# CROpland Mapping Using Earth Observation Derived Phenological Metrics +
## 3 Results  
The RF hyperparameter tuning produced the following settings: _mtry_ = 5, _min.node.size_ = 2, _ntree_ = 893 for NDVI, and _mtry_ = 4, _min.node.size_ = 3, _ntree_ = 424 for LAI. The selected predictor variables reporting the highest Gini index were 13 for NDVI and 11 for LAI (Table 1). The resulting spatial crop type map is shown in Figure 1. Regarding the classification obtained from the NDVI time series analysis, an overall accuracy of 78.6% was achieved \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Name** & **Description** & \multicolumn{2}{c}{**Unit**} & \multicolumn{2}{c}{**Importance**} \\ \hline  & & **NDVI** & **LAI** & **NDVI** & **LAI** \\ \hline PoS\_doy & Peak of season DoY & DoY & DoY & - & 2611.057 \\ \hline PoS\_value & Peak of season value & dl & m\({}^{2}\)/m\({}^{2}\) & - & - \\ \hline EGS\_doy & End of growing season DoY & DoY & DoY & - & 2653.588 \\ \hline EGS\_value & End of growing season value & dl & m\({}^{2}\)/m\({}^{2}\) & - & - \\ \hline EoS\_doy & End of season DoY & DoY & DoY & - & - \\ \hline EoS\_value & End of season value & dl & m\({}^{2}\)/m\({}^{2}\) & 22,521.31 & - \\ \hline amplitude & Amplitude value & dl & m\({}^{2}\)/m\({}^{2}\) & 27,390.47 & 2052.926 \\ \hline greenup\_doy & Greenup DoY & DoY & DoY & 47,205.49 & - \\ \hline greenup\_rate & Greenup rate & dl & m\({}^{2}\)/m\({}^{2}\) & 24,246.63 & - \\ \hline senescence\_doy & Senesence DoY & DoY & DoY & 57,316.61 & - \\ \hline senescence\_rate & Senesence rate & dl & m\({}^{2}\)/m\({}^{2}\) & 20,347.07 & - \\ \hline plateau\_slope & Rate of change during the maturity plateau & dl & m\({}^{2}\)/m\({}^{2}\) & 23,675.63 & - \\ \hline DoS & Duration of the season & Days & Days & 23,237.03 & 1627.551 \\ \hline LMP & Length of maturity plateau & Days & Days & - & 1450.587 \\ \hline STI & Seasonal time-integrated value & dl & m\({}^{2}\)/m\({}^{2}\) & 22,737.46 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._with a Cohen's kappa coefficient of 0.54 (Table 2). Some classes were more accurately classified than others, such as clover and alfalfa (UA = 91.1%; PA = 82.8%), maize (UA = 69.5%; PA = 58%), and winter cereals (UA = 55.9%; PA = 69.2%). On the contrary, sorghum was the worst classified (UA = 6%; PA = 26.8%). Rape and soy obtained low user's accuracy (17.2% and 17.6% respectively). As for the classified crop types resulting from the LAI time series analysis, an overall accuracy of 78.3% was achieved, with a [PERSON]'s kappa coefficient of 0.59 (Table 3). Unlike the NDVI model results, the LAI model generally showed high user's and producer's accuracies for all the classes, except for rapeseed (UA = 10.7%), and the misclassification was principally with winter cereals. \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**K = 0.54**} & \multicolumn{1}{c}{**Classification**} & \multicolumn{1}{c}{**\#C**} & \multicolumn{1}{c}{**\#C**} & \multicolumn{1}{c}{**\#C**} & \multicolumn{1}{c}{**\#C**} & \multicolumn{1}{c}{**\#C**} & \multicolumn{1}{c}{**\#C**} \\ \cline{2-11}
**Reference Map** & **\#C** & **\#C** & **\#C** & **\#C** & **\#C** & **\#C** & **\#C** & **\#C** & **\#C** \\ \hline
**Winter cereals** & **3804** & 1609 & 4 & 2 & 8 & 24 & 44 & 0 & 5495 & 69.2 \\
**Clower and Alfafla** & 2974 & **17,084** & 53 & 45 & 36 & 29 & 410 & 0 & 20,631 & 82.8 \\
**Maize** & 2 & 21 & **528** & 62 & 215 & 0 & 71 & 11 & 910 & 58 \\
**Sorghum** & 1 & 1 & 8 & **11** & 11 & 0 & 9 & 0 & 41 & 26.8 \\
**Sunflower** & 6 & 20 & 139 & 34 & **230** & 0 & 62 & 3 & 494 & 46.6 \\
**Rape** & 7 & 1 & 0 & 0 & 0 & **11** & 0 & 0 & 19 & 57.9 \\
**Horticultural crops** & 10 & 16 & 28 & 29 & 54 & 0 & **540** & 0 & 677 & 79.8 \\
**Soy** & 0 & 0 & 0 & 0 & 0 & 0 & **3** & 3 & 100 \\
**Total** & 6804 & 18,752 & 760 & 183 & 554 & 64 & 1136 & 17 & **28,270** & **OA\%** \\ \hline
**UA \%** & 55.9 & 91.1 & 69.5 & 6 & 41.5 & 17.2 & 47.5 & 17.6 & **OA\%** & 78.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Confusion matrix of the RF results from the NDVI time series analysis.