Surface Soil Moisture Retrievals Under Forest Canopy for L-Band SAR Observations Across a Wide Range of Incidence Angles by Inverting a Physical Scattering Model

Surface soil moisture retrievals were performed by inverting physical scattering models for forests over 30 degrees to 50 degrees incidence angle range and 0.05 to 0.40 m(3)/m(3) soil moisture range using L-band airborne synthetic aperture radar (SAR) data during a 28-day period. The forward models implemented single-scattering of discrete elements of trees and were validated at F2 site within 1.5 dB rmse of observation for VV-pol, which was enabled by introducing the gaps between trees. The physical forward models were inverted using the time-seriesSARdata to retrieve soilmoisture and soil surface roughness, which were validated with in situ data at four sites F1, F2, F3, and F5. Retrievals using VV input over the full dynamic ranges of wetness are accurate to 0.044 m(3)/m(3) unbiased rmse with correlations of 0.71 to 0.84, which is very encouraging for retrieval under forest canopy. The conditions of these results are the vegetation water content varied from 7.3 to 25.6 kg/m(2) and the sensitivity of VV to soil moisture changes ranged from 0.64 to 2.27 dB/(0.1 m(3)/m(3)). When both HH and VV were used as inputs to retrieval, the performance did not improve because the benefit of the multichannels was offset by the larger uncertainties in HH modeling. Due to the short duration of in situ data, the efficacy of commonly used relative change index retrieval is diminished. In comparison, the inversion of the scattering model is found to be an effective way to estimate forest soil moisture, it is capable of systematic correction of vegetation effect, and offers accurate retrieval of the dynamic ranges of soil moisture values in terms of unbiased rmse. The retrieval with the physical forward model provides a first step toward global application for the futureNISAR satellite.

Automated summary

Surface soil moisture retrieval using L-band airborne synthetic aperture radar (SAR) data with physical scattering models was accurate and showed high correlation in detecting soil moisture levels within forests with varying vegetation water content. The inversion of scattering model proved to be effective for estimating forest soil moisture, offering systematic correction of vegetation effects and precise retrieval of dynamic ranges of soil moisture values in unbiased root mean square error.