## 2 Survey for Outdoor Agricultural UAV Applications
### Remote Sensing
[58]} & An adaptive approach for \\ UAV-based pesticide spraying & & & & & & \\ in dynamic environments & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & & \\ \cline{1-1} & & & & & & & \\ \cline{1-1} & & & & & & & \\ \hline \multirow{5}{*}{12} & \multirow{5}{*}{[PERSON] et al. [59]} & Experimental evaluation of \\ UAV spraying for patch trees & & & & & & & & \\ of different shapes: Effects of \\ operational parameters on & & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \cline{1-1} & & & & & & \\ \hline \multirow{5}{*}{13} & \begin{tabular}{c} [PERSON], \\ [PERSON], [PERSON], \\ [PERSON], [PERSON], [PERSON] \\ and [PERSON] [80] \\ \end{tabular}  & Recognition of banana \\ & \begin{tabular}{c} [PERSON], [PERSON], [PERSON] \\ remote sensing \\ \end{tabular}  & 2020 & monitoring & 2020 & Panama & \begin{tabular}{c} Single \\ Bangana \\ \end{tabular}  & \ \begin{tabular}{c} Real-based multispectral camera sensor. The \\ UAV \\ \end{tabular}  & \begin{tabular}{c} Real-based multispectral camera sensor. The \\ slightly possible registration method used to establish the spatial relationships between infested \\ plants and non-infested plants on the known map. \\ \end{tabular}  \\ \hline
14 & \begin{tabular}{c} Wuet growth monitoring and \\ yield estimation based on \\ multi-rotor unmanned aerial \\ vehicle \\ \end{tabular}  & Crop & 2020 & Wheat & \begin{tabular}{c} Single \\ UAV \\ \end{tabular}  & \begin{tabular}{c} \begin{tabular}{c} \hline \hline \multicolumn{1}{c}{**No**} \\ \hline \hline \multirow{5}{*}{11} & \multirow{5}{*}{Fu et al. [60]} & Wheat growth monitoring and \\ yield estimation based on \\ multi-rotor unmanned aerial \\ vehicle \\ \end{tabular}  & Crop & 2020 & Wheat & \begin{tabular}{c} Single \\ UAV \\ \end{tabular}  & \begin{tabular}{c} \ \begin{tabular}{c} \hline \hline \multicolumn{1}{c}{**No**} \\ \hline \hline \end{tabular}  & \begin{tabular}{c} A computer-based system that controls a UAV for \\ precise pesticide deposition in the field and \\ metaheuristic route-planning method based on \\ particle swarm optimization, genetic algorithms, \\ hill-climbing and simulated annealing was evaluated \\ for autonomous adaptation of route changes. The \\ spray deposition was tracked by sensors, and the \\ system surrounded by wireless sensor networks \\ (WSN). The proposed system resulted in less \\ environmental damage, more precise changes in the route of flight and more accurate deposition of the \\ pesticide. \\ \end{tabular}  \\ \hline  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**No** & **Study** & **Study Name** & **Task** & **Year** & **Product/Focus** & \ \begin{tabular}{c} **UAV** \\ **Type** \\ \end{tabular}  & \begin{tabular}{c} **Purpose of Study** \\ \end{tabular}  \\ \hline  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**No** & **Study** & **Study Name** & **Task** & **Year** & **Product/Focus** & \ \begin{tabular}{c} **UAV** \\ **Type** \\ \end{tabular}  & \begin{tabular}{c} **Purpose of Study** \\ \end{tabular}  \\ \hline
25 & Elmokadem [71] & \begin{tabular}{c} Distributed Coverage Control \\ of Quadrotor Multi-UAV \\ Systems for Precision \\ Agriculture \\ \end{tabular}  & Field & 2019 & Region-based UAV & Multiple & \ \begin{tabular}{c} In this study, multiple UAV control strategies were presented for precision agriculture applications. \\ Using Vronet partitions, the positions of the UAVs \\ were determined, and collisions with each other \\ were prevented. Simulations were run in Azaude \\ and Robot Operating System (RGS) to show the performance of the proposed method. \\ \end{tabular}  & 2016 &
\begin{tabular}{c} A water deficit index (WWD) was obtained using images collected by a UAV. Using this index, the water stress of plants was measured. Both early and growing plant images were used to determine WJD.