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Invited Guest Speaker at the Taylor Geospatial Institutes GEOAI Gathering
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By NASA
4 min read
Entrepreneurs Challenge Winner PRISM is Using AI to Enable Insights from Geospatial Data
PRISM’s platform uses AI segmentation to identify and highlight residential structures in a neighborhood. NASA sponsored Entrepreneurs Challenge events in 2020, 2021, and 2023 to invite small business start-ups to showcase innovative ideas and technologies with the potential to advance the agency’s science goals. To potentially leverage external funding sources for the development of innovative technologies of interest to NASA, SMD involved the venture capital community in Entrepreneurs Challenge events. Challenge winners were awarded prize money, and in 2023 the total Entrepreneurs Challenge prize value was $1M. Numerous challenge winners have subsequently refined their products and/or received funding from NASA and external sources (e.g., other government agencies or the venture capital community) to further develop their technologies.
One 2023 Entrepreneurs Challenge winner, PRISM Intelligence (formerly known as Pegasus Intelligence and Space), is using artificial intelligence (AI) and other advances in computer vision to create a new platform that could provide geospatial insights to a broad community.
Every day, vast amounts of remote sensing data are collected through satellites, drones, and aerial imagery, but for most businesses and individuals, accessing and extracting meaningful insights from this data is nearly impossible.
The company’s product—Personal Real-time Insight from Spatial Maps, a.k.a. PRISM—is transforming geospatial data into an easy-to-navigate, queryable world. By leveraging 3D computer vision, geospatial analytics, and AI-driven insights, PRISM creates photorealistic, up-to-date digital environments that anyone can interact with. Users can simply log in and ask natural-language questions to instantly retrieve insights—no advanced Geographic Information System (GIS) expertise is required.
For example, a pool cleaner looking for business could use PRISM to search for all residential pools in a five-mile radius. A gardener could identify overgrown trees in a community. City officials could search for potholes in their jurisdiction to prioritize repairs, enhance public safety, and mitigate liability risks. This broad level of accessibility brings geospatial intelligence out of the hands of a few and into everyday decision making.
The core of PRISM’s platform uses radiance fields to convert raw 2D imagery into high-fidelity, dynamic 3D visualizations. These models are then enhanced with AI-powered segmentation, which autonomously identifies and labels objects in the environment—such as roads, vehicles, buildings, and natural features—allowing for seamless search and analysis. The integration of machine learning enables PRISM to refine its reconstructions continuously, improving precision with each dataset. This advanced processing ensures that the platform remains scalable, efficient, and adaptable to various data sources, making it possible to produce large-scale, real-time digital twins of the physical world.
The PRISM platform’s interface showcasing a 3D digital twin of California State Polytechnic University, Pomona, with AI-powered search and insights. “It’s great being able to push the state of the art in this relatively new domain of radiance fields, evolving it from research to applications that can impact common tasks. From large sets of images, PRISM creates detailed 3D captures that embed more information than the source pictures.” — Maximum Wilder-Smith, Chief Technology Officer, PRISM Intelligence
Currently the PRISM platform uses proprietary data gathered from aerial imagery over selected areas. PRISM then generates high-resolution digital twins of cities in select regions. The team is aiming to eventually expand the platform to use NASA Earth science data and commercial data, which will enable high-resolution data capture over larger areas, significantly increasing efficiency, coverage, and update frequency. PRISM aims to use the detailed multiband imagery that NASA provides and the high-frequency data that commercial companies provide to make geospatial intelligence more accessible by providing fast, reliable, and up-to-date insights that can be used across multiple industries.
What sets PRISM apart is its focus on usability. While traditional GIS platforms require specialized training to use, PRISM eliminates these barriers by allowing users to interact with geospatial data through a frictionless, conversational interface.
The impact of this technology could extend across multiple industries. Professionals in the insurance and appraisal industries have informed the company how the ability to generate precise, 3D assessments of properties could streamline risk evaluations, reduce costs, and improve accuracy—replacing outdated or manual site visits. Similarly, local governments have indicated they could potentially use PRISM to better manage infrastructure, track zoning compliance, and allocate resources based on real-time, high-resolution urban insights. Additionally, scientists could use the consistent updates and layers of three-dimensional data that PRISM can provide to better understand changes to ecosystems and vegetation.
As PRISM moves forward, the team’s focus remains on scaling its capabilities and expanding its applications. Currently, the team is working to enhance the technical performance of the platform while also adding data sources to enable coverage of more regions. Future iterations will further improve automation of data processing, increasing the speed and efficiency of real-time 3D reconstructions. The team’s goal is to expand access to geospatial insights, ensuring that anyone—from city planners to business owners—can make informed decisions using the best possible data.
