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- W2147820447 abstract "A time-series algorithm is proposed to retrieve bare surface soil moisture and rms height using two copolarized (HH and VV) L-band backscattering coefficients (σ <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sup> ). The retrieval approach inverts a forward model for radar scattering from an isotropic bare surface. Because real-time inversion of a complex forward model is often computationally impractical, the inversion is implemented using a precomputed lookup table representation of σ <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sup> obtained from numerical Maxwell model in 3-D simulations. The retrieval process assumes that surface roughness properties are constant during the time-series interval, so that only a single rms height estimate is produced for the entire time series. The use of this rms height estimate as a constraint simplifies the associated soil moisture retrievals at each time step. A Monte-Carlo simulation of this algorithm with 0.7 dB radar measurement error (1-sigma) shows that retrievals using six time steps outperform a “snapshot” method (which retrieves rms height and soil moisture at each time step) by a factor of about two in rms soil moisture error. A second study using measured data having 6 to 11 time steps shows an rms error of 0.044 cm <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3</sup> /cm <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3</sup> for soil moisture with a correlation coefficient of 0.89 between retrieved and in situ data. Surface rms height estimates are also found accurate to 10 to 30% of in situ measurements. It is also shown that retrieval performance is not sensitive to errors in knowledge of the surface roughness correlation length for most of the bare surface conditions examined." @default.
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- W2147820447 date "2012-05-01" @default.
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- W2147820447 title "Soil Moisture Retrieval Using Time-Series Radar Observations Over Bare Surfaces" @default.
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