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By NASA
iss071e650763 (Sept. 14, 2024) — The long exposure photograph taken by NASA astronaut Matthew Dominick shows star trails, streaks of city lights, and two Roscosmos crew ships, the Soyuz MS-26 docked to the Rassvet module (foreground) and the Soyuz MS-25 (background) docked to the Prichal docking module, as the International Space Station orbited 265 miles above central China.NASA Space Station trajectory data is now available to the public!
This data, called an ephemeris, is generated by the ISS Trajectory Operations and Planning Officer (TOPO) flight controllers in the Mission Control Center at NASA’s Johnson Space Center. TOPO keeps track of where the ISS is, where it is going to be, and most importantly makes sure it isn’t at risk of colliding with other objects in space. At ISS’s altitude, a very thin atmosphere is still present. This thin atmosphere creates drag and over time can cause TOPO’s predicted ISS trajectory to accumulate error. Because of this, TOPO updates the predicted trajectory approximately three times a week, so the ISS Flight Control Team has the best trajectory estimate possible. An accurate trajectory is essential for maintaining communications links, planning visiting vehicle rendezvous, and ensuring ISS’s path is clear of any potential collisions.
The links above and below are to the most current posted ephemeris. The ephemeris is in the CCSDS Orbital Ephemeris Message (OEM) standard and is available in .txt and .xml file formats. Each file contains header lines with the ISS mass in kg, drag area in m2, and drag coefficient used in generating the ephemeris. The header also contains lines with details for the first and last ascending nodes within the ephemeris span. Following this is a listing of upcoming ISS translation maneuvers, called “reboosts,” and visiting vehicle launches, arrivals, and departures.
After the header, ISS state vectors in the Mean of J2000 (J2K) reference frame are listed at four-minute intervals spanning a total length of 15 days. During reboosts (translation maneuvers), the state vectors are reported in two-second intervals. Each state vector lists the time in UTC; position X, Y, and Z in km; and velocity X, Y, and Z in km/s.
Orbit Ephemeris Message (OEM)
https://nasa-public-data.s3.amazonaws.com/iss-coords/current/ISS_OEM/ISS.OEM_J2K_EPH.txt https://nasa-public-data.s3.amazonaws.com/iss-coords/current/ISS_OEM/ISS.OEM_J2K_EPH.xml Users of this data should monitor this page for information regarding any future changes to the file format. Past data postings can be found archived on data.nasa.gov by searching “ISS COORDS.”
NOTE: NASA is providing this information for use by the general public. The OEM data format is supported natively by many commercial spaceflight software applications. Please consult your application’s support documentation for specific details on how to deploy this data.
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By NASA
1 Min Read 2024 NESC Technical Update
Annual Report of NESC Technical Activities
On behalf of the NASA Engineering and Safety Center (NESC), I am pleased to provide you with the 2024 NESC Technical Update. This annual report summarizes the technical work, engineering advancements, and knowledge capture efforts we made in FY24. With support provided by members of our NASA community from across the centers, we focused our efforts on performing value-added independent testing, analysis, and assessments of NASA’s high-risk projects to ensure safety and mission success.
This report contains summaries of technical assessments requested by our stakeholders and the technical bulletins and innovative techniques that resulted from that assessment work. Several of the NASA Technical Fellows provide summaries of accomplishments in their respective disciplines, and expertise drawn from across the Agency is featured on the Center Pages.
We appreciate the opportunity to share our progress and highlight the accomplishments of our technically and culturally diverse, multidisciplinary, multigenerational teams. All NESC knowledge products are available at nasa.gov/nesc. As always, we value your feedback and engagement. Thank you for your continuing support of the NESC.
Timmy R. Wilson
Director, NASA Engineering and Safety Center
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By NASA
Earth Observer Earth Home Earth Observer Home Editor’s Corner Feature Articles Meeting Summaries News Science in the News Calendars In Memoriam More Archives 4 min read
2024 AGU Fall Meeting Hyperwall Schedule
NASA Science at AGU Fall Meeting Hyperwall Schedule, December 9-12, 2024
Join NASA in the Exhibit Hall (Booth #719) for Hyperwall Storytelling by NASA experts. Full Hyperwall Agenda below.
