The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch Calibration and Validation of the SMAP Soil Moisture Algorithms.
McNairn, H., Jackson, T.J., Wiseman, G., Bélair, S., Berg, A.A., Bullock, P.R., Colliander, A., Cosh, M.H., Kim, S.-B., Magagi, R., Moghaddam, M., Njoku, E., Adams, J.R., Homayouni, S., Ojo, E., Rowlandson, T., Shang, J., Goïta, K., and Hosseini, M. (2015). "The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch Calibration and Validation of the SMAP Soil Moisture Algorithms.", IEEE Transactions on Geoscience and Remote Sensing, 53(5: Article number 6955796), pp. 2784-2801. doi : 10.1109/TGRS.2014.2364913 Access to full text
The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite is scheduled for launch in January 2015. In order to develop robust soil moisture retrieval algorithms that fully exploit the unique capabilities of SMAP, algorithm developers had identified a need for long-duration combined active and passive L-band microwave observations. In response to this need, a joint Canada-U.S. field experiment (SMAPVEX12) was conducted in Manitoba (Canada) over a six-week period in 2012. Several times per week, NASA flew two aircraft carrying instruments that could simulate the observations the SMAP satellite would provide. Ground crews collected soil moisture data, crop measurements, and biomass samples in support of this campaign. The objective of SMAPVEX12 was to support the development, enhancement, and testing of SMAP soil moisture retrieval algorithms. This paper details the airborne and field data collection as well as data calibration and analysis. Early results from the SMAP active radar retrieval methods are presented and demonstrate that relative and absolute soil moisture can be delivered by this approach. Passive active L-band sensor (PALS) antenna temperatures and reflectivity, as well as backscatter, closely follow dry down and wetting events observed during SMAPVEX12. The SMAPVEX12 experiment was highly successful in achieving its objectives and provides a unique and valuable data set that will advance algorithm development.
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