PRISM Intelligence founders Zachary Gaines, Hugo Delgado, and Maximum Wilder-Smith in their California State Polytechnic University, Pomona lab, where the company was first formed. Share
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Last Updated Apr 21, 2025 Related Terms
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By NASA
An image of a coastal marshland combines aerial and satellite views in a technique similar to hyperspectral imaging. Combining data from multiple sources gives scientists information that can support environmental management.John Moisan When it comes to making real-time decisions about unfamiliar data – say, choosing a path to hike up a mountain you’ve never scaled before – existing artificial intelligence and machine learning tech doesn’t come close to measuring up to human skill. That’s why NASA scientist John Moisan is developing an AI “eye.”
Oceanographer John MoisanNASA Moisan, an oceanographer at NASA’s Wallops Flight Facility near Chincoteague, Virginia, said AI will direct his A-Eye, a movable sensor. After analyzing images his AI would not just find known patterns in new data, but also steer the sensor to observe and discover new features or biological processes.
“A truly intelligent machine needs to be able to recognize when it is faced with something truly new and worthy of further observation,” Moisan said. “Most AI applications are mapping applications trained with familiar data to recognize patterns in new data. How do you teach a machine to recognize something it doesn’t understand, stop and say ‘What was that? Let’s take a closer look.’ That’s discovery.”
Finding and identifying new patterns in complex data is still the domain of human scientists, and how humans see plays a large part, said Goddard AI expert James MacKinnon. Scientists analyze large data sets by looking at visualizations that can help bring out relationships between different variables within the data.
Infrared images like this one from a marsh area on the Maryland/Virginia Eastern Shore coastal barrier and back bay regions reveal clues to scientists about plant health, photosynthesis, and other conditions that affect vegetation and ecosystems.John Moisan It’s another story to train a computer to look at large data streams in real time to see those connections, MacKinnon said. Especially when looking for correlations and inter-relationships in the data that the computer hasn’t been trained to identify.
Moisan intends first to set his A-Eye on interpreting images from Earth’s complex aquatic and coastal regions. He expects to reach that goal this year, training the AI using observations from prior flights over the Delmarva Peninsula. Follow-up funding would help him complete the optical pointing goal.
“How do you pick out things that matter in a scan?” Moisan asked. “I want to be able to quickly point the A-Eye at something swept up in the scan, so that from a remote area we can get whatever we need to understand the environmental scene.”
Moisan’s on-board AI would scan the collected data in real-time to search for significant features, then steer an optical sensor to collect more detailed data in infrared and other frequencies.
Thinking machines may be set to play a larger role in future exploration of our universe. Sophisticated computers taught to recognize chemical signatures that could indicate life processes, or landscape features like lava flows or craters, might offer to increase the value of science data returned from lunar or deep-space exploration.
Today’s state-of-the-art AI is not quite ready to make mission-critical decisions, MacKinnon said.
“You need some way to take a perception of a scene and turn that into a decision and that’s really hard,” he said. “The scary thing, to a scientist, is to throw away data that could be valuable. An AI might prioritize what data to send first or have an algorithm that can call attention to anomalies, but at the end of the day, it’s going to be a scientist looking at that data that results in discoveries.”
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Last Updated Feb 10, 2025 Related Terms
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By NASA
NASA’s Ames Research Center in California’s Silicon Valley, is celebrating 85 years of cutting-edge research and development in space, life sciences, supercomputing, aeronautics, and more for the benefit of humanity. Ames was founded as an aeronautical laboratory in December 1939, and has since contributed to many of NASA’s flagship missions from Apollo to Artemis.
NASA Ames experts are available for interviews Thursday, Dec. 19, and Friday, Dec. 20. To request an interview about the center’s legacy in space, science, technology, and aeronautics, email the Ames newsroom at: arc-dl-newsroom@mail.nasa.gov.
NASA Ames experts include:
James Anderson, NASA Ames historian; Lynn Harper, lead of integrative studies in the NASA Space Portal, working to propel U.S. industry toward the development of a sustainable, scalable, and profitable non-NASA demand for services and products manufactured in the microgravity environment of low Earth orbit; Shivanjli Sharma, aerospace research engineer, working to enable advanced aviation technologies for new methods of air cargo and passenger transportation in urban, suburban, rural, and regional communities; Dave Alfano, chief of the Ames Intelligent Systems Division, working to produce ground and flight software systems and data architectures for data mining, analysis, integration, and management; integrated health management, and more for missions across the agency. Ames has established itself as a leader in the aeronautics industry, developing foundational technologies for advanced air vehicles, including air taxis and remotely piloted aircraft. On the International Space Station, Ames researchers have tested a method to develop nutrients off-Earth and on-demand. Cube-shaped robots have been delivered to the station to assist astronauts with routine duties. Ames engineers have developed and are testing a heat shield for the Orion crew capsule that will safely return astronauts home to Earth as part of the agency’s Artemis missions to the Moon.