***Copies of the 2025 NASA Science Calendar will be distributed at the NASA Exhibit at the start of each day.***
MONDAY, DECEMBER 9
3:20 – 3:40 PM From Stars to Life: The Power of NASA Science Dr. Nicola Fox 3:40 – 4:00 PM NASA Planetary Science Division: 2024 Highlights Eric Ianson (PSD Deputy Director) 4:00 – 4:20 PM NASA Earth Science Overview Dr. Karen St. Germain 4:20 – 4:40 PM NASA Astrophysics: Looking Forward Dr. Mark Clampin 4:40 – 5:00 PM Helio Big Year Wind-Down and a Look Ahead Dr. Joseph Westlake 5:00 – 5:20 PM NASA Biological & Physical Sciences Overview Dr. Lisa Carnell 5:20 – 5:40 PM Astrobiology: The Science, The Program, and The Work Dr. Becky McCauley Rench TUESDAY, DECEMBER 10
10:15 – 10:30 AM Integration of Vantage Points and Approaches by NASA Earth Science Division Dr. Jack Kaye 10:30 – 10:45 AM Life after launch: A Snapshot of the First 9 Months of NASA’s PACE Mission Jeremy Werdell 10:45 – 11:00 AM Foundation Model in Earth Science: Towards Earth Science to Action Tsengdar Lee 11:15 – 11:30 AM NASA’s Office of the Chief Science Data Officer: Supporting a More Equitable, Impactful, and Efficient Scientific Future Kevin Murphy 11:30- 11:45 AM 30 Years of GLOBE: Advancing Earth System Science, Education, and Public Engagement Amy P. Chen 11:45 – 12:00 PM 2024 NASA Visualization Highlights Mark Subbarao 12:30 – 1:45 PM Grand Prize Winners of 2024 AGU Michael H. Freilich Student Visualization Competition Introductory Remarks from AGU & NASA Steve Platnick Thawing History: Retracing Arctic Expeditions in a Warming World Dylan Wootton Monitoring the Weather in Near Real-Time with Open-Access GOES-R Data Jorge Bravo Mitigating Agricultural Runoff with Tangible Landscape Caitlin Haedrich Earth Observation for Disaster Response: Highlighting Applied Products Patrick Kerwin 2:15 – 2:30 PM Water Science to Water Action John Bolten 2:30 – 2:45 PM Analyzing Space Weather at Mars Gina DiBraccio, Jamie Favors 2:45 – 3:00 PM NASA Airborne in the Arctic: An overview of the NASA Arctic Radiation-Cloud-aerosol-Surface-Interaction eXperiment (ARCSIX) Patrick Taylor 3:00 – 3:15 PM Science Activation and the 2023-24 Eclipses Lin Chambers 3:30 – 3:45 PM Tracking Extreme Fires in 2024 Douglas Morton 3:45 – 4:00 PM BioSCape: A Biodiversity Airborne Campaign in South Africa Anabelle Cardoso 4:00 – 4:15 PM U.S. Greenhouse Gas Center Lesley Ott 4:15 – 4:30 PM Data Governance and Space Data Ethics in the Era of AI: NASA Acres at the Leading Edge Alyssa Whitcraft, Todd Janzen 5:00 – 5:15 PM Global GEOS Forecasts of Severe Storms and Tornado Activity Across the United States William Putman 5:15 – 5:30 PM NASA Earth Action Empowering Health and Air Quality Communities John Haynes 5:30 – 5:45 PM The Habitable Worlds Observatory Megan Ansdell WEDNESDAY, DECEMBER 11
10:15 – 10:30 AM From Orbit to Earth: Exploring the LEO Science Digest Jeremy Goldstein 10:30 – 10:45 AM Hello, Hello Again: How Lunar Samples Introduced Us to the Solar System, and What We’ll Learn When We Meet Again Dr. Barbara Cohen 10:45 – 11:00 AM Planetary Defenders: How NASA Safeguards Earth from Asteroids Kelly Fast 11:15 – 11:30 AM Bringing Science Data Home Philip Baldwin 11:30 – 11:45 AM Fast-Tracking Earth System Science into Action: The Vision for the Integrated Earth System Observatory Cecile Rousseaux 11:45 – 12:00 PM A Decade of Monitoring Atmospheric CO2 from Space Junjie Liu 12:30 – 1:45 PM Grand Prize Winners of 2024 AGU Michael H. Freilich Student Visualization Competition Introductory Remarks from AGU & NASA Dr. Jack Kaye Photogrammetric Modeling and Remote