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

Abstract

AbstractThe soil moisture changes (M_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 () is sensitive to the changes in soil moisture (M_v) and, thus, can be potentially used for monitoring M_v. In this study, the relations between and M_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 (R2) of 40% to 56% and RMSE of 4.3 vol.% to 6.1 vol.% between the measured and estimated M_v for different crop types when the temporal baseline (T) was very short. As expected, higher accuracies were obtained using UAVSAR given its very short 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 T and shorter wavelength (5.6 cm), the accuracies of M_v estimations decreased significantly. The results of this study demonstrated that using the information from Sentinel-1 data is a promising approach for monitoring M_v 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.