## 3 Selection of Methods for Methodology
### Visual Characteristics (Features) of the Satellite Image Content
In contrast, in another direction (e.g., perpendicular to the dune crests), the texture might appear rough and exhibit significant changes in pixel values (Figure 3c). **Regions of very small sizes** image feature [34] is related to the number of small clusters in the satellite image. The size of the individual cluster could be determined by the pixel count. In color-based image segmentation, the number of clusters is equivalent to the number of colors perceived by the human eye. Each cluster typically represents a distinct color or a range of similar colors. If the satellite image contains a wide range of distinct color values, the user may set many clusters, with each representing a different color. These clusters have semantic meaning, such as crop fields or buildings (Figure 4c), and can influence image segmentation in several ways. Generally, the possibility of making errors during segmentation decreases if there are only several big clusters (Figure 4a) compared to many small clusters (Figure 4b,d). If the image contains noise or slight variations in pixel values (roughness), these can be misinterpreted as distinct regions when segmenting images with many small regions. This sensitivity to noise can lead to errors in segmentation, resulting in the inclusion of unwanted details (under-segmentation) or the fragmentation of larger meaningful regions (over-segmentation). Many segmentation methods employ region merging and filtering or applying smoothing or noise reduction as the pre-processing step to address these issues. **Distortions of regions** refer to errors or inaccuracies in delineating and separating objects or regions of interest within an image. These distortions can take various forms, including holes, shadows, clouds (smoke), sea spray (Figure 5c), or compression artifacts. Shadows (Figure 5b) in satellite images can be particularly challenging and often mistakenly segmented as part of an object. Changes in lighting conditions can result in variations in the appearance of shadows. Thicker and more opaque clouds can create additional shadows on the ground (Figure 5d). This can result in overly complex and redundant  
Figure 3: Roughness of different desert regions. (**a**) “desert_2 jpg”, (**b**) “desert_207.jpg”, (**c**) “desert_205.jpg”, (**d**) “desert_203.jpg”. Images from the AID desert class. segmentation results, which may require additional post-processing steps to merge or simplify the segmented regions. Holes in the segmentation result can be defined as visually noticeable regions in the original image but semantically unwanted within the segmented area based on the context and application. Holes (under-segmentation) can happen due to the presence of low contrast, noise, or the limitations of the segmentation method. If an object in the image is  
Figure 4: Several larger regions. (**a**) “storagetanks_156.jpg”, regions of very small size; (**b**) “storagetanks_359.jpg”; (**c**) “densresidential_24.jpg”; (**d**) “port_267.jpg”. Images from the AID. Figure 5: Distortions of regions. (**a**) “pond_186.jpg”, (**b**) “storagetanks_13 jpg”, (**c**) “beach_66.jpg”, (**d**) “farmland_74.jpg”. Images from the AID. partially occluded by another object or some obstruction, it can lead to holes. For example, the reflection of the tree shadows in the water (Figure 5a). **Smoothness** (or continuity) **of region edges** image feature refers to the degree to which the boundaries between different regions in an image are visually coherent and uninterrupted. In the context of image segmentation, the smoothness of region edges significantly affects the accuracy of the segmentation results. If the edges between regions are not smooth enough and exhibit noise or irregularities, it can lead to over-segmentation (Figure 6a,b). Compression artifacts can break continuous object boundaries into smaller, disconnected segments (jagged edges). This fragmentation can result in the segmentation algorithm treating parts of a single object as separate objects.