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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #313553

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Scaling and calibration of a core validation site for the soil moisture active passive mission

Author
item Cosh, Michael
item BINDLISH, R. - Science Systems, Inc
item COLLIANDER, ANDREAS - Jet Propulsion Laboratory
item Coopersmith, Evan
item HORNBUCKLE, B. - Iowa State University
item Jackson, Thomas
item McKee, Lynn
item Prueger, John

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 3/1/2015
Publication Date: 5/3/2015
Citation: Cosh, M.H., Bindlish, R., Colliander, A., Coopersmith, E.J., Hornbuckle, B., Jackson, T.J., Mckee, L.G., Prueger, J.H. 2015. Scaling and calibration of a core validation site for the soil moisture active passive mission [abstract]. American Geophysical Union, Fall Meeting Supplements. Paper No. H43B-01.

Interpretive Summary:

Technical Abstract: The calibration and validation of soil moisture remote sensing products is complicated due to the logistics of installing a long term soil moisture monitoring network in an active landscape. It is more efficient to locate these stations along agricultural field boundaries, but unfortunately this often results in non-representative sites with regards to land surface or soil moisture. The representative character of this network can only be established by large scale field sampling to provide a calibration dataset. To test this method, a team of samplers were deployed twice a week for the summer of 2014 in the South Fork Experimental watershed near Iowa Falls, Iowa (USA) to collect surface soil moisture data across a variety of vegetated land cover surfaces at 44 sites. These samples were compared to the soil moisture observations from in situ sensors and scaled to grid cells of different resolutions (3, 9, 36 km) that will be used as a core validation site for the Soil Moisture Active Passive (SMAP) Mission. Arithmetic and spatially weighted averages as well as modeled estimates of each grid cell were evaluated and scaling functions were developed at different grid resolutions. The in situ network is able to accurately represent at each grid resolution with an accuracy of less than 0.03 m3/m3 with a simple linear function.