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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 #340301

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

Location: Hydrology and Remote Sensing Laboratory

Title: Development and assessment of the SMAP enhanced passive soil moisture product

Author
item CHAN, S. - Jet Propulsion Laboratory
item BINDLISH, R. - Goddard Space Flight Center
item O'NEILL, P.E. - Goddard Space Flight Center
item Jackson, Thomas
item NJOKU, E. - Jet Propulsion Laboratory
item DUNBAR, R.S. - Jet Propulsion Laboratory
item CHAUBELL, J. - Jet Propulsion Laboratory
item PEIPMEIER, J. - Goddard Space Flight Center
item YUEH, S. - Jet Propulsion Laboratory
item ENTEKHABI, D. - Collaborator
item COLLIANDER, A - Jet Propulsion Laboratory
item CHEN, F. - Collaborator
item Cosh, Michael
item CALDWELL, T. - University Of Texas
item WALKER, J. - Monash University
item BERG, A. - University Of Guelph
item MCNAIRN, H. - Agriculture And Agri-Food Canada
item THIBEAULT, M - Collaborator
item MARTINEZ-FERNANDEZ, J. - University Of Salamanca
item UDALL, F. - Collaborator
item Seyfried, Mark
item Bosch, David - Dave
item Starks, Patrick - Pat
item Holifield Collins, Chandra
item Prueger, John
item Crow, Wade

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/2017
Publication Date: 1/1/2018
Citation: Chan, S., Bindlish, R., O'Neill, P., Jackson, T.J., Njoku, E., Dunbar, R., Chaubell, J., Peipmeier, J., Yueh, S., Entekhabi, D., Colliander, A., Chen, F., Cosh, M.H., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault, M., Martinez-Fernandez, J., Udall, F., Seyfried, M.S., Bosch, D.D., Starks, P.J., Holifield Collins, C.D., Prueger, J.H., Crow, W.T. 2018. Development and assessment of the SMAP enhanced passive soil moisture product. Remote Sensing of Environment. 204:931-941. https://doi.org/10.1016/j.rse.2017.08.025.
DOI: https://doi.org/10.1016/j.rse.2017.08.025

Interpretive Summary: A new high spatial resolution soil moisture product was developed and validated using passive microwave radiometer data collected by the Soil Moisture Active Passive (SMAP) satellite. The new enhanced product has four times better resolution than the standard radiometer product. This was achieved by exploiting the oversampling of the instrument in an optimal interpolation technique. Results of validation tests using ground-based observation proved that the approach was accurate and reliable. This new product will support a wider range of hydrologic and agricultural applications thus providing greater societal benefits.

Technical Abstract: Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones. Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAP/Sentinel-1 Active-Passive Soil Moisture Product in April 2017. This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correction/calibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 – October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m3/m3 unbiased root-mean-square error (ubRMSE). This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.