Regularized Dual-Channel Algorithm for the Retrieval of Soil Moisture and Vegetation Optical Depth from SMAP Measurements

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  • Mario J. Chaubell
  • Simon H. Yueh
  • Scott Dunbar
  • Andreas Colliander
  • Dara Entekhabi
  • Steven K. Chan
  • Fan Chen
  • Xiaolan Xu
  • Rajat Bindlish
  • Peggy E. Oneill
  • Jun Asanuma
  • Aaron Berg
  • David D. Bosch
  • Todd Caldwell
  • Michael Cosh
  • Chandra D. Holifield Collins
  • Jose Martinez-Fernandez
  • Mark Seyfried
  • Patrick Starks
  • Bob Su
  • Marc Thibeault
  • Jeffrey Walker

In August 2020, SMAP released a new version of its soil moisture (SM) and vegetation optical depth (VOD) retrieval products. In this work, we review the methodology followed by the SMAP regularized dual-channel (DCA) retrieval algorithm. We show that the new implementation generated SM retrievals that not only satisfy the SMAP accuracy requirements but also show a performance comparable to the single-channel algorithm that uses the V polarized brightness temperature (SCA-V). Due to a lack of in situ measurements we cannot evaluate the accuracy of the VOD. In this work, we show analyses with the intention of providing an understanding of the VOD product. We compare the VOD results with those from SMOS. We also study the relation of the SMAP VOD with two vegetation parameters: tree height and biomass.

TidsskriftIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Sider (fra-til)102-114
Antal sider13
StatusUdgivet - 2022

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