ADASS XXXI

Meg Schwamb


Biography

Meg Schwamb is a lecturer in the Astrophysics Research Centre (ARC) and the School of Mathematics and Physics at Queen's University Belfast (QUB) in the UK. Meg's research focuses on how planets and their building blocks form and evolve, by applying ground-based surveys to probe our Solar System's small body reservoirs. She is also involved in the Planet Four citizen science projects, which enlists the public to help study the seasonal processes of the Martian south pole and map the distribution of ridges on the Martian mid-latitudes. She also serves as co-chair of the Vera C. Rubin Observatory Legacy Survey of Space and Time Solar System Science Collaboration.

Affiliation

Queen's University Belfast

Twitter handle

@megschwamb

Homepage

http://www.megschwamb.com


Sessions

10-26
12:00
30min
Exploring Mars with 150,000 Earthlings
Meg Schwamb

Mars' south pole region is sculpted by the seasonal cycle of freezing and thawing of exposed carbon dioxide (CO2) ice. In the Spring, CO2 jets loft dust and dirt through cracks in the thawing CO2 ice sheet to the surface where it is thought that local surface winds blow the material into the hundreds of thousands of dark fans visible from orbit. By surveying the direction, frequency, and appearance of these dark fans (a proxy for the jets) and exploring how varying factors impact these properties, we can better understand the Martian climate. Over eons, the south polar CO2 jet process also carves channels and pits (dubbed araneiforms) into the surface. It is difficult if not impossible for computer algorithms to accurately identify the hundreds of thousands of individual fans visible within orbital imagery and map the locations of araneiforms in spacecraft observations. But these features are easily spotted by the human eye. Referred to as ‘crowdsourcing’ or ‘citizen science’, the combined assessment of many non-expert human classifiers with minimal training can equal or best that of a trained expert and in many cases outperform the best machine-learning algorithms.

Planet Four (http://www.planetfour.org) and Planet Four: Terrains (http://terrains.planetfour.org) are citizen science projects mining Mars Reconnaissance Orbiter (MRO) images to explore the seasonal processes on Mars’ polar regions. Planet Four enlists over 136,000 volunteers to map the sizes, shapes, and orientations of these fans in high resolution images. Planet Four is creating an unprecedented wind map of the south pole of Mars in order to probe how the Martian climate changes over time and is impacted year to year by dust storms and other global-scale events. Planet Four: Terrains, aims to study the distribution of the jet process across the south pole and identify new targets of interest for MRO. Over 12,000 people have helped identify araneiforms carved during the CO2 jet formation process.

In this talk, I'll give an overview of Planet Four and Planet Four: Terrains and present the latest results from these projects from combining the multiple volunteer assessments together. In particular, I will present Planet Four fan directions, examine some of the inter-annual variability of the fans over the Martian south polar region, and compare the inferred wind directions to Martian climate models. I’ll also present preliminary results from training a neural network with the Planet Four volunteer assessments.

Grand Ballroom