Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

Mohsen Ebrahimi-Khusfi, Seyed Kazem Alavipanah, Saeid Hamzeh, Farshad Amiraslani, Najmeh Neysani Samany, Jean Pierre Wigneron

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (H R ) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m 3 /m 3 to 0.06 m 3 /m 3 . Second, using the algorithm selected in a first step and defined above, the ω and H R parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and H R were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and H R were found for the different land cover classes. The obtained results indicated that the impact of the VOD parameter on SM retrievals is more considerable than the effects of H R and ω. Overall, the inclusion of the VOD parameter in the SMAP SM retrieval algorithm was found to be a very interesting approach and showed the large potential benefit of the synergy between SMAP and SMOS.

Original languageEnglish
Pages (from-to)148-160
Number of pages13
JournalInternational Journal of Applied Earth Observation and Geoinformation
Early online date12 Feb 2018
Publication statusPublished (in print/issue) - 1 May 2018

Bibliographical note

Funding Information:
Many thanks go to A. Al-Yaari and R. Fernandez-Moran for their helpful comments. The authors would like to acknowledge the Jet Propulsion Laboratory and NASA Reverb exploring tools; the Centre National d’Etudes Spatiales (CNES), the Centre d’Etudes Spatiales de la BIOsphère (CESBIO) and the French National Institute for Agricultural Research (INRA); and the International Soil Moisture Network (ISMN) for making respectively the SMAP, SMOS-IC and in situ SM measurements data freely available. The authors actually thank Iranian National Science Foundation for their supports in this research.

Publisher Copyright:
© 2017 Elsevier B.V.

Copyright 2019 Elsevier B.V., All rights reserved.


  • Calibration
  • SMAP
  • Soil roughness parameter (H )
  • Synergy
  • Vegetation optical depth (VOD)
  • Vegetation scattering albedo (ω)


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