## 3 Experiments
### Datasets
The dataset contains 80 images, each with a size of \(1000\times 1000\) pixels, covering a total of 64 scenes. The images were randomly selected from Landsat 8 satellite imagery between 2013 and 2014. Table 2 shows the details of each band in the SPARCS dataset. Figure 8: HRC_WHU: (**a**) original; (**b**) label diagrams. Figure 7: Example: (**a**) city; (**b**) farmland; (**c**) vegetation; (**d**) water; (**e**) barren land. The preview images in the SPARCS dataset are pseudo-color imagery, which maps shortwave infrared waves 1 (B6), near-infrared waves (B5), and red waves (B4) to RGB channels, thereby enabling the visualization of different feature types and providing key information for subsequent accurate classification. In the process of labeling, the tagger relies entirely on visual interpretation, avoiding the problem of incorrect labeling that can be caused by automatic threshold handling. The pixels in the image are labeled with seven categories, which are clouds, cloud shadows, cloud shadows on water, snow/ice, floods, and backgrounds. Since the two categories of flood and water cloud shadow account for only 1.8% and 0.24%, we merged them into water and cloud shadow, respectively. The merged label chart contains five categories, and Table 3 shows the corresponding tables of labels and categories. Due to memory limitations, we cropped 80 images from the SPARCS dataset into sub-images of 256 \(\times\) 256 pixel size, resulting in a total of 1280 images. Due to the limited training data, the experimental model is prone to overfitting, so we expanded the SPARCS dataset. We used techniques such as random rotation and vertical and horizontal flipping to expand the original 1280 images to 3168 images. Among them, the training set and the validation set have 2534 and 634 images, respectively. Figure 9 shows a set of original preview and label plots in the SPARCS dataset. \begin{table}
\begin{tabular}{c c c c} \hline
**Band Number** & **Band Name** & **Range (nm)** & **Spatial Resolution (m)** \\ \hline B1 & Coastal waves & 0.433–0.453 & 30 \\ \hline B2 & Rambo & 0.450–0.515 & 30 \\ \hline B3 & Green Wave & 0.525–0.600 & 30 \\ \hline B4 & Red Wave & 0.630–0.680 & 30 \\ \hline B5 & Near-infrared waves & 0.845–0.855 & 30 \\ \hline B6 & SWIR 1 & 1.560–1.660 & 30 \\ \hline B7 & SWIR 2 & 2.100–2.300 & 30 \\ \hline B8 & Panchromatic waves & 0.500–0.680 & 15 \\ \hline B9 & Cirrus waves & 1.360–1.390 & 30 \\ \hline B10 & Thermal Infrared 1 & 10.60–11.19 & 100 \\ \hline B11 & Thermal Infrared 2 & 11.50–12.51 & 100 \\ \hline B12 & New Band 1 & 1.610–1.670 & 20 \\ \hline B13 & New Band 2 & 2.100–2.200 & 20 \\ \hline B14 & New Band 3 & 3.900–4.000 & 60 \\ \hline B15 & New Band 4 & 4.500–4.800 & 60 \\ \hline B16 & New Band 5 & 8.000–8.500 & 120 \\ \hline \end{tabular}
\end{table} 
Table 2: Specific parameters of satellite imagery from the SPARCS dataset. \begin{table}
\begin{tabular}{c c c c} \hline
**Pixel Value** & **Category** & **Color** & **Percentage** \\ \hline
0 & Cloud & white & 21\% \\ \hline
1 & Cloud Shadow & black & 7\% \\ \hline
2 & Snow/ice & cyan & 6\% \\ \hline
3 & Water & blue & 4\% \\ \hline
4 & Background & grey & 62\% \\ \hline \end{tabular}
\end{table} 
Table 3: The table that corresponds to the labels and categories of the SPARCS dataset.