A statistical model for estimating microwave thermal sampling depth of bare soil

Abstract

One of the greatest advantages of microwave remote sensing over other remote sensing techniques is penetrability.Quantitatively estimating the sensing depth of passive microwave remote sensing is meaningful for simulation of satellite signals and validation of land surface parameters to estimate the sensing depth of passive microwave remote sensing. In this paper, a simple statistical model for estimating the thermal sampling depth in microwave frequencies of soil was developed and validated.Thermal Sampling Depth(TSD) was introduced to describe the source of the main signals of passive microwave remote sensing. To develop a simple statistical model for estimating the TSD of soil, a theoretical model was introduced to describe the emission characteristics of a three-layer case, which incorporates all multiple reflections at the two boundaries. Based on radiative transfer theory, the total emission of the three layers was calculated. Sensitivity analysis was then performed to demonstrate the effects of the soil properties and frequency on the TSD based on a simulation database covering a wide range of soil characteristics and frequencies. Based on the sensitivity analysis results, a statistical model for estimating TSD was developed. This model can estimate the TSD using four common and easily acquired parameters: soil moisture, temperature, frequency, and soil specific surface area. For validation, a controlled field experiment using a Truckmounted Multi-frequency Microwave Radiometer(TMMR) was designed and performed.The total Root Mean Square Error(RMSE) between the TSD measured in field experiment and estimated using the statistical model was approximately 0.5 cm for the TRMM’s four frequencies.The results indicated that the developed statistical model offers a relatively accurate and simple way to estimate the TSD.