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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 #362513

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16)

Author
item COLLIANDER, A - Jet Propulsion Laboratory
item Cosh, Michael
item MISRA, S - Jet Propulsion Laboratory
item Jackson, Thomas
item Crow, Wade
item POWERS, J. - Agriculture And Agri-Food Canada
item MCCAIN, H. - Agriculture And Agri-Food Canada
item BULLOCK, PAUL - University Of Manitoba
item BERG, A. - University Of Guelph
item MAGAGI, R. - Universite De Sherbrooke
item BINDLISH, R. - Goddard Space Flight Center
item WILLIAMSON, R. - Jet Propulsion Laboratory
item RAMOS, I. - Jet Propulsion Laboratory
item LATHAM, B. - Jet Propulsion Laboratory
item ONEIL, P.E. - Goddard Space Flight Center
item YUEH, S. - Jet Propulsion Laboratory

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/6/2019
Publication Date: 4/15/2019
Citation: Colliander, A., Cosh, M.H., Misra, S., Jackson, T.J., Crow, W.T., Powers, J., Mccain, H., Bullock, P., Berg, A., Magagi, R., Bindlish, R., Williamson, R., Ramos, I., Latham, B., Oneil, P., Yueh, S. 2019. Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16). Remote Sensing of Environment. 227:137-150. https://doi.org/10.1016/j.rse.2019.04.004.
DOI: https://doi.org/10.1016/j.rse.2019.04.004

Interpretive Summary: The Soil Moisture Active Passive Mission’s Validation Experiment in 2016 was conducted to study how the microwave satellite is able to estimate soil moisture over agricultural domains. Two areas were selected for inclusion in the study, namely the Carman domain near Winnipeg, Canada, and the South Fork domain near Ames, Iowa. Aircraft flights were coordinated between study regions between May and July of 2016 to capture a dynamic range of vegetation conditions. Both locations have previously demonstrated poor performance for soil moisture estimation from the satellite. Improved characterization of the ground measurements and the vegetation status allowed for improvement in the performance of the mission. This is useful for the application of soil moisture remote sensing to agricultural applications throughout the U.S. and world.

Technical Abstract: The NASA’s SMAP (Soil Moisture Active Passive) mission conducted a field experiment with its partners over two agricultural domains in Iowa and Manitoba in the summer of 2016 to address concerns observed in the SMAP soil moisture (SM) retrieval over agricultural areas. The experiment featured airborne PALS (Passive Active L-band System) flights over each domain with intensive ground measurements and dense networks of SM monitoring stations. With two intensive observation periods separated in time, the flights captured both early season low vegetation and later season high vegetation conditions. The comparison of the PALS brightness temperature (TB) measurements to the SMAP TB observed over the sites resulted in root mean square difference (RMSD) of 2.8 K and 4.0 K for vertical and horizontal polarizations, respectively. The subsequent SM analysis adjusted the PALS TB with the SMAP TB to allow equitable comparisons between the SM retrievals from the two instruments. The PALS SM retrieval used the SM sampled by the ground teams during the overpass days for its tuning, and a high-resolution vegetation water content product calibrated using the vegetation samples collected during the experiment. The tuning process was not able to find a satisfactory result with a constant set of parameters in the single channel algorithm for the two intensive observation periods of the experiment. This result indicated that the rapid change in the vegetation structure during the growth stages and likely variation in the surface roughness conditions were not compatible with rigid parameterization over the entire period. However, using seasonally variable parameterization we found that it was possible to retrieve soil moisture with satisfactory accuracy. Comparative analysis with the SMAP SM included aggregation of the PALS SM to the SMAP pixel-scale. The RMSD between the PALS SM and the aggregated manual field samples was less than 0.04 m3/m3 with Pearson correlation more than 0.85 for both sites. The comparison between different in situ sources indicated that the permanent network was not the source of the large biases observed for SMAP over the sites reported in earlier studies. Therefore, the results suggested the rapidly changing vegetation and surface conditions are not captured by the SMAP algorithm during the growing season caused the SMAP retrieval errors. In addition, the vegetation water content climatology used by the SMAP product showed significant deviations from the calibrated vegetation water content obtained during the experiment compounds the problem.