Soil Moisture Change Monitoring from C and L-band SAR Interferometric Phase Observations

The soil moisture changes (\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}) have a significant influence on forestry, hydrology, meteorology, agriculture, and climate change. Interferometric synthetic aperture radar (InSAR), as a potential remote sensing tool for change detection, was relatively less investigated for monitoring this parameter. DInSAR phase ({\boldsymbol{\varphi }}) is sensitive to the changes in soil moisture ({{\boldsymbol{M}}_{\boldsymbol{v}}}), and thus, can be potentially used for monitoring \Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}. In this article, the relations between {\boldsymbol{\varphi }} and \Delta {{\boldsymbol{M}}_{\boldsymbol{v}}} over wheat, canola, corn, soybean, weed, peas, and bare fields were investigated using an empirical regression technique. To this end, dual-polarimetric C-band Sentinel-1A and quad-polarimetric L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) airborne datasets were employed. The regression model showed the coefficient of determination (R 2 ) of 40% to 56% and RMSE of 4.3 vol.% to 6.1 vol.% between the measured and estimated \Delta {{\boldsymbol{M}}_{\boldsymbol{v}}} for different crop types when the temporal baseline (\Delta {\boldsymbol{T}}) was very short. As expected, higher accuracies were obtained using UAVSAR given its very short \Delta {\boldsymbol{T}} and its longer wavelength with R 2 of 47% to 59% and RMSE of 4.1 vol.% to 6.7 vol.% for different crop types. However, using the Sentinel-1 data with the long \Delta {\boldsymbol{T}} and shorter wavelength (5.6 cm), the accuracies of {{\bf \Delta }}{{\boldsymbol{M}}_{\boldsymbol{v}}} estimations decreased significantly. The results of this study demonstrated that