Vikrahraun-the 1961 basaltic lava flow eruption at Askja, Iceland: morphology, geochemistry, and planetary analogs.

We examine the morphology and chemistry of the Vikrahraun basaltic eruption emplaced at Askja Volcano, Iceland, from Oct. 26-Dec. 17, 1961. The eruption had three eruptive events, initiating with a'a and followed by alternating a'a and pahoehoe lava flow emplacement. We determine that while the eruption is chemically homogenous (Fe/Mg = 1.9-2.2, 47-52 wt.% SiO2), it demonstrates transitions from high to low viscosity lava flow morphologies. A'a flows have a total crystallinity (phenocryst and microlite abundance by area) ranging from 85-100%, which increases by 1% per km from the vents, while pahoehoe flows range from 55-86% and increase at a higher rate of 5% per km. Vesicularity systematically decreases with distance from the vent by 3% per km. Pahoehoe and vent samples have calculated temperatures 50 °C higher than a'a samples, which we interpret to be due to the difference between tube fed pahoehoe and open channel a'a lavas. The homogenous nature of the Vikrahraun lava makes it an excellent testbed to study the effects of observational scale and satellite resolution on the interpretation of surficial textures. Festoons, which are downslope pointed convex ridges from 1 to 5 m high and ~ 10 m long, are observed in event 2 a'a lavas in satellite imagery and topographic profiles. Features of this scale have previously only been documented in terrestrial rhyolitic lavas, leading planetary researchers to infer that festooned lava flows on Venus and Mars may be silicic. The diverse morphologies and homogenous composition make Vikrahraun an important planetary analog, where morphological complexity is over-attributed to chemical variation and suggests the need to re-evaluation planetary lava flow interpretations. Supplementary Information: The online version contains supplementary material available at 10.1186/s40623-022-01711-5.

Automated detection of geological landforms on Mars using Convolutional Neural Networks.

The large volume of high-resolution images acquired by the Mars Reconnaissance Orbiter has opened a new frontier for developing automated approaches to detecting landforms on the surface of Mars. However, most landform classifiers focus on crater detection, which represents only one of many geological landforms of scientific interest. In this work, we use Convolutional Neural Networks (ConvNets) to detect both volcanic rootless cones and transverse aeolian ridges. Our system, named MarsNet, consists of five networks, each of which is trained to detect landforms of different sizes. We compare our detection algorithm with a widely used method for image recognition, Support Vector Machines (SVMs) using Histogram of Oriented Gradients (HOG) features. We show that ConvNets can detect a wide range of landforms and has better accuracy and recall in testing data than traditional classifiers based on SVMs.

Hesperian age for western Medusae Fossae Formation, Mars.

The Medusae Fossae Formation (MFF) on Mars is an intensely eroded deposit north of the cratered highlands. It is widely thought that MFF materials were emplaced through ignimbrite eruptions. Recent geologic mapping of western MFF identified outliers of MFF materials well beyond the previously mapped western extent for the deposit, including outliers close to Gale crater. We report counts of impact craters on the MFF units that have implications for our understanding of the general history of MFF and the uppermost layered materials on the Gale crater mound.