The technique, refined by Brown scholars Benjamin Boatwright and James Head, is pivotal for identifying lunar surface features like craters and ridges. These maps are critical for planning safe landing sites and scientific exploration areas.
"It helps us piece together a better idea of what is actually there," said Boatwright, lead author of the study. "We need to understand the surface topography of the Moon where there isn't as much light, like the shadowed areas of the lunar south pole where NASA's Artemis missions are targeting. That will allow autonomous landing software to navigate and avoid hazards, like large rocks and boulders, that could endanger a mission. For that reason, you need models that map the topography of the surface at as high a resolution as possible because the more detail you have, the better."
The improved technique addresses the labor-intensive nature of previous methods and issues with complex lighting conditions. Advanced computer algorithms now automate much of the process and increase the resolution of the models.
"Shape-from-shading requires that the images that you're using be perfectly aligned with one another so that a feature in one image is in the exact same place in another image to build up those layers of information, but current tools are not quite in a place where you can just give it bunches of images and it'll spit out a perfect product," Boatwright said. "We implemented an image alignment algorithm where it picks out features in one image and tries to find those same features in the other and then line them up, so that you're not having to sit there manually tracing interest points across multiple images, which takes a lot a of hours and brain power."
Additional quality control algorithms and filters reduce errors in image alignment, enhancing precision to submeter resolutions. This improvement allows for larger surface areas to be mapped quickly.
The accuracy of the new maps was validated by comparing them with existing topographic models, revealing more precise lunar surface features. Data from NASA's Lunar Reconnaissance Orbiter instruments were primarily used in the study.
The researchers aim to produce and share these refined lunar maps using open-source algorithms, hoping to benefit both human and robotic exploration missions.
"These new map products are significantly better than what we had in exploration planning during the Apollo missions, and they will very much improve the mission planning and scientific return for Artemis and robotic missions," said Head, who contributed to the Apollo program.
Boatwright emphasized the broader impact, stating, "There's a wealth of information to be gained from making these types of tools accessible to all. It's an egalitarian way of doing science."
Research Report:Shape-from-shading Refinement of LOLA and LROC NAC Digital Elevation Models: Applications to Upcoming Human and Robotic Exploration of the Moon
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