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By NASA
5 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Cloud cover can keep optical instruments on satellites from clearly capturing Earth’s surface. Still in testing, JPL’s Dynamic Targeting uses AI to avoid imaging clouds, yielding a higher proportion of usable data, and to focus on phenomena like this 2015 volcanic eruption in Indonesia Landsat 8 captured.NASA/USGS A technology called Dynamic Targeting could enable spacecraft to decide, autonomously and within seconds, where to best make science observations from orbit.
In a recent test, NASA showed how artificial intelligence-based technology could help orbiting spacecraft provide more targeted and valuable science data. The technology enabled an Earth-observing satellite for the first time to look ahead along its orbital path, rapidly process and analyze imagery with onboard AI, and determine where to point an instrument. The whole process took less than 90 seconds, without any human involvement.
Called Dynamic Targeting, the concept has been in development for more than a decade at NASA’s Jet Propulsion Laboratory in Southern California. The first of a series of flight tests occurred aboard a commercial satellite in mid-July. The goal: to show the potential of Dynamic Targeting to enable orbiters to improve ground imaging by avoiding clouds and also to autonomously hunt for specific, short-lived phenomena like wildfires, volcanic eruptions, and rare storms.
This graphic shows how JPL’s Dynamic Targeting uses a lookahead sensor to see what’s on a satellite’s upcoming path. Onboard algorithms process the sensor’s data, identifying clouds to avoid and targets of interest for closer observation as the satellite passes overhead.NASA/JPL-Caltech “The idea is to make the spacecraft act more like a human: Instead of just seeing data, it’s thinking about what the data shows and how to respond,” says Steve Chien, a technical fellow in AI at JPL and principal investigator for the Dynamic Targeting project. “When a human sees a picture of trees burning, they understand it may indicate a forest fire, not just a collection of red and orange pixels. We’re trying to make the spacecraft have the ability to say, ‘That’s a fire,’ and then focus its sensors on the fire.”
Avoiding Clouds for Better Science
This first flight test for Dynamic Targeting wasn’t hunting specific phenomena like fires — that will come later. Instead, the point was avoiding an omnipresent phenomenon: clouds.
Most science instruments on orbiting spacecraft look down at whatever is beneath them. However, for Earth-observing satellites with optical sensors, clouds can get in the way as much as two-thirds of the time, blocking views of the surface. To overcome this, Dynamic Targeting looks 300 miles (500 kilometers) ahead and has the ability to distinguish between clouds and clear sky. If the scene is clear, the spacecraft images the surface when passing overhead. If it’s cloudy, the spacecraft cancels the imaging activity to save data storage for another target.
“If you can be smart about what you’re taking pictures of, then you only image the ground and skip the clouds. That way, you’re not storing, processing, and downloading all this imagery researchers really can’t use,” said Ben Smith of JPL, an associate with NASA’s Earth Science Technology Office, which funds the Dynamic Targeting work. “This technology will help scientists get a much higher proportion of usable data.”
How Dynamic Targeting Works
The testing is taking place on CogniSAT-6, a briefcase-size CubeSat that launched in March 2024. The satellite — designed, built, and operated by Open Cosmos — hosts a payload designed and developed by Ubotica featuring a commercially available AI processor. While working with Ubotica in 2022, Chien’s team conducted tests aboard the International Space Station running algorithms similar to those in Dynamic Targeting on the same type of processor. The results showed the combination could work for space-based remote sensing.
Since CogniSAT-6 lacks an imager dedicated to looking ahead, the spacecraft tilts forward 40 to 50 degrees to point its optical sensor, a camera that sees both visible and near-infrared light. Once look-ahead imagery has been acquired, Dynamic Targeting’s advanced algorithm, trained to identify clouds, analyzes it. Based on that analysis, the Dynamic Targeting planning software determines where to point the sensor for cloud-free views. Meanwhile, the satellite tilts back toward nadir (looking directly below the spacecraft) and snaps the planned imagery, capturing only the ground.
This all takes place in 60 to 90 seconds, depending on the original look-ahead angle, as the spacecraft speeds in low Earth orbit at nearly 17,000 mph (7.5 kilometers per second).
