A Method Using GNSS Lh-Reflected Signals for Soil Roughness Estimation

Abstract

ABSTRACT:Global Navigation Satellite System Reflectometry (GNSS-R) is based on the concept of receiving GPS signals reflected by the ground using a passive receiver. The receiver can be on the ground or installed on a small aircraft or UAV and collects the electromagnetic field scattered from the surface of the Earth. The received signals are then analyzed to determine the characteristics of the surface. Many research has been reported showing the capability of the GNSS-R technique. However, the roughness of the surface impacts the phase and amplitude of the received signals, which is still a worthwhile study. This paper presented a method can be used by GNSS-R to estimate the surface roughness. First, the data was calculated in the specular reflection with the assumption of a flat surface with different permittivity. Since the power reflectivity can be evaluated as the ratio of left-hand (LH) reflected signal to the direct right-hand (RH) signal. Then a semi-empirical roughness model was applied to the data for testing. The results showed the method can distinguish the water and the soil surface. The sensitivity of the parameters was also analyzed. It indicates this method for soil roughness estimation can be used by GNSS-R LH reflected signals. In the next step, several experiments need to be done for improving the model and exploring the way of the estimation.

Soil Moisture Content from GNSS Reflectometry Using Dielectric Permittivity from Fresnel Reflection Coefficients

“…From Figures 7 and 8, we can observe that for a given VOD coverage, surface reflectivity and SMC estimates are not sensitive to BSR values below 0.2 m. These results imply that small variations in surface reflectivity will not influence the SMC retrieval below BSR values of~0.2 m. On the contrary, Figure 8 clearly shows that GNSS-R reflectivity appears to be more sensitive to BSR values above 0.2 m, which supports the findings of [70] for this variable. Since the maximum value of SMAP BSR for the data sets of this study is not higher than 0.18 m, we can foresee that SMAP BSR values will have a small influence on SMC retrieval, as the permittivity is directly related to the surface reflectivity.…”

“…These results imply that small variations in surface reflectivity will not influence the SMC retrieval below BSR values of ~0.2m. On the contrary, Figure 8 clearly shows that GNSS-R reflectivity appears to be more sensitive to BSR values above 0.2m, which supports the findings of [70] for this variable. Since the maximum value of SMAP BSR for the data sets of this study is not higher than 0.18m, we can foresee that SMAP BSR values made in this work for using ICESat-2 BSR values (Figure 9).…”