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Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation.

Ruzbeh Akbar1, Michael H Cosh2, Peggy E O'Neill3

  • 1Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA.

IEEE Transactions on Geoscience and Remote Sensing : a Publication of the IEEE Geoscience and Remote Sensing Society
|April 17, 2018
PubMed
Summary

This study introduces a new Active-Passive method for estimating surface soil moisture and roughness. The approach optimizes radar and radiometer data, achieving accurate soil moisture retrievals with low error for various land covers.

Keywords:
RadarRadiometerSoil MoistureSoil Moisture Active-Passive (SMAP)

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Area of Science:

  • Remote Sensing
  • Geophysics
  • Hydrology

Background:

  • Accurate surface soil moisture estimation is crucial for various applications, including agriculture and climate modeling.
  • Traditional methods often face challenges with noise and model inaccuracies.

Purpose of the Study:

  • To present a robust physics-based Active-Passive (radar-radiometer) methodology for simultaneous soil moisture and roughness estimation.
  • To develop a data-driven regularization technique to enhance retrieval accuracy.

Main Methods:

  • Joint optimization of similar resolution radar and radiometer observations.
  • Implementation of a noise-dependent regularization term to balance sensor contributions.
  • Treating surface roughness as a free parameter to account for noise and model errors.

Main Results:

  • The methodology demonstrates effective soil moisture retrieval for corn and soybean land cover types.
  • Unbiased RMSE values ranged from 0.03 to 0.18 cm3/cm3, indicating high accuracy.
  • The developed regularization term successfully improved the balance between radar and radiometer data.

Conclusions:

  • The proposed Active-Passive approach offers a robust solution for soil moisture and roughness estimation.
  • Consistent forward emission and scattering models are vital for accurate soil moisture retrieval.
  • The method's performance was validated through extensive simulations and field data analysis.