## 4 Discussion
An example of the part of the map produced with Agisoft is presented in Figure 15. In this example, 37 images were used and the achieved processing time on a desktop computer (Intel i7 processor, 16 GB RAM, nVidia GTX 9700 GPU) was around 20 s. Although Agisoft metashape and Image Composite Editor are essentially different software tools, because Agisoft performs photogrammetric processing of digital images and generates 3D spatial data while ICE generates 2D images, both can be used for this application (importing updated maps into QGIS). Nevertheless, is worth noting that since Agisoft output has all the data needed for georeferencing as well as digital elevation data, these features can be used for further steps of mission planning (terrain passability calculation, terrain segmentation and search sectors' definition), which is not the case with ICE output. However, Agisoft software is not cheap (around USD 5000 per license), so a free option such as ICE should not be discarded. At the moment, both options are available on user request from the QGIS GUI, but adding an automated request for image stitching directly from the Python script on the client side (GS) should not be a problem. For our application, around 10-20 images per minute (depending on flight parameters and used hardware) will be received. Since the intention is to have maps updated as soon as possible, waiting for all images to be received and stitching them after that is not an acceptable option. A more reasonable approach would be making smaller updated map patches at appropriate time intervals. The optimal interval length is yet to be determined but, at the moment, we are planning to start with forwarding acquired images to the stitching phase every 2 min. Another issue for this type of operation could be flight missions in areas where the GPS signal is not reliable or even not fully available. As a solution, UAV localization based on simultaneous localization and mapping (SLAM) [68] could be introduced. These algorithms need a rather powerful onboard computer on the UAV. However, due to relatively high UAV altitudes while scanning the area, it is expected that a GPS signal will be available. Scenarios of non-urban search and rescue missions usually involve various types of terrain that must be surveyed. Hilly and mountainous environments are common and must be considered when presenting a final system solution. Possible approaches using a tethered UAV on the receiving side or a multi-UAV approach were already discussed in Section 2.3. Finding the best solution is a future challenge. The research presented in this work showed that the core of a future system can be made from the presented modules. Although some other systems with data link modules have higher data rates in their specifications, as already stated, we sought to keep system's price relatively low. Since this part of the market and the related technological solutions are very dynamic [53; 64], some new and superior devices at reasonable prices could be available soon, thereby allowing improvements in the throughput or limitations in the sizes of images that can be transmitted. Another important factor is the preparation time for initial mission planning based on the newly collected images of the terrain. To shorten the period of constructing updated maps, which corresponds to the time needed for the UAV to fly over the area of interest, there are several possible approaches. The first is based on a two-stage flight of the fixed-wing UAV. In the first stage, the UAV would fly at a higher altitude and collect images of a large area with a lower resolution. These images would only be used to make a new map but could not be used for the detection of people due to insufficient resolution. In the second stage, the UAV would fly at lower altitudes, providing images with a resolution appropriate for detection. Another possible approach can be based on the periodical collecting of images and updating maps of areas known for frequent cases of SAR missions.