## 4 Discussion  
Our results confirmed the potential of S1 for monitoring deciduous forest phenology [1], and, more importantly, we also discovered quite different performances for the coniferous forest phenology. These were possibly caused by the difference in SAR polarization backscattering behavior between different forests. For deciduous forests, the absorption and forward scattering of radar signals by foliage are more than that of backscattering [47]; therefore, the backscattering decreases significantly during the leaf-on period, which is consistent with the discovery of this research. Furthermore, it has also been discussed that the co-polarization of the C-band (VV of S1) is related to the vertical structure of forests [17; 18; 19], while cross-polarization (VH of S1) is related to forest canopy volume. It can therefore be explained that no signal variations occurred in the vertical structure, while the VH backscattering decreased rapidly because of the foliage dynamics. This difference causes seasonal variation in the ratio and differencing combinations and indicates the strong potential of S1 data to estimate the phenology of deciduous broadleaf forest. The amplitude of VH was higher than VV in 6 out of 12 coniferous sites in this study, but [PERSON] et al. [48] and [PERSON] et al. [1] pointed out that the amplitude of VV was higher than that of VH in their research (2.40 dB for VV and 2.08 dB for VH [48]). One possible explanation for this inconsistency could be the difference in the types of coniferous forests studied. Based on visual inspection of images in PhenoCam Level 2 products, the coniferous forests studied in this research are possible types with short needles, such as spruces and short-leaf pines, while the VH backscatter of coniferous forests was negatively correlated with the length of needle leaves [47], and this can be the reason for the amplitude of VH backscatter exceeding that of VV. Because of the negative correlation between the VH polarization and needle length, the polarization combinations may show different seasonal  
Figure 8: Correlations of phenological metrics in day of year between PhenoCam (x-axis) and satellite remote sensing (y-axis) in coniferous forests. (**a,e**): SOS extracted by FT; (**b,f**): EOS extracted by FT; (**c,g**): SOS extracted by DL; and (**d,h**): EOS extracted by DL. Red lines: VV-VH; and green lines: NDVI. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Forest Type**} & \multirow{2}{*}{**Index**} & \multicolumn{2}{c}{**SOS**} & \multicolumn{2}{c}{**EOS**} \\ \cline{3-6}  & & **FT** & **DL** & **FT** & **DL** \\ \hline \multirow{2}{*}{DB} & VH/VV & 0.30 & 0.72 & 0.01 & 0.00 \\  & VV-VH & 0.61 & 0.50 & 0.00 & 0.10 \\ \hline EN & VV-VH & 0.10 * & 0.35 & 0.01 & 0.01 \\ \hline \hline \end{tabular}  
* Negative correlation.  
\end{table} 
Table 3: Correlation between Sentinel-1 and Sentinel-2 NDVI extracted phenological metrics (shown by R\({}^{2}\) values). patterns among the forest types and may not show obvious seasonal variation when the amplitude of VH is close to that of VV, and this may be the reason for the 6 sites that did not show significant variations in VV-VH. Therefore, further research is required on the potential of S1 data for monitoring coniferous forest phenology. Previous studies have shown the stability of the NDVI for phenological studies [49]. A recent study also indicated that the phenological estimation results for comprehensive vegetation types based on S1 C-band backscatter are less accurate than those of S2 NDVI [20]. This study partly concurs with their conclusion about coniferous forest phenological estimation. The unexplained negative SOS correlation between S1 and PhenoCam and the instability of the VV-VH profile indicates that the tested algorithm in this research may not be suitable for the extraction of coniferous forest phenology. Therefore, S2 data are more suitable for large-scale phenological observations of coniferous forests.