# Review of Photogrammetric and Lidar Applications of UAV
## 5 Selected UAV Sensors and Their Applications  
Nowadays, there are a large number of UAVs that are specific in terms of their shape, mass, size, height, or range. Tables 6 and 7 show different types of UAV carriers according to specific parameters during measurement, under different conditions, and in different parts of the world with high-quality results. Data obtained from the selected papers are graphically presented in Figure 2. The result is a graphic representation of the main parameters obtained using the selected sensors. The graph shows the comparison of GSD, RMSE, and flight height for chosen sensors. The best results according to GSD were obtained when measured with the DJI Phantom 4 [58], DJI Phantom 4 PRO [61], and Droidworx Skyjib Oktokopter [63], where the GSD achieves an accuracy of less than 2 cm. On the other hand, according to RMSE, the best accuracy is achieved in measurements with the DJI Phantom 4 [58], DJI Inspire 2 [62], GV1300 [64], and Baloon [67], where the RMSE accuracy does not exceed 2 cm. \begin{table}
\begin{tabular}{c c c c c c} \hline
**UAV** & **Camera** & **Flight Height (m)** & **GSD (m)** & **RMSE (m)** & **References** \\ \hline DJI Phantom 4 Pro & 1\({}^{\prime\prime}\) CMOS & 35 & 0.010 & 0.011 & [58] \\ \hline DJI Phantom 4 Pro & Parrot Sequoia & 50 & 0.040 & 0.370 & [59] \\ \hline
3 DR Solo & Parrot Sequoia & 50 & 0.065 & 0.250 & [60] \\ \hline DJI Phantom 4 RTK & 1\({}^{\prime\prime}\) CMOS & 45 & 0.018 & 0.080 & [61] \\ \hline DJI Inspire 2 & Zenmuse X5S RGB & 120 & 0.023 & 0.020 & [62] \\ \hline Droidworx Skyjib & & & & & \\ Oktokopter & Canon 550D & 30 & 0.010 & 0.140 & [63] \\ \hline \end{tabular}
\end{table} 
Table 6: Specific parameters of measurement with UAV equipped with a camera. \begin{table}
\begin{tabular}{c c c c c c} \hline
**UAV** & **Lidar** & **Flight Height (m)** & **GSD (m)** & **RMSE (m)** & **References** \\ \hline GV1300 & Velodyne Puck VLP-16 & 80 & 0.141 & 0.012 & [64] \\ \hline Droidworx Skyjib Oktokopter & Ibeo LUX & 30 & 0.076 & 0.420 & [63] \\ \hline RIEGL RicCOPTER & VUX-1 UAV & 55 & 0.024 & 0.750 & [65] \\ \hline Oktokopter Droidworx/Mikrokopter & Ibeo LUX & 50 & 0.141 & 0.340 & [66] \\ \hline Baloon & Velodyne HDL-32E & 25 & 0.032 & 0.015 & [67] \\ \hline \end{tabular}
\end{table} 
Table 7: Specific parameters of measurement with UAV equipped with lidar. Ground Sampling Distance is the size of the image pixel projected in object space. The larger the GSD size, the smaller the spatial resolution of the image. UAVs have GSDs ranging from 1 to 5 cm. GSD affects, but does not define, the accuracy of the measurement. Horizontal accuracy can often be less than the GSD, but vertical accuracy is usually significantly worse. However, acquired high-quality image grids that are well supported by GCP points can achieve vertical errors less than the GSD. The size of the GSD is related to the choice of camera (e.g., focal length and pixel spacing) and flight altitude [16]. Root Mean Square Error is required as a global quality indicator that indicates the accuracy value. It is generally reported that the smaller the RMSE value, the more accurate the measurement. It is the distance between the input position of the GCP ground control point and the retransformed position for the same GCP. It states how closely the retransformed location matches the desired output point location [16]. In [58], the authors investigated and monitored the development of erosion, morphological changes in talus cones, and the dynamics of the movement of rock blocks and talus cones between individual stages of measurement in the Small Cold Valey in the High Tatras in the north of Slovakia at an altitude of 1600 m (AMSL). The total area of investigation was 5000 m\({}^{2}\). Geodetic and photogrammetric methods were used to document the current state of the site and generate DEM. The survey aimed to capture the morphology of the terrain in high level of detail.