A Precise Mosaic View of Mars’s South Pole

A Precise Mosaic View of Mars’s South Pole

To get a precise view of a planet’s surface, scientists can build a mosaic using images captured by cameras mounted on an orbiting spacecraft. This process requires accounting for how the spacecraft and its camera were oriented when each photo was taken, as well as how that positioning corresponds to existing topographic data. Software speeds the task, but the process typically still demands a lot of manual work.

Now Robbins et al. have developed a workflow that automates many of the manual steps of the mosaic-building process. The novel approach eases the key challenge of accurately tying specific features, such as the rim of a crater, together in different images, minimizing the chance that small errors will accumulate.

To demonstrate the value of the new workflow, the researchers applied it to the Martian south pole and its surroundings. They selected this region because its dust storms, heavy frost, other harsh weather, and difficult lighting conditions make it particularly challenging to build an accurate mosaic with manual corrections.

The new workflow successfully generated a mosaic of the south polar region from 9,652 images captured by the Context Camera aboard the Mars Reconnaissance Orbiter and tied to topographic data collected by the Mars Orbiter Laser Altimeter. The mosaic comprises 255 billion pixels, with each pixel representing 6 meters of Martian ground, and is significantly more accurate than earlier mosaics of the same region.

The researchers have made the new mosaic and its underlying data publicly available as a resource for future Mars research through NASA’s Planetary Data System Cartography and Imaging Sciences Node Annex. Meanwhile, ongoing efforts by the authors and other researchers could apply the new workflow to create mosaics for other regions on Mars—or for other planetary bodies. (Earth and Space Science, https://doi.org/10.1029/2019EA001054, 2020)

—Sarah Stanley, Freelance Writer

Text © 2020. AGU. CC BY-NC-ND 3.0

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