P-Band and L-Band Radiometry Retrieval of Soil Moisture and Temperature Profiles

This article explores the potential of P-band and L-band radiometry for estimating soil moisture and temperature profiles. A total of 3977 hourly in situ soil data were collected at depths (d) of 5-60 cm in Beltsville, MD, USA. Using the data, a coherent model was used to generate synthetic brightness temperatures at an incidence angle of 40 degrees for frequencies of 0.8, 0.9, 1.1, and 1.4 GHz. These synthetic brightness temperatures facilitated the estimation of soil moisture (m(v)) and temperature (T) profiles, which were modeled as quadratic functions with three coefficients. The inversion problem was formulated as a least-squares problem and optimized by the adaptive simulated annealing (ASA) algorithm. Regression analysis highlighted the sensitivity of the soil moisture and temperature function coefficients on the brightness temperature at 1.4 GHz and the differential between 1.4 and 0.8 GHz (R-2=0.62-0.97), yielding the best-fit models to describe the relationships. The application of the ASA algorithm incorporating the best-fit models to constrain the search spaces showed the RMSE of soil moisture m(v )<= 0.04 cm(3)/cm(3) and soil temperature T <= 1.35 degree celsius for depths d <= 20 cm, and mv <= 0.10 ccm(3)/cm(3) and T <= 1.60 degree celsius for d <= 60 cm. A streamlined inversion method was also investigated which used the best-fit models as the retrieval formula and solely relied on the V-pol data. The streamlined inversion method achieved comparable retrieval accuracy but reducing the runtime from 770 to 0.54 s for one inversion. This approach simplifies the data collection process by eliminating the need for H-pol data, potentially broadening its flexibility and applicability.