## 4 Results  
### Jilin-1 GP01/02 PMS Angle Effect Correction Validation  
The coefficient \(C_{\lambda}\) was employed to assess the efficacy of the angle effect correction across five distinct methodologies for the green, red, and near-infrared bands of the Jilin-1 GP01/02 PMS. Table 9 presents the mean and standard deviation values of \(C_{\lambda}\) for these five correction methods. Analysis of the data reveals that the average \(C_{\lambda}\) values obtained through the VJB method are consistently lower than those of the other four approaches, particularly when \(\theta_{s}>40^{\circ}\). Under such conditions, the maximum discrepancy in \(C_{\lambda}\) values between the VJB method and the other algorithms can extend to \(-0.13\), with the standard deviation being markedly higher--by several folds or even tens of folds--compared to the other four methods. This observation suggests a potential overcorrection issue associated with the VJB method. Excluding the Fixed-Landsat method, wherein the mean \(C_{\lambda}\) values for the red band surpass 1, the remaining methods all yield values that are less than 1. This contrast implies that the fixed parameters optimized for the Landsat red band are not directly transferable for correcting the red band of the Jilin-1 GP01/02 PMS. Consequently, subsequent analyses will be restricted to the MODIS-based, AFX, and Fixed-Jilin-1 methods. As \(\theta_{s}\) and \(\theta_{v}\) increase for these three methods, there is a corresponding decrease in the mean \(C_{\lambda}\) value and an increase in the standard deviation. Notably, for the MODIS-based method, the mean \(C_{\lambda}\) value across the green, red, and NIR bands drops by more than 5.0%, 5.8%, and 1.8%, respectively, when \(\theta_{s}>40^{\circ}\) as opposed to \(\theta_{s}\approx 20^{\circ}\). Furthermore, the \(C_{\lambda}\) values for both the MODIS-based and AFX methods in the NIR band are considerably higher than those in the green and red bands. In contrast, the Fixed-Jilin-1 method demonstrates greater stability, with \(C_{\lambda}\) standard deviation values that are markedly lower across all bands when compared to the other two methods. To assess the precision of the angular correction effect across various methods, we conducted a verification using the nadir reflectance data from the Jilin-1 GP01/02 PMS, which were cross-referenced with the simulated green, red, and NIR reflectance values derived from measured spectral data. The reflectance correction accuracy for each method is depicted in Figures 5-7 for the green, red, and NIR bands, respectively. Post-correction  
Figure 4: VIs-based LAI, FVC, and chlorophyll (R550 nm/T720 nm) estimations. The \(X\)-axis is the vegetation index, the left \(Y\)-axis is the R\({}^{2}\) value, and the right \(Y\)-axis is the RMSE value. **(a)** LAI, **(b)** FVC, and **(c)** chlorophyll (T850 nm/T720 nm). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Crop Parameters** & **Regression** & **R\({}^{2}\)** & **RMSE** \\ \hline LAI & \(LAI=e^{\frac{W/1-2.272}{\lambda 58}}\) & 0.84 & 0.73 \\ FVC & \(FVC=0.028\times e^{4.52\times MTV/2}\) & 0.81 & 6.9\% \\ chlorophyll (T850 nm/T720 nm) & \(CHL=e^{(0.26\times CVI-1)}\) & 0.85 & 0.15 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Regression analysis between VIs and the LAI, FVC, chlorophyll (T850 nm/T720 nm). reflectance values were found to be more closely aligned with actual values, as evidenced by higher coefficients of R\({}^{2}\), and a reduced root mean square error (RMSE) and mean relative error (MRE), compared to pre-correction values. Similar to the findings regarding the \(C_{\lambda}\) values, the VJB method exhibited the poorest correlation with the true reflectance, indicated by the lowest R\({}^{2}\). The Fixed-Landsat method appears to have exacerbated the impact of the angular effect on the red band, resulting in a corrected reflectance that deviated more significantly from the actual value than before the correction.