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The presence of buried glacial ice and putative extinct rock glaciers in Mars' equatorial regions has implications for understanding its climate history and sensitivity to changes in insolation and has significant implications for past global redistribution of the water ice cryosphere. We quantify the morphology of rock glacier- "like" features on the northern slopes of Aeolis Mons (known also as Mount Sharp) within Gale crater and use this information to evaluate a possible rock glacier origin for these forms. Detailed morphometric evaluation of cross and long profiles of these lobate features, which exhibit higher slopes at their heads, lower slopes at their distal edge, and a convex upward cross-sectional profile and oversteepened sides, resembles active terrestrial rock glaciers. However, the absence of a chevron wrinkle pattern and sublimation features could indicate extensive aeolian reworking and the lack of deflation could indicate a higher rock to ice mixture. The lack of cratering surfaces relative to the cratered surfaces that they overly could indicate a younger age and are possibly indistinguishable in age from the capping units of Mount Sharp, which may have once been more laterally extensive and may have been the source of these mass wasting forms. [ABSTRACT FROM AUTHOR]

New approaches for comparative planetology are vital to recognize and assess possible shared formative processes that shape landforms on different planetary bodies, and in the case of this study to identify possible cirques preserved from past martian climates that may have been more favorable to equatorial ice. We used "RetinaNet", an augmented Convolutional Neural Network (CNN) initially trained with digital elevation data from over 1950 terrestrial cirques, to identify similar forms along a 50x50km area of the equatorial martian Dichotomy Boundary east of Gale Crater. A significant number of false positive detections associated with CTX stereo pair derived DEM artifacts and tile edges as well as craters were automatically removed. High confidence levels assigned by the machine learning algorithm suggest that the 16-remaining cirque-like forms may have formed and evolved under similar conditions to their terrestrial analogs. Morphometric data extracted for each of these cirque-like forms was statistically compared to terrestrial analog morphometric measures. While cirque length and width were significantly larger than their terrestrial counterparts and the area of these forms was ~150 % larger, on average headwall heights were ~25 % shorter. Allometric relationships suggest that the shape of these martian features changes proportionally as they grow in contrast to terrestrial forms where length increases faster than width and height. This could be due to the weaker gravitational force on Mars (3.721 m/s2) and other effects related to martian climate and environmental conditions, such as cold based glaciation. The identification of cirques in an equatorial region has implications for cryosphere distribution/redistribution and martian geologic and climatic history. • Cirques are bowl-shaped depressions on side of mountains created by glacial flow. • Machine Learning algorithm that detects Cirques trained on Earth was used on Mars. • Cirques on Mars likely to have formed under similar conditions as Earth cirques. • Detected cirque on Mars tropical regions likely associated with climate change. • Martian cryosphere expanded towards tropics during high obliquity in recent past. [ABSTRACT FROM AUTHOR]

Transverse aeolian ridges (TARs) are unusual bedforms on the surface of Mars. TARs are common but sparse on Mars; TAR fields are small, rarely continuous, and scattered, making manual mapping impractical. There have been many efforts to automatically classify the Martian surface, but they have never explicitly located TARs successfully. Here, we present a simple adaptation of the off-the-shelf neural network RetinaNet that is designed to identify the presence of TARs at a 50-m scale. Once trained, the network was able to identify TARs with high precision (92.9%). Our model also shows promising results for applications to other surficial features like ripples and polygonal terrain. In the future, we hope to apply this model more broadly and generate a large database of TAR distributions on Mars. [ABSTRACT FROM AUTHOR]