Assessment of the SMAP Passive Soil Moisture Product

Steven K. Chan, Rajat Bindlish, Peggy E. O'Neill, Eni G Njoku, Tom Jackson, Andreas Colliander, Fan Chen, Mariko Burgin, Scott Dunbar, Jeffrey Piepmeier, Simon H. Yueh, Dara Entekhabi, Michael H Cosh, Todd Caldwell, Jeffrey Walker, Xiaoling Wu, Aaron Berg, Tracy Rowlandson, Anna Pacheco, Heather McNairnMarc Thibeault, Jose Martinez-Fernandez, Angel Gonzalez-Zamora, Mark Seyfried, David D. Bosch, Patrick J. Starks, David Goodrich, John H. Prueger, Michael Palecki, Eric J Small, Marek M Zreda, Jean-Christophe Calvet, Wade T Crow, Yann Kerr

Research output: Contribution to journalArticleResearchpeer-review

447 Citations (Scopus)


The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2-SM-P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2-SM-P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.

Original languageEnglish
Article number7478653
Pages (from-to)4994-5007
Number of pages14
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number8
Publication statusPublished - 1 Aug 2016


  • Brightness temperature
  • L-band
  • land emission
  • Level 2 Passive Soil Moisture Product (L2-SM-P)
  • Level 3 Daily Composite Version (L3-SM-P)
  • passive microwave remote sensing
  • soil moisture
  • Soil Moisture Active Passive (SMAP)
  • tau-omega(τ-ω) model
  • validation

Cite this