## 2 Materials and Methods
### Minimizing the Restrictions  
Within the scope of this study, two datasets were created, dataset-1 and dataset-2. The first was created to minimize restrictive effects based on the proposed approach, while the other had the same number of images but was structurally shallower, and was created to concretely demonstrate the positive contributions of the proposed approach. One of the constraints is that the images contain a single band. Because DL-based SR models work on multi-band images, three-band images were obtained by adding two copies of each image to the existing one. Although this situation makes the images artificially multispectral in the dataset, it does not do so in terms of content. The main purpose of this process was to run the SR model without errors during training. Although the images contain three bands, the richness that cannot be provided in terms of content is provided with the approach depicted in Figure 2.  
Photographs from different years covering the same regions were used together. Due to the changes in LC over time, photographs from different years represent various content with a single band. A region that appears as a residential area within the same region in the 1968 and 1982 images might have been a bare land in 1954. In such cases, two spectral variations were obtained for regions representing the same content in the dataset. As a result, the limitation arising from the number of bands in historical aerial photographs is overcome by digitally converting them into three bands and representing the same regions separately with images derived for different years. In the dataset to be used in SR studies, differences between photographs have an effect of increased distinguishability. Apart from the differences in the distribution of LC within the area covered by the photograph, color information is a factor that makes the images different from each other. Because the images used in the study are single bands, there is no color diversity as in multispectral images. This causes different photographs to display higher similarity than color images even though they contain different regions. To minimize this limitation, intensity values were used. The brightness value in multispectral images, which is the numerical equivalent of color information, is replaced by intensity values in  
Figure 1: Orthophotos and historical photographs used for the study. grayscale images. These values were used to control details and brightness adjustments in grayscale images. For this reason, apart from the distribution of LC, intensity values were taken as the basic factor affecting distinguishability in the grayscale images. Although forestry areas generally have low intensity values, photographs of forestry with an average brightness value greater than 128 for an 8-bit image were included in the dataset. Similarly, although farmland areas in historical images mostly had high intensity values, photographs of agricultural areas with low intensity values on average were included in the dataset. The need to provide distinguishability due to the lack of color information was minimized by creating photographs that contain homogeneous intensity values. A visual depiction of the intensity distributions of the images in both datasets is presented in Figure 3.  
Another limitation of historical aerial photography is that there are not enough available HR-LR pairs, both numerically and in quality, to cover the different land cover classes required for SR applications. The quality of HR images and the LR images derived from them makes learning the relationship between image pairs difficult. Even LR images derived from images considered HR in many commonly used datasets, such as T91 [22],  
Figure 3: Intensity distributions of dataset-1 (**left**) and dataset-2 (**right**). Figure 2: Eliminating single-band situation. DIV2K [23], Set5 [24], and Set14 [25], bear a higher level of discrimination than those used in this study. This is the result of the technological possibilities available with the hardware of the period.