## 3 Results
### Selection of the Best Inversion Strategy
#### 3.3.3 C\({}_{ab}\) and Car Retrieval Performance Comparison  
For C\({}_{ab}\) at q = 300, apart from DMCARI2, VI differences performed better than methods based on RMSE and SAM (Table 9). GM\({}_{\_}{94}\)b is the overall best-performing VI, with the lowest RMSE, highest R\({}^{2}\), and lowest STDB (5.21 ug/cm\({}^{2}\), 0.73, and 3.38 ug/cm\({}^{2}\), respectively), besting even soil-adjusted VI. When compared to field measurements from all dates, most GM\({}_{\_}{94}\)b-estimated points are very close to the first bisector, and only one point (pink from summer 2013) is greatly underestimated (Figure 10a).  
For Car, at q = 400, the best method is also clear: RMSE INT CAR is the only method to present a low RMSE, a low STDB, and a high R\({}^{2}\) (1.34 ug/cm\({}^{2}\), 1.06 ug/cm\({}^{2}\) and 0.59, respectively. See Table 9).  
The RMSE INT CAR method showed the best performances overall, with estimated values very close to the first bisector (Figure 10b) for all seasons.  
Figure 8: Influence of \(q\) on the estimation RMSE for LAI (**a**), C\({}_{ab}\) (**b**) and Car (**c**) using validation data from every date.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Method**} & **RMSE** & **bias** & **STDB** & \multirow{2}{*}{\(\mathbf{R^{2}}\)} \\  & **[m\({}^{2}\)/m\({}^{2}\)]** & **[m\({}^{2}\)/m\({}^{2}\)]** & **[m\({}^{2}\)/m\({}^{2}\)]** \\ \hline RMSE INT LAI & 0.62 & \(-\)0.49 & 0.29 & 0.38 \\ SAM INT LAI & 0.39 & \(-\)0.27 & 0.25 & 0.63 \\ NDVI & 0.22 & 0.07 & 0.18 & 0.80 \\ MSAVI2 & 0.25 & 0.14 & 0.17 & 0.81 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Inversion methods performances for LAI estimation for \(q\) = 100 over all dates available.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{2}{c}{**RMSE**} & \multicolumn{2}{c}{**bias**} & \multicolumn{2}{c}{**STDB**} \\  & [\(\mu\)g/cm\({}^{2}\)] & [\(\mu\)g/cm\({}^{2}\)] & [\(\mu\)g/cm\({}^{2}\)] & [\(\mu\)g/cm\({}^{2}\)] & \\ \hline \multicolumn{2}{c}{\(C_{ab}\)} & & & \\ \hline RMSE INT CAB & 11.92 & 8.99 & 5.21 & 0.14 \\ SAM INT CAB & 11.37 & 7.46 & 6.05 & 0.08 \\ MCARI2 & 12.15 & \(-\)5.05 & 8.62 & 0.01 \\ TCARI/OSAVI & 6.34 & 2.75 & 4.15 & 0.48 \\ Maccioni & 8.02 & 4.36 & 5.03 & 0.32 \\ gNDVI & 5.39 & \(-\)2.15 & 3.82 & 0.61 \\ GM\_94b & 5.21 & \(-\)3.21 & 3.38 & 0.73 \\ \hline \multicolumn{2}{c}{Car} & & & \\ \hline RMSE INT CAR & 1.34 & 0.79 & 1.06 & 0.59 \\ SAM INT CAR & 6.53 & 1.59 & 4.53 & 0.29 \\ R515/R570 & 4.01 & \(-\)1.26 & 3.74 & 0.26 \\ CRI & 2.89 & \(-\)0.2 & 2.1 & 0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Inversion method performances for \(C_{ab}\) (\(q=300\)) and Car (\(q=400\)) estimations over all dates available.  
Figure 9: Estimated LAI using the \(D_{NDVI}\) method versus measured LAI. Colors indicates the location within the site, see Figure 1. Error bars for the y-axis correspond to the estimation standard deviation, computed as the standard deviation of the first \(q=100\) solutions. For the x-axis, as each plot’s measured LAI is the average of the computed LAI from each of the DHP of the plot, error bars correspond to the minimum and maximum values of each plot’s DHP set.