Inversion of Physical Models Using L-Band Airborne SAR Data for Soil Moisture Estimates at Field Scale

Abstract

L-band capability to monitor soil moisture at field scale (∼100m) is examined using ground and airborne radar data. We report the recent progress in inverting physically-based forward models for radar scattering through time-series retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for various vegetation types: pasture, corn, soybean, canola, and shrub over the entire vegetation growth cycles. Various changes to the forward and retrieval algorithm per each species are summarized. Assessed over all available fields of corn, bean, pasture, and wheat, the data-cube time-series inversion has the retrieval rmse of 0.050 to 0.075 m^3 /m^3, and the correlation of 0.5 to 0.9.

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