 2016. An ice age recorded in the polar deposits of Mars. Science 352, 1075–1078. https://doi.org/10.1126/science.aad6968[4] Foss, Frederick J., et al. “3D Imaging of Mars' Polar Ice Caps Using Orbital Radar Data.” The Leading Edge, vol. 36, no. 1, 2017, pp. 43–57., https://doi.org/10.1190/tle36010043.1.[5] Lalich, D. E., et al. “Radar Reflectivity as a Proxy for the Dust Content of Individual Layers in the Martian North Polar Layered Deposits.” Journal of Geophysical Research: Planets, vol. 124, no. 7, 2019, pp. 1690–1703., https://doi.org/10.1029/2018je005787.[6] Smith, I. B., et al. (2025), A Major Climatic Change of the North Polar Layered Deposits of Mars, LPSC LVI, abst 1452.
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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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».