<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper reports on the retrieval of soil moisture from dual-polarized L-band (1.6 GHz) radar observations acquired at view angles of 15<formula formulatype="inline"><tex>∘</tex></formula>, 35 <formula formulatype="inline"><tex>∘</tex></formula>, and 55<formula formulatype="inline"><tex>∘ </tex></formula>, which were collected during a field campaign covering a corn growth cycle in 2002. The applied soil moisture retrieval algorithm includes a surface roughness and vegetation correction and could potentially be implemented as an operational global soil moisture retrieval algorithm. The surface roughness parameterization is obtained through inversion of the Integral Equation Method (IEM) from dual-polarized (HH and VV) radar observations acquired under nearly bare soil conditions. The vegetation correction is based on the relationship found between the ratio of modeled bare soil scattering contribution and observed backscatter coefficient <formula formulatype="inline"><tex>(σˢᵒⁱˡ/σᵒᵇˢ)</tex></formula> and vegetation water content <formula formulatype="inline"><tex>$(W)$</tex></formula>. Validation of the retrieval algorithm against ground measurements shows that the top 5-cm soil moisture can be estimated with an accuracy between 0.033 and 0.064 <formula formulatype="inline"><tex>cm³⁻³</tex></formula>, depending on the view angle and polarization. </para>
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Joseph et al. (2008) studied this question.
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