# Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping
## 3 Results
### Classification
#### 3.2.2 Supervised Machine Learning Model  
From the five-fold cross-validation tuning with 20 repetitions, the selected hyperparameters for the EUNIS II level classification were: \(mtry=20\); \(num.trees=908\); \(min.node.size=2\). For the EUNIS III level classification, a different hyperparameters set has been tuned for each EUNIS II level class. For the T1 classification, the \(mtry\) was set to 24, the \(num.trees\)  
Figure 4: List of environmental, temporal and spectral predictors selected after multi-collinearity and expert-based analysis for each EUNIS II and III hierarchical level. Gini index values are reported for each Random Forests (RF) model: EUNIS II; T1 = Broadleaved Decidous; T2 = Broadleaved Evergreen; T3 = Needleleaved. Colored bars represent the variable importance ranking, based on the Gini index value. Only variables with colored bars were selected as predictors in the model. * reconsidered variable through expert-based selection procedure. was set to 989, and the _min.node.size_ was set to 3; for the T2 classification, the _mtry_ was set to 16, the _num.trees_ was set to 527, and the _min.node.size_ was set to 2; and, for the T3 classification, the _mtry_ was set to 15, the _num.trees_ was set to 981, and the _min.node.size_ was set to 2. The forest habitat types classification, using the RF modelling approach based on all input records (i.e., response variable) and including the variables selected (i.e., predictor variables), achieved an overall accuracy of 87% at the EUNIS II level classes (i.e., T1, T2, and T3). The highest misclassification was found between the broadleaved deciduous and the broadleaved evergreen habitat-type forests. The three EUNIS II level classes of forest (broadleaf and conifer forest) achieved very high producer's and user's accuracies (>85%; see Table 4). The second stage of habitat-type classification has been performed at EUNIS III hierarchical level, achieving an overall accuracy of 76.14%. The highest overall accuracy was the one of the broadleaved evergreen forest, equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively (see Tables 5-7). Within the broadleaved evergreen habitat type classes, the mainland laurophylulous forest (EUNIS III T2) obtained the lowest classification accuracy (29.4%), and its highest misclassification was with the Mediterranean evergreen _Quercus_ forest; instead, regarding the Mediterranean evergreen _Quercus_ forest, a user's accuracy of 96.5% was achieved (see Table 5). The needleleaved forest (EUNIS II T3) classes were, on average, well classified; indeed, the user's accuracy was higher than 65% for each class. On the contrary, classes of broadleaved deciduous forests (EUNIS II T1) were classified worst: six classes had a user's accuracy below 50%, three classes had a user's accuracy between 50% and 60%, and only three classes had a user's accuracy higher than 60%. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Map Class**} & \multicolumn{8}{c}{**Reference Class**} \\ \cline{2-11}  & **T1** & **T2** & **T3** & **Sum** & **UA (SE)** \\ \hline
**T1** & **1037** & 80 & 63 & 1180 & 89.9 (0.00) \\
**T2** & 93 & 564 & 0 & 657 & 87.6 (0.01) \\
**T3** & 23 & 0 & **162** & 185 & 72 (0.02) \\ \hline
**Sum** & 1153 & 644 & 225 & **OA (SE)** & 87.2\% (0.75) \\ \hline
**PA (SE)** & 87.9 (0.00) & 85.8 (0.03) & 87.6 (0.13) & **Kappa** 0.77 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Confusion matrix of RF result for the EUNIS II level classification. T1: broadleaved deciduous forest habitat-type, T2: broadleaved evergreen forest habitat-type, T3: needleleaved forest habitat-type. OA: Overall Accuracy, PA: Producer’s Accuracy, UA: User’s Accuracy, SE: Standard Error.