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Multivariate Data Fusion and Uncertainty Quantification for Remote Sensing
Completed
TRL 6 (started at 3, targeting 6)
Description
Formulate and implement algorithms for fusing data from multiple remote sensing instruments to optimally estimate CO2 vertical profiles. Provide formal measures of uncertainty associated with data fusion output. Demonstrate with data from AIRS and ACOS/OCO-2 with ability to include OCO-3, ASCENDS, and other sources when available. Work with science partners to demonstrate value for evaluating and improving CO2 transport models.
Benefits
SMAP
Details
| Technology area | Software, Modeling, Simulation, and Information Processing > Modeling > Science Modeling |
| Program | Advanced Information Systems Technology (AIST) |
| Lead organization | NASA Headquarters, Washington, DC |
| Start date | 2009-05-01 |
| End date | 2012-04-30 |
Project contacts
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