For more information on Ames’ history and contributions, visit:
https://www.nasa.gov/reference/ames-history
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Rachel Hoover
Ames Research Center, Silicon Valley, Calif.
650-604-4789
rachel.l.hoover@nasa.gov
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By NASA
Media are invited to learn about a unique series of flight tests happening in Virginia in partnership between NASA and GE Aerospace that aim to help the aviation industry better understand contrails and their impact on the Earth’s climate. Contrails are the lines of clouds that can be created by high-flying aircraft, but they may have an unseen effect on the planet – trapping heat in the atmosphere.
The media event will occur from 9 a.m.-12 p.m. on Monday, Nov. 25 at NASA’s Langley Research Center in Hampton, Virginia. NASA Langley’s G-III aircraft and mobile laboratory, as well as GE Aerospace’s 747 Flying Test Bed (FTB) will be on site. NASA project researchers and GE Aerospace’s flight crew will be available to discuss the Contrail Optical Depth Experiment (CODEX), new test methods and technologies used, and the real-world impacts of understanding and managing contrails. Media interested in attending must contact Brittny McGraw at brittny.v.mcgraw@nasa.gov no later than 12 p.m. EST, Friday, Nov. 22.
Flights for CODEX are being conducted this week. NASA Langley’s G-III will follow GE Aerospace’s FTB in the sky and scan the aircraft wake with Light Detection and Ranging (LiDAR) technology. This will advance the use of LiDAR by NASA to generate three-dimensional imaging of contrails to better characterize how contrails form and how they behave over time.
For more information about NASA’s work in green aviation tech, visit:
https://www.nasa.gov/aeronautics/green-aero-tech
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David Meade
Langley Research Center, Hampton, Virginia
757-751-2034 davidlee.t.meade@nasa.gov
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By NASA
2 min read
Geospatial AI Foundation Model Team Receives NASA Marshall Group Achievement Award
Rahul Ramachandran of NASA IMPACT, left, Elizabeth Fancher of NASA IMPACT, Ankur Kumar of the University of Alabama in Huntsville (UAH), Sujit Roy of UAH, Raghu Ganti of IBM Research, David McKenzie of NASA, Muthukumaran Ramasubramanian of UAH, Iksha Gurung of UAH, and Manil Maskey of NASA IMPACT, right, accept the NASA Marshall Space Flight Center Group Achievement Award on Thursday, August 15, 2024 at NASA Marshall. NASA NASA’s science efforts aim to empower scientists with the tools to perform research into our planet and universe. To this end, a collaborative effort between NASA and IBM created an AI geospatial foundation model, which was released as an open-source application in 2024.
Trained on vast amounts of NASA Earth science data, the foundation model can be adapted for Earth science applications such as flood, burn scar, and cropland studies. Tailoring the model for a specific task takes far less data than the original training set, providing an easy path for researchers to perform AI-powered studies.
For their groundbreaking work on this project, the development team behind the foundation model has received the NASA Marshall Space Flight Center Group Achievement Award. Their success with the model showcases their commitment to advancing AI and scientific research and will inspire progress in this field for years to come.
The team members from NASA’s Marshall Space Fight Center /IMPACT (Interagency Implementation and Advanced Concepts Team) are:
Rahul Ramachandran Manil Maskey Elizabeth Fancher The team members from the University of Alabama in Huntsville (UAH) are:
Sujit Roy Ankur Kumar Christopher Phillips Iksha Gurung Muthukumaran Ramasubramanian The team members from IBM are:
Ranjini Bangalore Juan Bernabe-Moreno Dario Augusto Borges Oliveira Linsong Chu Blair Edwards Paolo Fraccaro Carlos Gomes Raghu Ganti Adnan Hoque Johannes Jakubik Levente Klein Devyani Lambhate Gabby Nyirjesy Naomi Simumba Johannes Schmude Mudhakar Srivatsa Harini Srinivasan Daniela Szwarcman Rob Parkin Kommy Weldemariam Campbell Watson Bianca Zadrozny The team members from Clark University are:
Hamed Alemohammad Michael Cecil Steve Li Sam Khallaghi Denys Godwin Maryam Ahmadi Fatemeh Kordi To learn more about the NASA projects improving accessible science discovery for the benefit of all, visit the Open Science at NASA page.
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Last Updated Aug 15, 2024 Related Terms
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