LANHAM, MARYLAND – On Thursday, March 5, 2026, a.i. solutions announced a formal partnership with the U.S. Geological Survey (USGS) Technology Transfer Office (TTO) through a Cooperative Research and Development Agreement (CRADA). The collaboration is designed to modernize flight operations for the Landsat satellite constellation by implementing advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to improve mission reliability and operational efficiency.
The partnership focuses on the digital transformation of traditional flight dynamics. Under the terms of the CRADA, a.i. solutions will work alongside the USGS to explore automated solutions for anomaly triage, telemetry trending, and complex orbital mechanics analysis. This initiative follows a December 2024 Sources Sought Notice in which the USGS signaled its intent to optimize the long-standing Earth observation program through algorithmic automation.
Mission Parameters and Technical Scope
The Landsat fleet serves as a primary source of global land-use data, with assets maintaining a precise sun-synchronous orbit. The technical demands of the CRADA address the following operational realities:
- Velocity: Spacecraft travel at approximately 17,000 mph.
- Altitude: Operational orbit is maintained at 438 miles (705 km) above Earth.
- Focus Areas: AI/ML applications will specifically target telemetry analysis and “trending,” allowing flight controllers to predict component degradation before critical failures occur.
a.i. solutions, founded in 1996, has a deep history with the Landsat program, having previously provided flight dynamics support for the launch and commissioning of Landsat 9. The company’s flagship product, FreeFlyer, is widely utilized across civilian and military sectors for high-fidelity orbit determination and mission analysis.
Timeline for Implementation
The initial research phase is currently underway, utilizing extensive telemetry data libraries from the active Landsat 8 and Landsat 9 missions. The USGS and a.i. solutions intend to release periodic updates on the research findings as the AI models move from the training environment to integrated flight operations testbeds.
