## 5 Results and Discussion
### Vegetation Correction  
The fraction of bare soil and vegetation affected backscatter as well as the changes in the vegetation scatter contribution during the growing cycle lead to different correlations between the change of backscatter and change of soil moisture. Using the co-polarized backscatter signal as an estimator for bare soil and vegetation conditions during the growing season for agricultural areas, the consecutive backscatter ratios are adjusted through a linear regression (Section 4.1.4). In this regard, the effect of increasing vegetation scattering contribution within the total backscatter signal can be corrected. In Figure 8, the backscatter ratios from Fourier Series transformed and vegetational adapted time series of CRNP station SE_C_001 are shown. At the agricultural crop dominated SE_C_001 station, a small positive trend is present, indicating a decline in backscatter ratios caused by increasing vegetation scatter contribution. By removing this trend, the backscatter ratios related to lower backscatter value are increased, while the ratios related to higher backscatter values are decreased. By grouping the backscatter ratios into three vegetational periods of no-vegetation (January, February, October, November, and December in light grey), intermediate-vegetation (Mar, Apr, Aug, and Sep in dark grey), and full-vegetation cover (May, June, and July in black), most of the increase in backscatter ratios fall into the full-vegetation period. A similar correction can be observed within the non-vegetation period, leveling down the related backscatter ratios. Normalizing the backscatter ratios to the mean backscatter value, the ratios within the intermediate-vegetation period are not changed considerably.  
Figure 9 shows the soil moisture from Fourier Series transformed and vegetation corrected backscatter time series, compared to the in-situ measured soil moisture for the CRNP station RU_C_006. In general, an increase in estimated soil moisture can be observed within the period from February to May, while a decrease is observed between June and October. From November onward, both soil moisture estimations are aligning. This leads to a better match between the in situ and estimated soil moisture and corrects for the relative underestimation of soil moisture in the first half of the year, dominated by growing vegetation, relative to the overestimation of soil moisture in the second half of the year, characterized by vegetation maturing and drying. In this respect, the temporal course of the measured and the estimated soil moisture are in better agreement. In particular, the estimated soil moisture minimum of the vegetation-corrected time series is in August and thus agrees with the values measured at the station and not in May as in the uncorrected soil moisture estimate. For this example, the soil moisture estimation without vegetation correction achieves an R\({}^{2}\) of 0.54 with an uRMSE of 0.044 m\({}^{3/}\)m\({}^{3}\), while the vegetation corrected ones lead to an increase in R\({}^{2}\) to 0.80 with an uRMSE of 0.029 m\({}^{3/}\)m\({}^{3}\).  
Figure 8: Comparison between backscatter ratios from Fourier Series (red) and vegetation corrected backscatter time series for the CRNP station SE_C_001. The ratios for vegetation adapted time series are grouped into three vegetation periods, while the ratios from Fourier transformed time series are colored in red.