Identification of Small Lava Tubes in the 1961 Lava Flow at Askja, Iceland Mya Thomas Monitoring Air Quality Using MODIS and CALIPSO Data in Conjunction with Socioeconomic Data to Map Air Pollution in Hampton Roads Virginia Marilee Karinshak Visualizing UAV-Based Detection and Severity Assessment of Brown Spot Needle Blight in Pine Forests Swati Singh Different Temperatures of a Solar Flare Crisel Suarez 2:15 – 2:30 PM Ancient and Modern Sun Gazing: New view of our star as seen by CODEX and upcoming missions MUSE, PUNCH and SunRISE Dr. Nicholeen Viall, Dr. Jeff Newmark 2:30 – 2:45 PM A Stroll Through The Universe of NASA Citizen Science Sarah Kirn 2:45 – 3:00 PM OSIRIS-REx Returned Samples from the Early Solar System Jason Dworkin 3:00 – 3:15 PM To the Moon, Together: Ensuring Mission Success in an Increasingly Busy Lunar Environment Therese Jones 3:30 – 3:45 PM What Goes Around Comes Around – Repeating Patterns in Global Precipitation George Huffman 3:45 – 4:00 PM Parker Solar Probe: Thriving, Surviving, and Exploring our Sun to Make Paradigm Shifting Discoveries Nour Rawafi, Betsy Congdon 4:00 – 4:15 PM Europa Clipper Curt Niebur 4:15 – 4:30 PM Roman Space Telescope and Exoplanets Rob Zellem 5:00 – 5:15 PM Mars Exploration: Present and Future Dr. Lindsay Hays 5:15 – 5:30 PM Superstorm: The surprise entry into the Helio Big Year celebration of the Sun, and possibly a foreshadowing of what’s to come during Solar Maximum Kelly Korrek 5:30 – 5:45 PM From EARTHDATA to Action: Enabling Earth Science Data to Serve Society Katie Baynes THURSDAY, DECEMBER 12
10:15 – 10:30 AM Geospace Dynamics Constellation: The Space Weather Rosetta Stone Katherine Garcia-Sage, Doug Rowland 10:30 – 10:45 AM Future of Magnetosphere to Ionosphere Coupling Lara Waldrop, Skyler Kleinschmidt, Sam Yee 10:45 – 11:00 AM NASA ESTO: Launchpad for Novel Earth Science Technologies Michael Seablom 11:00 – 11:15 AM From Leaf to Orbit: NASA Research Reveals the Changing Northern Landscape Dr. Liz Hoy 11:30 – 11:45 PM OpenET: Filling a Critical Data Gap in Water Management Forrest Melton 11:45 – 12:00 PM Dragonfly: Flights of Exploration Across Saturn’s Moon Titan, an Organic Ocean World Zibi Turtle 12:00 – 12:15 PM Venus and DAVINCI Natasha Johnson 12:15 – 12:30 PM IMAP: The Modern-Day Celestial Cartographer Prof. David J. McComas Share
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Last Updated Dec 04, 2024 Related Terms
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By Space Force
STARCOM’s Delta 10 hosted the second annual Tactics Development Conference and the first with international partner participation.
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By NASA
4 min read
Expanded AI Model with Global Data Enhances Earth Science Applications
On June 22, 2013, the Operational Land Imager (OLI) on Landsat 8 captured this false-color image of the East Peak fire burning in southern Colorado near Trinidad. Burned areas appear dark red, while actively burning areas look orange. Dark green areas are forests; light green areas are grasslands. Data from Landsat 8 were used to train the Prithvi artificial intelligence model, which can help detect burn scars. NASA Earth Observatory NASA, IBM, and Forschungszentrum Jülich have released an expanded version of the open-source Prithvi Geospatial artificial intelligence (AI) foundation model to support a broader range of geographical applications. Now, with the inclusion of global data, the foundation model can support tracking changes in land use, monitoring disasters, and predicting crop yields worldwide.
