PS 99-78 - NASA's next Earth observation mission to measure soil moisture, freeze/thaw, and net ecosystem exchange globally

Friday, August 6, 2010
Exhibit Hall A, David L Lawrence Convention Center
Joshua B. Fisher1, Kyle McDonald2, Mahta Moghaddam3, Sab Kim2, Michael Cosh4, Andreas Colliander2, Tom Jackson4, Erika Podest2 and Eni Njoku2, (1)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, (3)Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, (4)USDA ARS Hydrology and Remote Sensing Lab, Beltsville, MD
Background/Question/Methods

Soil moisture drives ecological patterns and processes, yet cannot be accurately determined at large spatial scales from direct measurements. It has been one of NASA’s chief Earth science goals to overcome this barrier using satellite remote sensing, and leading NASA’s top tier missions next to be launched is the SMAP mission (Soil Moisture Active-Passive) aimed at measuring soil moisture from space. Using a combination of active radar and passive microwave sensing, SMAP is able to penetrate clouds and moderately thick canopies to detect soil moisture in the top 5 cm of soil. These data, which will be among the most accurate and broadly distributed remote sensing measurements of soil moisture available, are used in turn with land surface and other models to generate products of root zone soil moisture (9 km), freeze/thaw state (3 km), and net ecosystem exchange (1 km).

Vegetation cover can interfere significantly with remote sensing-based retrieval of soil moisture. This interference depends on vegetation structure as well as water content. We conducted a large-scale field experiment (CanEx) in Canada during June 2010 to support algorithm testing and development for the SMAP mission. A goal of this campaign was to assess performance of the SMAP soil moisture retrieval algorithms in a boreal landscape. During CanEX, airborne and satellite active and passive microwave (L-band) data were acquired as well as a large set of in situ vegetation and soil measurements. 

Results/Conclusions

The in situ data are used to parameterize microwave radiative transfer models to assess the influence of forest structure on the radar backscatter–in situ soil moisture measurement relationship. Coupling field measurements, remote sensing, and radiative transfer modeling improves our understanding of the vegetation effect on remote sensing retrievals of soil moisture while supporting algorithm development for the SMAP mission.

This work was conducted in part by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

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