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This paper investigates the feasibility of using an airborne synthetic aperture radar (SAR) to validate spaceborne SAR data. This is directed at soil moisture sensing and the recently launched soil moisture active passive (SMAP) satellite. The value of this approach is related to the fact that vicarious targets such as rain forests and oceans calibrate only the extrema of backscattering coefficients (σ0) and that the relationship between soil moisture and σ0 is nonlinear. Furthermore, corner reflectors are difficult to deploy to calibrate medium resolution (1–3 km) space- borne sensors such as the one onboard SMAP. A challenge with the approach is the varying incidence angle (θ(inc)) of the airborne sensor versus the constant value used by SMAP. The impact of this on the inter-comparison of airborne and SMAP data is analyzed through simulation and aircraft data analysis. In the absence of the SMAP SAR data, the airborne SAR and scatterometer σ0 from the recent field campaign provided the imaging geometry similar to the spaceborne case. The effect of θinc on the intercomparison using these two airborne data sets was found to be small if the landcover within the footprint is homogeneous and if σ0 (natural unit) changes very little or approximately linearly with θinc . Over heterogeneous pixels consisting of pasture, grass, forest, and growing corn, the simulation shows that the mean and standard deviation of the difference in σ0 between the SAR and scatterometer data are smaller than 0.4 and 0.3 dB, respectively. The test results with the airborne data are generally consistent with the simulation results: the mean and standard deviation of the difference are smaller than 0.9 dB for HH, VV, and HV. These magnitudes are comparable with those of the major sources of the difference: the relative calibration errors of the airborne instruments (
