## 3 Data and Methods
### Optical Data Fusion  
We combined eight spectral bands across the VIS-NIR regions from Sentinel-2 with the higher spatial resolution R, G, B, NIR, and synthesized bands from PlanetScope using the P + XS fusion method [84]. This image fusion technique enhances the spatial resolution of multispectral imagery by leveraging the finer spatial detail of high-resolution images (e.g., PlanetScope) while preserving the rich spectral information from lower-resolution sources (e.g., Sentinel-2). The core idea behind the P + XS method is that the high-resolution image provides detailed spatial patterns (such as edges and textures), while the low-resolution multispectral image provides accurate spectral information. The method linearly combines the high-resolution image with the resampled low-resolution image, transferring spatial detail from the former to the latter without significantly distorting the spectral characteristics. The Sentinel-2's 20 m bands (bands 5, 6, and 7) were matched with a synthesized PlanetScope band (S), as detailed in the equation presented in Table 4, which approximates the spectral properties of these bands [84]. Table 4 outlines the spectral band matches between Sentinel-2 and PlanetScope imagery.  
The P + XS method serves as a fusion design framework that guides the integration of high-resolution and low-resolution imagery. Within this framework, it is necessary to select a specific fusion algorithm to apply at the band level. We adopted the Smoothing Filter-based Intensity Modulation (SFIM) technique to perform the actual fusion.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Sentinel-2**} & \multicolumn{3}{c}{**PlanetScope**} \\ \hline
**Name** & **Description** & **Resolution** & **Name** & **Description** & **Resolution** \\ \hline Band 2 & Blue & & Band 1 & Blue & \\ Band 3 & Green & & Band 2 & Green & \\ Band 4 & Red & & Band 3 & Red & \\ Band 8 & NIR & & Band 4 & NIR & 4.77 m \\ Band 8A & Red Edge 4 & & Band 4 & NIR & 4.77 m \\ Band 5 & Red Edge 1 & & 20 m & \(S=\frac{83+84}{2}\) & & \\ Band 7 & Red Edge 3 & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Spectral correspondence between Sentinel-2 and PlanetScope bands. S is the synthetic band used to match Sentinel-2 bands 5, 6, and 7.  
Figure 5: U-Net encoder/decoder architecture diagram.  
SFIM is an image fusion technique designed to enhance the spatial resolution of low-resolution multispectral images while preserving their original spectral characteristics [85; 86]. SFIM has been successfully combined with the P + XS framework to improve the quality of fused imagery for land cover classification [87]. In this study, SFIM was used to integrate the lower-resolution bands of Sentinel-2 with the higher-resolution PlanetScope imagery in a band-wise manner. Specifically, all Sentinel-2 bands will be resampled to 4.77 m using cubic convolution and then fed into the following fusion formula together with the corresponding PlanetScope bands:  
\[FUS_{i}=\frac{X_{i}\times Y}{\underline{Y}} \tag{1}\]  
\(FUS_{i}\) is the i band after fusion, \(X_{i}\) is the \(i\)-th band of the resampled Sentinel-2 image, \(Y\) is the corresponding PlanetScope band, and \(\underline{Y}\) is the band \(Y\) after low-pass filtering and averaging.  
A 3 \(\times\) 3 mean low-pass filter was applied to the Sentinel-2 bands during the SFIM process, using the default configuration in ArcGIS Pro. The remaining SWIR1 and SWIR2 bands in the Sentinel-2--those not corresponding to any PlanetScope bands--were resampled to a spatial resolution of 4.77 m using cubic convolution and then directly combined with the previously fused bands, which yielded the optical fusion dataset composed of ten bands.