## 4 Results and Analysis  
### Characteristic Band Selection Analysis  
With reference to the coordinates of the measured data points, five vegetation samples were selected from the preprocessed OHS hyperspectral images, and the spectral mean curves of the five vegetation samples are shown in Figure 3a. From Figure 3a, it can be seen that the spectral mean curves of the five planted vegetation samples exhibit distinct characteristics of vegetation spectral curves, i.e., there is a typical \"red edge\" feature within the spectral wavelength range of 680 nm-760 nm. It is worth noting that the spectral mean curve for _Sueda glauc_ does not show obvious characteristics of vegetation spectral curves, which is due to the fact that _Sueda glauc_ is more widely distributed in the Yellow River Delta and the growth density of vegetation is small, so its spectral curve is easily affected by the soil substrates. From the figure, it can be seen that the differences in the five vegetation curves were primarily observed in the near-infrared band, with less noticeable differences in the visible band. Figure 3b displays the spectral mean curve of the vegetation after the removal of the continuum. Here, it is evident that the differences in the spectral characteristics of the vegetation in the near-infrared band have essentially been normalized and eliminated, while the differences in the spectral characteristics of the vegetation in the visible band  
Figure 3: Spectral mean curves of 5 planted covers before and after continuum removal. (**a**) Raw spectrum mean spectrum, (**b**) Mean spectrum after continuum removal. have been accentuated. This is particularly notable in the green and red band ranges, where the differences in the spectral characteristics between different vegetation types are significantly more pronounced compared to the original spectral curves. Moreover, the gap between the maximum and minimum values of spectral reflectance within these two bands is also further widened compared to the original spectrum. The removal of the continuum further enhanced the separability between _Phragmites_ and _Spartina alterniflora_ compared to the original spectra. However, the separability between Tamarix and _Suada glauca_ was reduced after the removal of the continuum. Figure 4 illustrates the pairwise comparison of spectral features between _Phragmites_ and the other four vegetation species. In the original spectra, the differences between _Phragmites_ and _Typha orientalis Presl_ are not prominent, both in the visible and near-infrared bands. However, after the continuum removal, the distinguishable band between _Phragmites_ and the remaining four vegetation types is shifted from the near-infrared band of the original spectra to the visible band. Within the distinguishable band range, the spectral differences between _Phragmites_ and the other vegetation types are significantly amplified, which demonstrates that the removal of the continuum is advantageous for the extraction of the spectral features of _Phragmites_. Table 3 presents a lookup table of the spectral characteristics of the five vegetation types before and after the continuum removal. In this table, the spectral curves of the five vegetation types after the removal of the continuum are the upper-right blue sections of the two comparative graphs of the distinguishable bands, while the original spectral curves are the lower-left green sections of these comparative graphs. By intersecting these bands, wavelength ranges of 466-709 nm and 806-833 nm were selected as the feature bands. Following the selection of the feature bands, principal component analysis (PCA) was employed for the dimensionality reduction of the OHS hyperspectral remote sensing image data. After this reduction, it was observed that the first three principal components already contained more than 99% of the original information. Consequently, the first three principal components were selected to synthesize the effect map to serve as the reference map for the subsequent vegetation classification phase.