# Review of Photogrammetric and Lidar Applications of UAV
## 6 Discussion
### High-Frequency Keyword Analysis  
For analysis of scientific studies filling the references of this review, 156 different research publications indexed in the Web of Science (WOS) were chosen. In total, 538 keywords were obtained, which were subject to further processing. The main themes of the analysis of the common occurrence of the keyword were the use and application of UAVs. The results of the systematic analysis of keywords helped us better understand the development and further direction of research in this field. With this approach, we wanted to identify the power of links between keywords and the number of analyzed documents. The same approach was also used by the authors [PERSON] et al. [204]. Through the Vosviewer interface, the identified network of the common occurrence of keywords was divided into eight primary clusters (Figure 4). Each keyword in Figure 4 was visualized through one node using a colored visualization of circle symbols.  
Figure 4: Co-occurrence network of high-frequency keywords with colored clusters.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Software** & **References** \\ \hline Pix4D & [77; 79; 82; 104; 107; 137; 168; 177] \\ \hline Agisoft Photoscan & [63; 74; 101; 106; 142; 165] \\ \hline Agisoft MetaShape & [58; 61; 62; 74] \\ \hline Autodesk, Autodesk ReCap & [104; 106] \\ \hline COLMAP & [106] \\ \hline LiDAR360 & [64; 106] \\ \hline QGIS & [137] \\ \hline RiSCAN PRO & [101] \\ \hline \hline \end{tabular}
\end{table}
Table 12: Classification by software.  
The size of the node itself varies. It is expressed by a direct linear dependence on the number of keywords (larger symbols and text mean a higher occurrence of keywords). The choice of selection condition to recognize the keywords with a frequency of more than three appearances (threshold) was set in our study. The interconnection between two nodes creates/indicates a relationship between the specific keywords (Table 13).  
The processing interface identified 28 keywords (256 occurrences and a total link strength of 440 on UAVs). The results show that it is probable that there are other research areas related to the central term UAV. This result presents the conclusion that reflects the relationship between every important node, theme, and keyword. Circular nodes such as Photogrammetry, SfM, lidar, and Remote Sensing in UAV binding are the most significant and co-occurring, presenting a possible further direction in this research field.  
\begin{table}
\begin{tabular}{c c c c} \hline
**ID Number** & **Keywords** & **Occurences** & **Total Link Strength** \\ \hline
1 & uav & 89 & 112 \\ \hline
2 & photogrammetry & 21 & 44 \\ \hline
3 & sfm & 18 & 41 \\ \hline
4 & lidar & 17 & 27 \\ \hline
5 & remote sensing & 14 & 25 \\ \hline
6 & point cloud & 10 & 17 \\ \hline
7 & drone & 8 & 13 \\ \hline
8 & dem & 6 & 13 \\ \hline
9 & tls & 6 & 17 \\ \hline
10 & monitoring & 5 & 10 \\ \hline
11 & uav photogrammetry & 5 & 6 \\ \hline
12 & accuracy & 4 & 10 \\ \hline
13 & cadastral boundaries & 4 & 10 \\ \hline
14 & cultural heritage & 4 & 8 \\ \hline
15 & deep learning & 4 & 6 \\ \hline
16 & laser scanning & 4 & 8 \\ \hline
17 & precision agriculture & 4 & 8 \\ \hline
18 & dsm & 3 & 5 \\ \hline
19 & forest inventory & 3 & 6 \\ \hline
20 & gis & 3 & 8 \\ \hline
21 & image processing & 3 & 5 \\ \hline
22 & image segmentation & 3 & 8 \\ \hline
23 & landslide & 3 & 13 \\ \hline
24 & mapping & 3 & 4 \\ \hline
25 & orthophoto & 3 & 9 \\ \hline
26 & sensors & 3 & 1 \\ \hline
27 & tree height & 3 & 5 \\ \hline
28 & uav remote sensing & 3 & 1 \\ \hline \end{tabular}
\end{table}
Table 13: The keywords information of all clusters.