What’s Next
With the cloud-avoidance capability now proven, the next test will be hunting for storms and severe weather — essentially targeting clouds instead of avoiding them. Another test will be to search for thermal anomalies like wildfires and volcanic eruptions. The JPL team developed unique algorithms for each application.
“This initial deployment of Dynamic Targeting is a hugely important step,” Chien said. “The end goal is operational use on a science mission, making for a very agile instrument taking novel measurements.”
There are multiple visions for how that could happen — possibly even on spacecraft exploring the solar system. In fact, Chien and his JPL colleagues drew some inspiration for their Dynamic Targeting work from another project they had also worked on: using data from ESA’s (the European Space Agency’s) Rosetta orbiter to demonstrate the feasibility of autonomously detecting and imaging plumes emitted by comet 67P/Churyumov-Gerasimenko.
On Earth, adapting Dynamic Targeting for use with radar could allow scientists to study dangerous extreme winter weather events called deep convective ice storms, which are too rare and short-lived to closely observe with existing technologies. Specialized algorithms would identify these dense storm formations with a satellite’s look-ahead instrument. Then a powerful, focused radar would pivot to keep the ice clouds in view, “staring” at them as the spacecraft speeds by overhead and gathers a bounty of data over six to eight minutes.
Some ideas involve using Dynamic Targeting on multiple spacecraft: The results of onboard image analysis from a leading satellite could be rapidly communicated to a trailing satellite, which could be tasked with targeting specific phenomena. The data could even be fed to a constellation of dozens of orbiting spacecraft. Chien is leading a test of that concept, called Federated Autonomous MEasurement, beginning later this year.
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Melissa Pamer
Jet Propulsion Laboratory, Pasadena, Calif.
626-314-4928
melissa.pamer@jpl.nasa.gov
2025-094
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Last Updated Jul 24, 2025 Related Terms
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By NASA
6 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
NASA Ames research scientist Kristina Pistone monitors instrument data while onboard the Twin Otter aircraft, flying over Monterey Bay during the October 2024 deployment of the AirSHARP campaign. NASA/Samuel Leblanc In autumn 2024, California’s Monterey Bay experienced an outsized phytoplankton bloom that attracted fish, dolphins, whales, seabirds, and – for a few weeks in October – scientists. A team from NASA’s Ames Research Center in Silicon Valley, with partners at the University of California, Santa Cruz (UCSC), and the Naval Postgraduate School, spent two weeks on the California coast gathering data on the atmosphere and the ocean to verify what satellites see from above. In spring 2025, the team returned to gather data under different environmental conditions.
Scientists call this process validation.
Setting up the Campaign
The PACE mission, which stands for Plankton, Aerosol, Cloud, ocean Ecosystem, was launched in February 2024 and designed to transform our understanding of ocean and atmospheric environments. Specifically, the satellite will give scientists a finely detailed look at life near the ocean surface and the composition and abundance of aerosol particles in the atmosphere.
Whenever NASA launches a new satellite, it sends validation science teams around the world to confirm that the data from instruments in space match what traditional instruments can see at the surface. AirSHARP (Airborne aSsessment of Hyperspectral Aerosol optical depth and water-leaving Reflectance Product Performance for PACE) is one of these teams, specifically deployed to validate products from the satellite’s Ocean Color Instrument (OCI).
The OCI spectrometer works by measuring reflected sunlight. As sunlight bounces off of the ocean’s surface, it creates specific shades of color that researchers use to determine what is in the water column below. To validate the OCI data, research teams need to confirm that measurements directly at the surface match those from the satellite. They also need to understand how the atmosphere is changing the color of the ocean as the reflected light is traveling back to the satellite.
In October 2024 and May 2025, the AirSHARP team ran simultaneous airborne and seaborne campaigns. Going into the field during different seasons allows the team to collect data under different environmental conditions, validating as much of the instrument’s range as possible.
Over 13 days of flights on a Twin Otter aircraft, the NASA-led team used instruments called 4STAR-B (Spectrometer for sky-scanning sun Tracking Atmospheric Research B), and the C-AIR (Coastal Airborne In-situ Radiometer) to gather data from the air. At the same time, partners from UCSC used a host of matching instruments onboard the research vessel R/V Shana Rae to gather data from the water’s surface.
