## 2 Materials and Methods
### Classification and Accuracy Assessment
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Accuracy** & **Method** & **Classifier** & **Input Image** & \multicolumn{2}{c}{**Segmented**} & **Segmentation** \\  & & & & **Additional Image** & **Settings** \\ \hline
60.9 & OBIA & SVM & Sept 29/All Bands & May 22/Bands 8 3 2 & SegSize 5 \\
54.3 & OBIA & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-2 & May 22/Bands 8 3 2 & SegSize 5 \\
49.4 & OBIA & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-2 & May 22/Bands 8 3 2 & SegSize 5 \& SA 1-6 \\
71.7 & OBIA & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-4 & May 22/Bands 8 3 2 & SegSize 5 \\
67.3 & OBIA & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-5 & May 22/Bands 8 3 2 & SegSize 5 \& A 1-6 \\
59 & OBIA & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-6 & May 22/Bands 8 3 2 & SegSize 5 \& SA 1-2-5 \\
61.6 & OBIA & RF & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-7 & May 22/Bands 8 3 2 & SegSize 5 \\
63.3 & PB & SVM & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-8 & \\
76.2 & PB & RF & Sept 29/Bands 2 3 4 5 6 7 8 9 \& PCA 1-9 & \\
67.7 & OBIA & SVM & Sept 29/PCA 1-12 & May 22/Bands 8 3 2 & SegSize 5 \\
61.8 & OBIA & SVM & May 22/All Bands & May 22/Bands 8 3 2 & SegSize 5 \\
80.7 & OBIA & SVM & May 22/Sept 29/Bands 8 3 2 & May 22/Bands 8 3 2 & SegSize 5 \\  & & & \& PCA 14 \& NDVI May 22 & \\
76 & OBIA & SVM & May 22/All Bands \& NDVI \& PCA 1-4 & May 22/Bands 8 3 2 & SegSize 5 \\
65 & OBIA & SVM & May 22/Bands 2 3 8 8 & NDVI May 22 & May 22/Bands 8 3 2 & SegSize 5 \\
75.7 & OBIA & SVM & May 22/Bands 2 3 7 8 9 & May 22/Bands 8 3 2 & SegSize 5 \\  & & & \& PCA 14 \& NDVI May 22 & \\
55 & PB & SVM & May 22/Bands 2 3 7 8 9 \& PCA 1-4 \& NDVI May 22 & \\
75.1 & PB & RF & May 22/Bands 2 3 7 8 9 \& PCA 1-4 \& NDVI May 22 & \\
87.2 & OBIA & SVM & May 22/Bands 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
59.9 & OBIA & SVM & May 22/Bands 5 6 7 \& PCA 1-4 & May 22/Bands 8 3 2 & SegSize 5 \\
78.8 & OBIA & SVM & May 22/Bands 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
53.7 & PB & SVM & May 22/Bands 5 6 7 & May 22/Bands 6 7 & \\
67.1 & OBIA & RF & May 22/Bands 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
87.2 & OBIA & SVM & May 22/Bands 5 6 7 \& May 22/Bands 8 3 2 & SegSize 5 \\
87.2 & OBIA & SVM & May 22/Bands 4 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
62.5 & OBIA & RF & May 22/Bands 4 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
80.3 & OBIA & SVM & May 22/Bands 8 3 2 & SegSize 5 \\  & & & \& May 22/Bands 8 3 2 & SegSize 5 \\
63.3 & OBIA & SVM & May 22/CSA 1-12 & May 22/Bands 8 3 2 & SegSize 5 \\
60 & OBIA & SVM & May 22/All Bands \& PCA 3 1-4 & May 22/Bands 8 3 2 & SegSize 5 \\
89.1 & OBIA & SVM & August 09/All Bands & May 22/Bands 8 3 2 & SegSize 5 \\
63.1 & OBIA & RF & August 09/All Bands & May 22/Bands 8 3 2 & SegSize 5 \\
46 & PB & SVM & August 09/All Bands & May 22/Bands 8 3 2 & SegSize 5 \\
65.2 & OBIA & SVM & August 09/Bands 5 6 7 & May 22/Bands 8 3 2 & SegSize 5 \\
80.5 & OBIA & SVM & August 09/Bands 5 6  
Different classification settings were chosen based on the spectral information but also the spatial resolution of the different bands (10 m vs. 20 m). For segmentation, for example, higher spatial resolution is important for better detail. Different multitemporal approaches were tested with a combination of the 20 m resolution red edge bands (bands seven, six and five). A variation of different segmentation parameters was applied to the 22 May scene (with the highest spectral differences) to test effects of varying parameters. The best segmentation result (see Table 3 part 1) was used as segmented image for the OBIA for both ML algorithms and compared to the PB classification using the same bands, PCs and indices. In total, 54 classifications were conducted and compared to optimize the separation of broad-leaved tree species (oak, beech and other deciduous trees). For accuracy assessment of all classification approaches, samples derived from the inventory areas (compare Table 2 and Figure 1) were randomly split into training and test samples. The center of all pixels contained in the inventory circles were considered a sample.