CHANTILLY, Va., - Orion Space Solutions in Chantilly, Va. announced that it has been awarded a contract by the National Oceanic and Atmospheric Administration (NOAA) to support its Advanced Access Methods for Earth Observations Digital Twin (EO-DT) program. Work on the two-year project began this month in Silver Spring, Md.
The EO-DT program aims to improve the management and dissemination of critical data through digital twins of Earth, incorporating open science principles, findable, accessible, interoperable, and reusable (FAIR) data, and interoperability to meet the needs of diverse users. Orion's team will explore the use of natural language processing (NLP) and large language models (LLM) to enhance access to the vast amounts of data NOAA gathers from satellite sources.
As part of NOAA’s EO-DT Joint Ventures Program, Orion developed a digital twin platform that employs artificial intelligence and cloud-based high-performance computing to process, analyze, and visualize Earth observation data. The platform integrates observations from space, atmosphere, land, and sea into a single system, enabling users to model and study real-time, predictive, and hypothetical scenarios.
"At Orion, we take pride in our ability to apply scientific rigor and innovation to uncover new capabilities in mission-critical areas for our customers," said Chad Fish, president and general manager of Orion, which is a subsidiary of Archfield. "We have already proven how AI can be leveraged for enhanced space domain awareness and Earth observation, and we are excited to extend that work to satellite mission planning."
The new effort will focus on using NLP and LLM for advanced data processing, particularly in the areas of satellite digital twins, space weather, and space domain awareness. Orion plans to draw on its prior research to ensure the tools maintain credibility and preserve the integrity of information.
"Data is only as valuable as the insights that are gleaned from it," said Kevin Kelly, chief executive officer at Arcfield. "We are thrilled to expand on our successes from the EO-DT program and to demonstrate how we can transform observations into actionable insight that can be applied to real-world problems."