The Prithvi Geospatial foundation model, first released in August 2023 by NASA and IBM, is pre-trained on NASA’s Harmonized Landsat and Sentinel-2 (HLS) dataset and learns by filling in masked information. The model is available on Hugging Face, a data science platform where machine learning developers openly build, train, deploy, and share models. Because NASA releases data, products, and research in the open, businesses and commercial entities can take these models and transform them into marketable products and services that generate economic value.
“We’re excited about the downstream applications that are made possible with the addition of global HLS data to the Prithvi Geospatial foundation model. We’ve embedded NASA’s scientific expertise directly into these foundation models, enabling them to quickly translate petabytes of data into actionable insights,” said Kevin Murphy, NASA chief science data officer. “It’s like having a powerful assistant that leverages NASA’s knowledge to help make faster, more informed decisions, leading to economic and societal benefits.”
AI foundation models are pre-trained on large datasets with self-supervised learning techniques, providing flexible base models that can be fine-tuned for domain-specific downstream tasks.
Crop classification prediction generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. Focusing on diverse land use and ecosystems, researchers selected HLS satellite images that represented various landscapes while avoiding lower-quality data caused by clouds or gaps. Urban areas were emphasized to ensure better coverage, and strict quality controls were applied to create a large, well-balanced dataset. The final dataset is significantly larger than previous versions, offering improved global representation and reliability for environmental analysis. These methods created a robust and representative dataset, ideal for reliable model training and analysis.
The Prithvi Geospatial foundation model has already proven valuable in several applications, including post-disaster flood mapping and detecting burn scars caused by fires.
One application, the Multi-Temporal Cloud Gap Imputation, leverages the foundation model to reconstruct the gaps in satellite imagery caused by cloud cover, enabling a clearer view of Earth’s surface over time. This approach supports a variety of applications, including environmental monitoring and agricultural planning.
Another application, Multi-Temporal Crop Segmentation, uses satellite imagery to classify and map different crop types and land cover across the United States. By analyzing time-sequenced data and layering U.S. Department of Agriculture’s Crop Data, Prithvi Geospatial can accurately identify crop patterns, which in turn could improve agricultural monitoring and resource management on a large scale.
The flood mapping dataset can classify flood water and permanent water across diverse biomes and ecosystems, supporting flood management by training models to detect surface water.
Wildfire scar mapping combines satellite imagery with wildfire data to capture detailed views of wildfire scars shortly after fires occurred. This approach provides valuable data for training models to map fire-affected areas, aiding in wildfire management and recovery efforts.
Burn scar mapping generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. This model has also been tested with additional downstream applications including estimation of gross primary productivity, above ground biomass estimation, landslide detection, and burn intensity estimations.
“The updates to this Prithvi Geospatial model have been driven by valuable feedback from users of the initial version,” said Rahul Ramachandran, AI foundation model for science lead and senior data science strategist at NASA’s Marshall Space Flight Center in Huntsville, Alabama. “This enhanced model has also undergone rigorous testing across a broader range of downstream use cases, ensuring improved versatility and performance, resulting in a version of the model that will empower diverse environmental monitoring applications, delivering significant societal benefits.”
The Prithvi Geospatial Foundation Model was developed as part of an initiative of NASA’s Office of the Chief Science Data Officer to unlock the value of NASA’s vast collection of science data using AI. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT), based at Marshall, IBM Research, and the Jülich Supercomputing Centre, Forschungszentrum, Jülich, designed the foundation model on the supercomputer Jülich Wizard for European Leadership Science (JUWELS), operated by Jülich Supercomputing Centre. This collaboration was facilitated by IEEE Geoscience and Remote Sensing Society.
For more information about NASA’s strategy of developing foundation models for science, visit https://science.nasa.gov/artificial-intelligence-science.
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Last Updated Dec 04, 2024 Related Terms
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