## 2 Data Specifications and Preprocessing  
To train and test classification algorithms under varying conditions, six subsets of different multi-spectral satellite image types are used in the following (Figure 1a). Details about the specific images, including spectral, radiometric and geometric properties, acquisition date, subset area and applied image preprocessing steps are listed in Table 1. All images have been layer-stacked, georectified and when covering the same spatial subset have been co-registered to each other. In case of resampling operations, a nearest neighbor algorithm has been applied since it is the interpolator that alters the spectral values the least [23]. For image fusion of multi-spectral and panchromatic bands (pan-sharpening), the Brovey transform, which is implemented in GRASS [24], has been used. The Brovey transform [25] is a color transform algorithm that normalizes the lower resolution multi-spectral image bands and multiplies the result with a higher resolution (panchromatic) band. Figure 1: (**a**) Image subsets. (**b**) Image segmentations. (**c**) Reference datasets. For each image subset, a reference dataset has been compiled. The images have been segmented using an efficient graph-based segmentation algorithm [26] (see also Section 3) (Figure 1b) and the resulting segments have been manually labeled based on visual interpretation of the satellite image to create the reference datasets (Figure 1c). For the VHR satellite images (Quickbird (QB), WorldView-2 (WV2) and Ikonos (IK) [27]), landcover classes were organized in two groups: (1) \"built-up areas\" (\"buildings\") and (2) \"not built-up areas\" (\"vegetation\", \"bare soil\", \"shadow\", \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Image** & **Type** & \begin{tabular}{c} **Spectral** \\ **Res. (\(\mathbf{\mu}\)m)** \\ \end{tabular} & \begin{tabular}{c} **Radiom.** \\ **Res. (bit)** \\ \end{tabular} & \
\begin{tabular}{c} **Geom.** \\ **Res. (\(\mathbf{m}\))** \\ \end{tabular} &
\begin{tabular}{c} **Size (px)** \\ **Coverage** \\ \end{tabular} & **Preprocessing** \\ \hline
**IK** & Ikonos & \begin{tabular}{c} 0.45–0.9 \\ (4 bands) \\ \end{tabular} & 11 & \begin{tabular}{c} 1 (pan) \\ 4 (mul) \\ \end{tabular} & \begin{tabular}{c} 800 \(\times\) 500 \\ 11 \\ \end{tabular} & \
\begin{tabular}{c} 22.02.03 \\ Hobart \\ 1500 \(\times\) 1200 \\ \end{tabular} &
\begin{tabular}{c} pan-sharpened \\ 29.09.09 \\ Bushke \\ \end{tabular} \\
**QB** & Quickbird & \begin{tabular}{c} 0.45–0.90 \\ (4 bands) \\ \end{tabular} & 11 & \begin{tabular}{c} 0.5 (pan) \\ 2.4 (mul) \\ \end{tabular} & \begin{tabular}{c} 1200 \(\times\) 800 \\ 2.4 (mul) \\ \end{tabular} & \
\begin{tabular}{c} 12.10.11 \\ Karakol \\ \end{tabular} &
\begin{tabular}{c} pan-sharpened \\ 22.08.77 \\ - \\ \end{tabular} \\
**TM** & Landsat TM & \begin{tabular}{c} 0.45–12.5 \\ (7 bands) \\ \end{tabular} & 8 & \begin{tabular}{c} 30 (mul) \\ 120 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 120 (PIR) \\ \end{tabular} & \
\begin{tabular}{c} 1000 \(\times\) 700 \\ 14.08.01 \\ \end{tabular} &
\begin{tabular}{c} pan-sharpened \\ 22.08.77 \\ - \\ \end{tabular} \\
**ETM** & Landsat ETM & \begin{tabular}{c} 0.45–12.5 \\ (7 bands) \\ \end{tabular} & 8 & \begin{tabular}{c} 30 (mul) \\ 120 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 120 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} & \begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} & \
\begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} &
\begin{tabular}{c} 1000 \(\times\) 700 \\ 1000 (PIR) \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Satellite images, their specifications and applied preprocessing steps. Figure 1: _Cont._  
\"other sealed surfaces\").