A Spatially Constrained Multichannel Algorithm for Inversion of a First-Order Microwave Emission Model at L-Band

Lun Gao, Morteza Sadeghi, Andrew F. Feldman, Ardeshir Ebtehaj

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9 Scopus citations


Understanding and reducing the uncertainties in the inversion of the first-order radiative transfer models at the L-band are important for the improved spaceborne retrievals of soil moisture (SM) and vegetation optical depth (VOD) over dense canopy. This article quantifies and compares the sensitivity of dual-channel inversion of the two-stream (2S) and - models and proposes a new inversion approach for simultaneous retrievals of SM, VOD, and vegetation-scattering albedo from a single satellite overpass. In particular, the inversion algorithm incorporates the information of the nearby spatial observations, assuming that the values of VOD and remain locally invariant, and constrains its solutions to high-resolution a priori physical/climatological knowledge of the retrieval variables. The results demonstrate that the uncertainty in the inversion of 2S model is slightly higher than the - model under noisy observations and remains homoscedastic for SM and , while grows heteroscedastically for higher VOD values due to the shape of the cost function. The results are validated using the SMAP data, the dense Mesonet SM network, the in situ measurements from the International SM Network (ISMN), and the derived VOD from the Moderate Resolution Imaging Spectroradiometer (MODIS)-normalized difference vegetation index (NDVI) over the state of Oklahoma in the United States. It is shown that the new approach can recover simultaneously high-resolution features of SM, VOD, and only from a single Soil Moisture Active Passive (SMAP) overpass, where the unbiased root-mean-squared error (ubRMSE) of SM and VOD is reduced by 30% and 70%, respectively, when compared with an unconstrained time-windowed inversion approach.

Original languageEnglish (US)
Article number9079480
Pages (from-to)8134-8146
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number11
StatePublished - Nov 2020

Bibliographical note

Funding Information:
Manuscript received September 12, 2019; revised January 12, 2020 and March 10, 2020; accepted April 9, 2020. Date of publication April 27, 2020; date of current version October 27, 2020. This work was supported in part by the Terrestrial Hydrology Program (THP) through Dr. J. Entin under Grant 80NSSC18K1528 and in part by the Future Investigators in NASA Earth and Space Science and Technology Program (FINESST) Through Dr. A. Leidner under Grant 80NSSC19K1333. (Corresponding author: Lun Gao.) Lun Gao, Morteza Sadeghi, and Ardeshir Ebtehaj are with Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55414 USA (e-mail: gaoxx996@umn.edu).

Publisher Copyright:
© 1980-2012 IEEE.


  • L-band radiometry
  • Soil Moisture Active Passive (SMAP)
  • soil moisture (SM)
  • vegetation optical depth (VOD)
  • vegetation-scattering albedo


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