## 2 Survey for Outdoor Agricultural UAV Applications  
This section addresses outdoor UAV studies carried out for precision agriculture for different missions. UAV-based precision agriculture studies include applications such as crop monitoring, mapping, irrigation, etc. Useful information about the crop can be obtained with images acquired through the UAV camera. [PERSON] et al. [30] evaluated the accuracy, spatial and temporal consistency and precision of six different vegetation indices (CIVE, ExG, ExGR, Woebbecke index, NGRDI and VEG) in a wheat crop using images from a low-cost camera attached to a UAV. With ExG and VEG indices, it achieved the best accuracy in vegetation fraction mapping with values of 87.73-91.99% at a height of 30 m and 83.74-87.82% at a height of 60 m. With this study, it was proven that a low-cost camera UAV can be used in precision agriculture applications such as weed management. According to [PERSON] et al. [31], accurate mapping of individual plants with UAV images is difficult, given the large variations in sizes and geometries and the distribution of plants. In this context, the authors used fraileljones plants as an example andproposed the Scale Sequence Residual U-Net (SS Res U-Net) semantic segmentation model. The proposed semantic method provided a more successful classification compared to FCN, standard U-Net, Res U-Net and MS Res U-Net methods. [PERSON] et al. [32] used both multispectral UAV and WorldView-3 images to quickly and consistently assess macadamia tree status with remotely sensed images. In the application for three different areas, excellent, good, moderate, fair and poor classes were used for trees, and the classification algorithm was a random forest classifier. Tree condition was more successfully predicted with WorldView-3 images. Numerous examples of previous studies can be cited, as above. However, the number of these studies using UAVs for agricultural purposes is quite high. Therefore, grouping these studies according to their tasks provides more efficient information to the reader. For this reason, in this study, recent state-of-the-art studies on the use of UAVs in precision agriculture obtained from the Web of Science are investigated. These journals have high impact factors in the Web of Science. Previous studies have generally aimed to perform an outdoor agricultural task with UAVs. Table 1 provides information about the tasks, years, agricultural product handled, type of UAV and purpose of these recent studies. An article can contain different tasks at the same time. For example, most of the mapping articles also involve crop monitoring and remote sensing. When Table 1 is examined, it is seen that UAV solutions are actively explored in agriculture, and UAV missions performed outdoors are very diverse. The definition of these tasks can be generalized as in Table 1, although the applications are in different areas and for different crops. Table 1 shows that UAVs performing agricultural tasks have recently been widely published in Web of Science indexed journals. This situation is discussed in more detail in the study by [PERSON], [PERSON], [PERSON] and [PERSON] [23]. Therefore, it is clear that the interest in UAVs in agriculture has increased in recent years and that UAVs will play a major role in the future of agriculture [25]. The previous studies in Table 1 show that different crops can benefit from the capabilities of the UAV, such as data collection and flexible mobility; that is, a large gain in production and yield can be achieved with the UAV. Most agricultural products require constant control, and sometimes, changes that are invisible to the human eye can occur in crops. The UAV is still a very important alternative for many crops, especially for addressing such problems. For this reason, it is expected that studies similar to those in Table 1 will be applied frequently in the future. A more detailed description of UAV missions that mostly have applications is given below.