Ocean Color and Water Leaving Reflectance
The Ocean Color Instrument measures something called water leaving reflectance, which provides information on the microscopic composition of the water column, including water molecules, phytoplankton, and particulates like sand, inorganic materials, and even bubbles. Ocean color varies based on how these materials absorb and scatter sunlight. This is especially useful for determining the abundance and types of phytoplankton.
Photographs taken out the window of the Twin Otter aircraft during the October 2024 AirSHARP deployment showcase the variation in ocean color, which indicates different molecular composition of the water column beneath. The red color in several of these photos is due to a phytoplankton bloom – in this case a growth of red algae. NASA/Samuel Leblanc
The AirSHARP team used radiometers with matching technology – C-AIR from the air and C-OPS (Compact Optical Profiling System) from the water – to gather water leaving reflectance data.
“The C-AIR instrument is modified from an instrument that goes on research vessels and takes measurements of the water’s surface from very close range,” said NASA Ames research scientist Samuel LeBlanc. “The issue there is that you’re very local to one area at a time. What our team has done successfully is put it on an aircraft, which enables us to span the entire Monterey Bay.”
The larger PACE validation team will compare OCI measurements with observations made by the sensors much closer to the ocean to ensure that they match, and make adjustments when they don’t.
Aerosol Interference
One factor that can impact OCI data is the presence of manmade and natural aerosols, which interact with sunlight as it moves through the atmosphere. An aerosol refers to any solid or liquid suspended in the air, such as smoke from fires, salt from sea spray, particulates from fossil fuel emissions, desert dust, and pollen.
Imagine a 420 mile-long tube, with the PACE satellite at one end and the ocean at the other. Everything inside the tube is what scientists refer to as the atmospheric column, and it is full of tiny particulates that interact with sunlight. Scientists quantify this aerosol interaction with a measurement called aerosol optical depth.
“During AirSHARP, we were essentially measuring, at different wavelengths, how light is changed by the particles present in the atmosphere,” said NASA Ames research scientist Kristina Pistone. “The aerosol optical depth is a measure of light extinction, or how much light is either scattered away or absorbed by aerosol particulates.”
The team measured aerosol optical depth using the 4STAR-B spectrometer, which was engineered at NASA Ames and enables scientists to identify which aerosols are present and how they interact with sunlight.
Twin Otter Aircraft
AirSHARP principal investigator Liane Guild walks towards a Twin Otter aircraft owned and operated by the Naval Postgraduate School. The aircraft’s ability to perform complex, low-altitude flights made it the ideal platform to fly multiple instruments over Monterey Bay during the AirSHARP campaign. NASA/Samuel Leblanc
Flying these instruments required use of a Twin Otter plane, operated by the Naval Postgraduate School (NPS). The Twin Otter is unique for its ability to perform extremely low-altitude flights, making passes down to 100 feet above the water in clear conditions.
“It’s an intense way to fly. At that low height, the pilots continually watch for and avoid birds, tall ships, and even wildlife like breaching whales,” said Anthony Bucholtz, director of the Airborne Research Facility at NPS.
With the phytoplankton bloom attracting so much wildlife in a bay already full of ships, this is no small feat. “The pilots keep a close eye on the radar, and fly by hand,” Bucholtz said, “all while following careful flight plans crisscrossing Monterey Bay and performing tight spirals over the Research Vessel Shana Rae.”
Campaign Data
Data gathered from the 2024 phase of this campaign is available on two data archive systems. Data from the 4STAR instrument is available in the PACE data archive and data from C-AIR is housed in the SeaBASS data archive.
Other data from the NASA PACE Validation Science Team is available through the PACE website: https://pace.oceansciences.org/pvstdoi.htm#
Samuel LeBlanc and Kristina Pistone are funded via the Bay Area Environmental Research Institute (BAERI), which is a scientist-founded nonprofit focused on supporting Earth and space sciences.
About the Author
Milan Loiacono
Science Communication SpecialistMilan Loiacono is a science communication specialist for the Earth Science Division at NASA Ames Research Center.
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Last Updated Jun 26, 2025 Related Terms
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