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Wheat canopy structure and surface roughness effects on multiangle observations at L-Band

Abstract : The multiangle observation capability of the Soil Moisture and Ocean Salinity mission is expected to significantly improve the inversion of soil microwave emissions for soil moisture, by enabling the simultaneous retrieval of the vegetation optical depth and other surface parameters. Consequently, this paper investigates the relationship between soil moisture and brightness temperature at multiple incidence angles using airborne L-band data from the National Airborne Field Experiment in Australia in 2005. A forward radio brightness model was used to predict the passive microwave response at a range of incidence angles, given the following inputs: 1) ground-measured soil and vegetation properties and 2) default model parameters for vegetation and roughness characterization. Simulations weremade across various dates and locations with wheat cover and evaluated against the available airborne observations. The comparison showed a significant underestimation of the measured brightness temperatures by the model. This discrepancy subsequently led to soil moisture retrieval errors of up to 0.3 m3/m3. Further analysis found the following: 1) The roughness value HR was too low, which was then adjusted as a function of the soil moisture, and 2) the vegetation structure parameters tth and ttv required optimization, yielding new values of tth = 0.2 and ttv = 1.4 from calibration to a single flight. Testing the optimized parameterization for different moisture conditions and locations found that the rootmean- square simulation error between the forward model predictions and the airborne observations was improved from 31.3 K (26.5 K) to 2.3 K (5.3 K) for wet (dry) soil moisture condition.
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Submitted on : Thursday, May 24, 2012 - 4:18:36 PM
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S. Peischl, J.P. Walker, D. Ryu, Yann H. Kerr, R. Panciera, et al.. Wheat canopy structure and surface roughness effects on multiangle observations at L-Band. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50 (5), pp.1498-1506. ⟨10.1109/TGRS.2011.2174644⟩. ⟨ird-00701154⟩



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