*4.2. What Data Quality can be Achieved with UAS-Technology?*

The data quality can be derived from checkpoint residuals and a visual evaluation of the final orthomosaic. Final checkpoint residuals are outlined in Table 8. Almost pixel-level geometric accuracy was achieved with the Busogo dataset. Both Gahanga and Busogo show more than 10cm RMS error of horizontal residuals. Differences regarding final geometric accuracy can be attributed to the UAS equipment and sensor as well as to the device and conditions for the measurements of reference points. Nonetheless, obtained orthomosaics are of high geometric accuracy and comparable to results in other scientific contributions [44,45].


**Table 8.** Specifications of final results.

The visual evaluation revealed commonalities but also some differences in the datasets. Figure 5 presents the final orthomosaics of all three datasets. It is evident that sufficient overlap was considered during the flight missions as no gaps were present and the area of interest was entirely covered by the reconstructed scene. Differences of the visual quality are evident in the close-up views. Here, the image quality was best for the Muhoza dataset, as most features including rooftops, as well as vegetation, were well exposed in the orthomosaic. In contrast, the Busogo dataset showed a lower image quality, visible in over-exposed roofs and problems to fulfil a proper histogram matching during image processing. This can be attributed to the adverse lighting conditions during data capture. Even though meteorological conditions were perfect for flying during data capture of the Gahanga dataset, the sensor showed substantial difficulties to deal with bright and dark image features. Especially a large part of the parking area is very overexposed, even though the surface was covered with reddish gravel.

**Figure 5.** Overview of the generated orthomosaics and GCP/checkpoint distribution.
