Global Sensitivity Analysis of the L-MEB Model for Retrieving Soil Moisture

Zengyan Wang, Tao Che, Yuei An Liou

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


A global sensitivity analysis utilizing the extended Fourier amplitude sensitivity test is used to determine the parameter sensitivity of the L-band microwave emission of the biosphere (L-MEB) model. The results are analyzed from two perspectives of calibration and inversion. First, the parameters of surface soil moisture, soil roughness factor, vegetation optical depth at nadir, and effective land surface temperature are the four most sensitive parameters in the L-MEB model, demonstrating their possibility to be retrieved in the multiparameter retrieval approaches. Then, the high total sensitivity index (TSI) values of surface soil temperature in the analyses emphasize the importance of high-precision land surface temperature data in the surface soil moisture retrievals, especially for rougher or more vegetated surface conditions. Finally, our analysis indicates that TSI values are high for the soil surface roughness and vegetation optical depth model parameters but low for the vegetation structure, single scattering albedo, and soil roughness coefficient model parameters at incidence angles near nadir. This suggests that calibration experiments performed at small incidence angles may be appropriate for some but not all of the model parameters, which characterize the effect of soil surface roughness and vegetation on the terrestrial brightness temperature. Consequently, new calibration procedures that account for the different relative sensitivities of these model parameters at larger incidence angles may need to be developed in the future.

Original languageEnglish
Article number7389400
Pages (from-to)2949-2962
Number of pages14
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number5
StatePublished - May 2016


  • Global sensitivity analysis (SA)
  • L-band microwave emission of the biosphere (L-MEB)
  • passive microwave remote sensing
  • soil moisture


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