## 4 Results
### Daily Time Variation of Dielectric Constant  
A typical feature of the derived dielectric constant using CYGNSS data along with daytime interval is investigated at distinct locations that were selected from the list of core validation sites for SMAP soil moisture. Figure 5 shows the time series comparisons and correlation scatter plots between CYGNSS and SMAP data when specular points occur at Yanco, Australia. The methods for drawing a 2D global image with EASE grid are applied to CYGNSS data, as explained in Section 3. Subsequently, the search process is applied to find the location of the pixel containing the geographical position of Yanco. Because the global soil moisture map from SMAP has been built on an EASE grid, the location of the pixel in CYGNSS 2D global map is identical to the SMAP global image. Analysis data observed on the desired specular point are extracted from the specific pixel in the 2D global map using CYGNSS and SMAP data. By repeating the described process to the entire satellite dataset, a daily time series figure can be obtained, as seen in Figures 5-7. Approximately three years of CYGNSS and SMAP data were examined, spanning from March 2017 to April 2020. In Figure 5a,b, blue dots represent the dielectric constant and reflectivity from CYGNSS satellites and red dots indicate the soil moisture and dielectric constant that originated from the SMAP satellite. Figure 5a demonstrates the results of the dielectric constant derived from Equations (2) through (6) from CYGNSS data as compared with the dielectric constant calculated from the semi-empirical model that was applied to SMAP data. Figure 5b presents the comparison plot between reflectivity from Equation (2) with CYGNSS data and SMAP soil moisture data. Figure 5: (**a**) Time series plot of dielectric constant at measurement site Yanco, Australia using CYGNSS and SMAP; (**b**) time series plot of reflectivity and soil moisture at same location with reflectivity from CYGNSS and soil moisture from SMAP using (**a**); (**c**) scattering plot of CYGNSS-derived reflectivity and SMAP using (**a**); and, (**d**) scattering plot of CYGNSS-derived dielectric constant and SMAP dielectric constant using results of (**b**). The CYGNSS-based estimation has the tendency of clearly following a SMAP-based dielectric constant and soil moisture, as seen in both Figure 5a,b. The computed dielectric constant and reflectivity results are also within the expected values: the dielectric constant is larger than 1 and the reflectivity is between 0 and 1, with no shifting of the data axis or normalization method applied to the CYGNSS data. These results are encouraging, as, at 6.6 times less the cost, the CYGNSS mission can provide soil moisture estimates that are comparable to those of the SMAP mission. Additionally, these correlations support quantitative values of soil moisture from CYGNSS satellites, because the dielectric constant, which plays an important role to calculate soil moisture, exists in a reasonable range when the GNSS-R data are applied. The difference of peak values between CYGNSS and SMAP can be observed in both Figure 5a,b. The peak values of dielectric constant presented in Figure 5a are shown to be distinct, and they are considered to have relations to weather condition, season, surface roughness, and, mostly, the calibration process. A more detailed comparison between the dielectric constant from CYGNSS and SMAP with the GNSS-R specified soil moisture model is an important part of future research. Figure 6: (**a**) Time series plot of dielectric constant at measurement site Texas Soil Moisture Network, U.S using CYGNSS and SMAP; (**b**) time series plot of reflectivity and soil moisture at same location with reflectivity from CYGNSS and soil moisture from SMAP using (**a**); (**c**) scattering plot of CYGNSS-derived reflectivity and SMAP using (**a**); and, (**d**) the scattering plot of CYGNSS-derived dielectric constant and SMAP dielectric constant using results of (**b**).