What would take NASA’s geological map of the Moon to the next dimension? One excited geophysicist armed with 3D modelling software took on the challenge.
“I’m a Geoscientist, so I can appreciate the hard work that went into creating a product of that scale. I was impressed and also curious to understand the methodologies used to create this map. What type of gridding or image stitching and processing did they use to create this?” says Geoff Plastow project geophysicist at Seequent.
“This is the culmination of 50 years of science and data all sort of blended together into this one map. It’s quite amazing actually.”
The Unified Geologic Map of the Moon was the result of a combined effort by scientists at the United States Geological Survey (USGS), NASA, and Lunar Planetary Institute. Despite it seeming so alien, creating this otherworldly 2D map would have met problems familiar to any terrestrial geoscientist.
“You have all this data: some of which is digital, some of it is geo-referenced precisely. Pulling this all together was not an easy job. If you’re working on an exploration project or a mapping project here on Earth, you have the same problems on a slightly different scale”
The Moon map is essentially humanity’s most remote desktop survey.
There simply isn’t the time and resources to physically collect geological specimens everywhere on a site, whether that’s on Earth or in the ocean (much less the Moon). Geophysical surveys are able to collect data over large areas in remote places, no matter which planetary body they’re on.
“Here on Earth, we use remote sensing. We use satellite information. We use machine learning. We use whatever data is available. And, NASA did the same thing. They just did it on a different scale.”
Take a look into the data behind our pseudo-geological Moon model using Seequent Evo Web Visualisation in Seequent Central:
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Learn more about the Geologic Map of the Moon: https://www.usgs.gov/news/usgs-releases-first-ever-comprehensive-geologic-map-moon -
Using complementary techniques of laser altimeter missions and stereo image analysis, NASA has assembled a robust topographic map of the moon. -
The Apollo 11 Landing Site: Apollo 11, July 20th, 1969, Mare Tranquillitatis. “One small step for a man, one giant leap for mankind.” The first rock samples collected on the Moon. Also, the site of the first lunar geophysical survey to detect and quantify “moonquakes.” More info: https://www.lpi.usra.edu/lunar/missions/apollo/apollo_1 -
Free Air Gravity Disturbance from the NASA Grail mission. Details: https://en.wikipedia.org/wiki/GRAIL -
Bouguer Gravity Disturbance: Using the Lunar topography data, the topographic effects were removed from the Free Air Gravity to reveal sub-surface gravity anomalies. -
Using the Bouguer Gravity data, a depth to source estimate was made using Oasis montaj. On average, the crust thickness is ~50km. Blue represents Thin Crust, Yellow represents Thick Crust. -
Lunar Rock Density : Using VOXI Earth Modelling and Oasis montaj, a 3D inversion of the GRAIL gravity data was performed. The 3D model displays the recovered density values below the surface of the Moon.
Jump to the bottom of the story to watch a video walkthrough using web visualisation.
See you on the dark side of the Moon
Because of its orbit, there’s a side of the Moon that we don’t see. A lot of people likely went immediately to see the so-called “dark side” for themselves on the map. Geoff found one impressive feature that is hidden from our Earth-bound vantage point.
“It’s the largest known crater in our solar system. At around 2,500 km wide, the South Pole-Aitken Basin is larger than any crater that we have on Earth.”
Yet, that’s not all that drew his attention.
“I was attracted to the gravity data,” he laughs.
“To produce a lot of the structural and lineament data, I suspected that they used remote sensing gravity. They certainly have a pretty good digital elevation map as well, from various orbiting satellites missions. So, they used a combination of the digital elevation data, high resolution photography of the Moon’s surface, remote sensing spectral information, and of course, gravity.”
When you know what makes up a map, then you can determine: How can the data be modelled? Geoff looked at areas with high concentrations of gravity disturbances, mass concentrations, or “mass cons.”
Mass cons, or gravity disturbances, on any data set are always intriguing to geophysicists. The area around the South Pole-Aitken Basin had plenty to look at.
But first, there was a major issue with the Moon data that you wouldn’t have on Earth.
Getting your lunar bearings
A unique problem for this extraterrestrial map was that – GPS doesn’t exist on the Moon.
“How do you know where you’re standing on the Moon? Something we take for granted is the projected coordinate system. On Earth, we have many different coordinate systems, latitudes and longitudes, eastings and northings. What do you do on another planet?” explains Geoff.
