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

Abstract

Surface soil moisture retrievals were performed by inverting physical scattering models for forests over <inline-formula><tex-math notation= LaTeX >$\\text{30}^\\circ$</tex-math></inline-formula> to <inline-formula><tex-math notation= LaTeX >$\\text{50}^\\circ$</tex-math></inline-formula> incidence angle range and 0.05 to 0.40\xa0m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula>/m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula> soil moisture range using <inline-formula><tex-math notation= LaTeX >$L$</tex-math></inline-formula>-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 <inline-formula><tex-math notation= LaTeX >$F$</tex-math></inline-formula>2 site within 1.5\xa0dB rmse of observation for VV-pol, which was enabled by introducing the gaps between trees. The physical forward models were inverted using the time-series SAR data to retrieve soil moisture and soil surface roughness, which were validated with <italic>in situ</italic> data at four sites <inline-formula><tex-math notation= LaTeX >$F$</tex-math></inline-formula>1, <inline-formula><tex-math notation= LaTeX >$F$</tex-math></inline-formula>2, <inline-formula><tex-math notation= LaTeX >$F$</tex-math></inline-formula>3, and <inline-formula><tex-math notation= LaTeX >$F$</tex-math></inline-formula>5. Retrievals using VV input over the full dynamic ranges of wetness are accurate to 0.044\xa0m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula>/m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula> 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\xa0kg/m<inline-formula><tex-math notation= LaTeX >$^2$</tex-math></inline-formula> and the sensitivity of VV to soil moisture changes ranged from 0.64 to 2.27\xa0dB/(0.1\xa0m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula>/m<inline-formula><tex-math notation= LaTeX >$^3$</tex-math></inline-formula>). 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 <italic>in situ</italic> 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 future NISAR satellite.