Estimating soil moisture using the Danish polarimetric SAR

The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms height from coand cross-polarized ratio, have been examined, but the results are less satisfactory. As soil moisture response to backscattering coefficient σ^o is mainly coupled to surface roughness effect for bare fields, a bilinear model coupling volumetric soil moisture m_v and surface rms height σ to σ^o has been applied. This model has previously been investigated with MAESTRO-1 data at Flevoland in The Netherlands. The results from the present analysis showed that correlation coefficients between the model and the observed σ^o are 0.86-0.81 for hh, vv and hv (vh) polarizations. For estimation of surface parameters with the bilinear model, the correlation coefficient between the estimated and measured soil moisture, as well as rms height, is about 0.77. To improve the result, the local incidence angles need to be taken into account