## 3 Results
### Relationships between Optical Spectral Vegetation Indices and LAI, Biomass
The results demonstrated that the COSVI-RPPs were highly significantly related to LAI and biomass. They could be used to estimate LAI and biomass in winter wheat. The results show that the MTVI2 \(\times\) RVI regression equation for estimating LAI and the EVI \(\times\) RVI regression equation for estimating biomass were fitted to power regression equations (Table 8). To validate the estimation accuracy of the regression equations for LAI and biomass, the predicted values and the measured values were compared based on the RMSE and nRMSE. The results showed that the RMSE and nRMSE values ranged from 0.65 to 0.80 and 19.52% to 24.02% for LAI, respectively; the RMSE and nRMSE values ranged from 146.33 g/m\({}^{2}\) to 201.47 g/m\({}^{2}\) and 20.21% to 27.84% for biomass, respectively (Table 8). There was good consistency between the predicted values and the measured values. The RMSE and nRMSE values for the regressions between the MTVI2 \(\times\) RVI and LAI were 0.65 and 19.52%, and those for the regressions between the EVI \(\times\) RVI and biomass were 146.33 g/m\({}^{2}\) and 20.21%, respectively. The results showed that MTVI2 \(\times\) RVI and EVI \(\times\) RVI were better than RVI, MTVI2 and EVI, RVI alone for estimation of LAI and biomass in winter wheat, respectively (Figure 3). The results suggested that the MTVI2 \(\times\) RVI and EVI \(\times\) RVI could be used to improve the estimation accuracy of LAI and biomass, respectively. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Vegetation Indices**} & \multicolumn{4}{c}{**LAI**} & \multicolumn{4}{c}{**Biomass**} \\ \cline{2-9}  & \multicolumn{2}{c}{**Regression Equations**} & \multirow{2}{*}{**R2**} & \multirow{2}{*}{**RMSE**} & \multicolumn{2}{c}{**nRMSE**} & \multicolumn{2}{c}{**Regression Equations**} & \multirow{2}{*}{**R2**} & \multirow{2}{*}{**nRMSE**} \\  & \multicolumn{2}{c}{**Equations**} & & & & **(\%)** & & **Equations** & & **(g/m\({}^{2}\))** & **(\%)** \\ \hline RVI1 \(\times\) RVI & y = 2.1548x\({}^{0.6299}\) & 0.56** & 0.70 & 20.72 & y = 231.5x\({}^{1.2164}\) & 0.72** & 182.42 & 25.20 \\ NDVI \(\times\) RVI & y = 1.4685x\({}^{2.4896x}\) & 0.58** & 0.75 & 22.52 & y = 321.6x\({}^{1.4544}\) & 0.77** & 151.27 & 20.90 \\ SAVI \(\times\) RVI & y = 8.0998x\({}^{0.6071}\) & 0.60** & 0.68 & 20.46 & y = 3186.5x\({}^{1.2003}\) & 0.76** & 168.31 & 23.26 \\ OSAVI \(\times\) RVI & y = 8.1476x\({}^{0.6233}\) & 0.61** & 0.74 & 22.22 & y = 3163.9x\({}^{1.2232}\) & 0.77** & 155.65 & 20.51 \\ EVI \(\times\) RVI & y = 6.9326x\({}^{5.9973}\) & 0.64** & 0.67 & 20.12 & y = 2394.4x\({}^{1.1858}\) & 0.80** & 146.33 & 20.21 \\ MTVI2 \(\times\) RVI & y = 6.2472x\({}^{0.3814}\) & 0.68** & 0.65 & 19.52 & y = 1816.2x\({}^{0.7426}\) & 0.75** & 170.58 & 23.57 \\ RVI1 \(\times\) DERD & y = 2.037x\({}^{0.2306x}\) & 0.52** & 0.75 & 22.52 & y = 190.5e\({}^{0.4714x}\) & 0.71** & 201.47 & 27.84 \\ NDVI \(\times\) DERD & y = 1.8016x\({}^{1.992\chi}\) & 0.56** & 0.80 & 24.02 & y = 151.66x\({}^{1.117\chi}\) & 0.79** & 159.52 & 22.04 \\ SAVI \(\times\) DERD & y = 1.9088x\({}^{2.2375\chi}\) & 0.58** & 0.70 & 20.72 & y = 174.92e\({}^{0.4701x}\) & 0.76** & 161.21 & 22.28 \\ OSAVI \(\times\) DERD & y = 1.896x\({}^{2.210\chi}\) & 0.60** & 0.72 & 21.62 & y = 171.94e\({}^{4.404\chi}\) & 0.79** & 148.65 & 20.54 \\ EVI \(\times\) DERD & y = 1.848e\({}^{1.834\chi}\) & 0.62** & 0.78 & 23.42 & y = 171.25e\({}^{3.5926x}\) & 0.78** & 156.67 & 21.65 \\ MTVI2 \(\times\) DERD & y = 6.1902x + 2.0154 & 0.67** & 0.68 & 20.46 & y = 1781.2x + 216.35 & 0.72** & 178.43 & 24.65 \\ \hline \hline \end{tabular} Note: **Model significant at the 0.01 probability level (\(\rho<0.01\)).  
\end{table} 
Table 8: The regression relationships between combined optical spectral vegetation indices and radar polarimetric parameters and winter wheat LAI, biomass (n = 80). Figure 3: Comparison of MTVI2 (**a**) RVI (**b**) and MTVI2\(\times\)RVI (**c**) for estimation of LAI and EVI (**d**), RVI (**e**) and EVI\(\times\)RVI (**f**) for estimation of biomass, respectively.