The map uses a custom coordinate system for the Moon: Moon 2000. That way, the data and Geoff could get their bearings.
“All their different data sets need to talk to each other. All the gravity, spectrometry, and all of the maps with interpreted faults, they all need to talk to each other in the same spatial sense.”
NASA and the USGS graciously made all of the Moon map data public and available in Esri ArcGIS format.
“The one thing that struck me was when I opened it in Esri ArcGIS – Everything opened in the right location,” says Geoff.
“When I opened it, it opened up like a data set that I would just look at here in North America. The only the only difference is that in the bottom corner it said ‘Moon 2000.’”
Jumping into the data
Seequent is an Esri partner. Geoff knew that the data would integrate with Seequent geoscience software.
“When I saw this, I thought: Can I bring this into Oasis montaj or Target for ArcGIS? It has a coordinate system. And it is geoscience data…” Geoff says.
“And it opened pretty easily. I exported it from Esri ArcGIS. I did a little bit of data gymnastics to get it into just a more digestible format.”
Transferring the map data into Oasis montaj was just the first step.
“I was open able to open the geologic layers and the contacts and the lineaments and the gravity data. And I was able to reproduce a lot of the visualisations.”
Deeper into the dark side
The Unified Geologic Map of the Moon itself is in 2D, but the data sets within it hold 3D information. Gravity data is a geophysical measurement representing relative changes in rock density. You can look at different gravity readings to understand relative depths, densities, and sizes of structures beneath the surface.
“How deep are some of these gravity structures? How deep are they below the surface of the Moon? And then, like on terrestrial projects, we would want to get some idea of rock densities,” says Geoff.
How could you turn a 2D map into a 3D model? Thankfully, both a raw gravity data set and a corrected gravity data set were provided and offered the key.
As part of the Gravity Recovery and Interior Laboratory (GRAIL) project, NASA has covered the moon with Free-Air and Bouguer corrected gravity data.
“The [Bouguer] correction removes the topographic effects, they stripped them away using a digital elevation model that they’ve collected. And what that does is it provides us some insight into the structure below the topography,” Geoff explains.
“I worked with some of the potential field tools in Oasis montaj to determine quick source depth estimates, just to give us a quick ballpark idea of how deep some of these structures are.”
Next, Geoff took the corrected data set and sent it to the Cloud for a geophysical inversion, creating a 3D model (voxel), using VOXI Earth Modelling. Between preparing the data and completing the inversion, the entire process took just an hour and a half.
“I did what we would call an ‘unconstrained inversion’ in VOXI,” Geoff explains. This is a normal first step when working with a new dataset, especially one this large. We review and compare how well the observed gravity data matches the modelled gravity data and adjust the 3D modelling parameters as needed. We can always include more information to constrain the inversion, such has physical rock properties or structural information to improve our model.
Missing links
There’s also a lot that we don’t know. No one is drilling on the Moon. In total, the Apollo astronauts collected and returned just 381.69 kg of samples. It’s a surprising amount but even with those surface samples, vital geological data remains missing from below the surface.
“We know that there’s a fault or geologic contact. We can see it from the visual data from the satellite photogrammetry data, and then we can see it in the in the digital elevation model. We can interpret faults, but we don’t know what’s happening below the surface. We don’t know: Is the fault vertical? Or, is it a shallow fault? We have no idea what the dip direction is.”
Still, it was possible to bring the VOXI model into Seequent Central, a Cloud-hosted model collaboration and data management solution. This way, the grid data could be pulled directly into a Leapfrog Geo 3D geological model for further 3D development.
Interactive, 3D map of the Moon
The Leapfrog 3D model is far from perfect, but it’s one more small step for the Unified Geologic Map of the Moon – after a giant leap for interplanetary geoscience.
“In some sense, every geoscience model is incorrect. With the addition of new information, our models can be improved and refined.”
“So if we ever determined what dip direction is in some of these faults then, we can easily update the model and then begin to refine the geological and geophysical model.”
As much as Geoff was excited about the new Moon map, he was even more excited about what it meant for the future:
“It’s amazing to think that there are organisations and groups thinking about exploring asteroids as well. How can we take our learnings from this endeavor and apply that to an asteroid? It may sound like science fiction, but this work and research is already underway.”
Check out a walk through of all the layered data using Seequent Evo Web Visualisations: