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

Abstract

The soil moisture changes (Δ Mv) 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 (varphi) is sensitive to the changes in soil moisture (Mv), and thus, can be potentially used for monitoring ΔMv. In this article, the relations between varphi and Δ Mv 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 (R2) of 40% to 56% and RMSE of 4.3 vol.% to 6.1 vol.% between the measured and estimated Δ Mv for different crop types when the temporal baseline (Δ T) was very short. As expected, higher accuracies were obtained using UAVSAR given its very short Δ T and its longer wavelength with R2 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 Δ T and shorter wavelength (5.6 cm), the accuracies of Δ Mv estimations decreased significantly. The results of this study demonstrated that using the varphi information from Sentinel-1 data is a promising approach for monitoring Δ Mv at an early growing season or before the crop starts growing, but using L-band SAR data and lower temporal baselines are recommended once the biomass increases.