## 3 Results and Discussions  
### Spectral Feature Analysis  
In the study area, the most common land cover types are vegetation, crops, bare soil (Gobi), desert, river, building, road and other. First of all, we analyzed the spectral features (Figure 4) of seven types of objects on the ground in the GF-2 multispectral image (Figure 5), which was acquired on 24 May 2021. As shown in Figure 4, most of the samples are observed to have the highest reflectance in the NIR band, except water, which is able to absorb the NIR radiation to an extreme degree. It can be inferred that the water body can be identified by the reflectance of the NIR band or by the NDWI index instead. In addition, the samples of the cement rooftop show stronger reflectance in all of the four visible bands other than that of the metal rooftop or the land (either with covers or without). This interprets the rooftop of cement (mostly for the residential housing) as a bright rectangle in either the RGB composite or the pseudocolored imageries. The metal rooftop, on the other hand, shows the highest reflectance in the blue band, causing the rooftop to often be painted as blue. This kind of rooftop is often related to the factories or commercial buildings in Western China. In this paper, we introduce an index that identifies the feature of colored metal rooftops in accordance with the spectral reflectance (Figure 4), named the NDMRI (normalized difference metal rooftop index), which is defined as follows:  
\[NDMRI=\frac{\rho_{blue}-\rho_{red}}{\rho_{blue}+\rho_{red}} \tag{10}\]  
From Figure 5, we find that the water body and the buildings with the blue metal roof are highlighted in the NDWI and NDMRI image, respectively. Moreover, we are able to \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Validated Results**} \\ \cline{2-6}  & & **Category 1** & **Category 2** & **\(\dots\dots\)** & **Category N** \\ \cline{2-6} Predicted & Category 1 & \(p_{11}\) & \(p_{12}\) & \(\dots\dots\) & \(p_{1N}\) \\ Results & Category 2 & \(p_{21}\) & \(p_{22}\) & \(\dots\dots\) & \(p_{2N}\) \\  & \(\dots\dots\) & \(\dots\dots\) & \(\dots\dots\) & \(\dots\dots\) & \(\dots\dots\) \\  & Category N & \(p_{N1}\) & \(p_{N2}\) & \(\dots\dots\) & \(p_{NN}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The confusion matrix. Figure 4: Mean reflectance of six types of samples extracted from GF-2 multispectral bands. Vegetation: land covered by vegetation; plastic film: land covered by plastic films; water: river, pool, lake, etc. ; bare soil: land with no covers; desert: the desert samples; cement roof: rooftop that is made up of cement or similar materials; metal roof: rooftop that is made up of metal. discriminate between the metal and cement rooftop by the difference of spectral reflectance in red or green (see Figure 4). Accordingly, we analyze the ability of the feature extraction of NDVI and EVI regarding the different land cover types: crops, plastic film, desert and shrubs in the Gobi area (see Figure 6 for details). Figure 5: The GF-2 multispectral image slices (**left**), acquired on 24 May 2021, and the feature index image pairs (**right**). A: desert; B: river; C lake; D: blue metal rooftop of buildings; E: cement rooftop of buildings (white square). Figure 6: The GF-2 multispectral image slices (**left**), acquired on 24 May 2021, and the feature index image pairs (**right**). A: land covered by plastic film; B: land with vegetation/crops; C bare soil; D: desert; E: shrubs in the desert. As shown in Figure 6, the NDVI index can be used to differentiate between land covered with plastic film (a common agricultural technique in the spring in Western China, serving to maintain the temperature and humidity of the soil below) and vegetation (crops). This is because the vegetation tends to reflect more NIR radiation than the agricultural plastic film.