Abstract
An outdoor test beds with different soil surface roughness and soil moisture contents were prepared beside the Department of Physics, Indian Institute of Technology (BHU), Varanasi, India. In the present experiment, the bistatic scatterometer measurements were carried out for bare soil surface in the incident angle range of 20° to 70° for HH- and VV-polarisation at X-band. The bistatic scattering coefficient was found to increase with the soil moisture content and decrease with increase in soil surface roughness. The dynamic range of bistatic scattering coefficient was found more at VV-polarisation than HH-polarisation. The linear regression analysis was performed between bistatic scattering coefficients and soil moisture content at different soil surface roughness conditions for selecting the suitable incidence angle to generate the datasets for the calibration and validation of the artificial neural network model. The bistatic scattering coefficients at lower incidence angles were found more suitable to generate the datasets for the calibration and validation of ANN models. The observed values of soil moisture, RMS height and correlation length were found close with the values retrieved by ANN for both HH- and VV-polarisations. The retrieval of soil surface parameters by scatterometer data using ANN model was found more accurate at VV-polarisation than HH-polarisation.
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