# GNSS-IR Soil Moisture Retrieval Using Multi-Satellite Data Fusion Based on Random Forest
## 5 Discussion
### Analysis of the Impact of Terrain on Soil Moisture Retrieval  
Due to the daily revisit cycle of GPS satellites and the relatively fixed trajectory of each satellite, the entire satellite network's arc segments almost completely cover all areas surrounding the receiver, adequately reflecting the impact of different terrains on the reflected signals. Existing research shows that there is a linear relationship between the phase of the reflected signal and soil moisture [7]. Therefore, a stronger correlation between phase and soil moisture is more conducive to soil moisture retrieval. To explore the impact of terrain changes on soil moisture retrieval, this paper analyzed the DEM map near the P041 site, as shown in Figure 17b. It was found that the terrain gradually rose to the southeast of the P041 site, gradually decreased to the northwest, and was relatively flat to the west and northeast. Four satellites, whose arc segments spanned rising, lowering and flat terrains, were selected to compare the impact of different terrains on soil moisture retrieval. Figure 17a displays the azimuth range maps for three types of arc segments from four satellites. Figure 17b displays the DEM map near the P041 site. In Figure 17a, the total azimuth range for the four satellites was, respectively, 36\({}^{\circ}\)-51\({}^{\circ}\), 111\({}^{\circ}\)-155\({}^{\circ}\), and 284\({}^{\circ}\)-325\({}^{\circ}\). Subsequently, the phases derived from the different arc segments of these four satellites were correlated with the soil moisture reference values. This analysis was combined with DEM to study the impact of terrain on soil moisture retrieval. Figure 18 shows the correlation between the phases from different arc segments of the four satellites, and the soil moisture reference values. Table 4 displays the R between the phases of different satellites at various azimuth angles, and the soil moisture reference values. Figure 16: A linear regression analysis of the soil moisture retrieval results from different RF models at the P041 site compared to the reference values. Red dots represent the MDI algorithm, and green triangles represent the MDA algorithm. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Station** & **Model** & **R** & **RMSE** & **MAE** \\  & & & **cm\({}^{3}\)/cm\({}^{3}\)** & **cm\({}^{3}\)/cm\({}^{3}\)** \\ \hline \multirow{2}{*}{P041} & RF MDI & 0.94 & 0.032 & 0.025 \\  & RF MDA & 0.91 & 0.042 & 0.029 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: R, RMSE, and MAE between retrieved soil moisture and reference values for both algorithms at site P041. Figure 17: (**a**) Distribution of arc segments for satellites G03, G10, G19, and G26; (**b**) the DEM near the P041 station. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**AZI** & **36\({}^{\circ}\)–51\({}^{\circ}\)** & **111\({}^{\circ}\)–155\({}^{\circ}\)** & **284\({}^{\circ}\)–325\({}^{\circ}\)** \\
**Satellite** & **R** & **R** & **R** \\ \hline G03 & 0.6 & 0.04 & 0.4 \\ G10 & 0.53 & 0.04 & 0.08 \\ G19 & 0.67 & 0.24 & 0.14 \\ G26 & 0.64 & 0.43 & 0.27 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The R between the phase of different satellites at various azimuth angles, and the soil moisture reference values. Figure 18: The correlation coefficients between the phase of different satellites at various azimuth angles and the soil moisture reference values. In this study, satellites G03, G10, G19, and G26 were selected based on the DEM at the P041 site to analyze the impact of terrain on the results of soil moisture retrieval. From Figure 18 and Table 4, it is evident that, when the satellite trajectory azimuth angles were between 36\({}^{\circ}\) and 51\({}^{\circ}\), the phases extracted from satellites G03, G10, G19, and G26 all had a high correlation with the soil moisture reference values, with an average correlation coefficient of 0.61.