Measuring surface roughness height to parameterize radar backscatter models for retrieval of surface soil moisture

R Bryant, MS Moran, DP Thoma… - … and Remote Sensing …, 2007 - ieeexplore.ieee.org
R Bryant, MS Moran, DP Thoma, CDH Collins, S Skirvin, M Rahman, K Slocum, P Starks…
IEEE Geoscience and Remote Sensing Letters, 2007ieeexplore.ieee.org
Surface roughness is a crucial input for radar backscatter models. Roughness
measurements of root mean-squared height (h rms) of the same surface can vary depending
on the measuring instrument and how the data are processed. This letter addresses the
error in h rms associated with instrument bias and instrument deployment issues such as
number and length of measurement transects. It was found that at least 20 transect
measurements, 3 m in length, for study sites ranging from 3.5 to 1225 m 2 in size were …
Surface roughness is a crucial input for radar backscatter models. Roughness measurements of root mean-squared height (h rms ) of the same surface can vary depending on the measuring instrument and how the data are processed. This letter addresses the error in h rms associated with instrument bias and instrument deployment issues such as number and length of measurement transects. It was found that at least 20 transect measurements, 3 m in length, for study sites ranging from 3.5 to 1225 m 2 in size were necessary to get a consistent h rms measurement. Also, roughness heights of longer transect lengths were highly dependent on the method of detrending the transects. Finally, soil moisture was predicted by inverting the integral equation model using roughness heights taking into account instrument bias, number of measurements, and the detrending method. For common configurations of the Radarsat sensor and reasonable h rms values, error associated with measurement of h rms generally exceeded plusmn20% of soil-moisture prediction
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