# Review of Photogrammetric and Lidar Applications of UAV
## 6 Discussion
### Discussion on Applications of UAVs
#### 6.2.1 Mapping and Surveying
UAV technology is used as an alternative to speed up processes in the field of real estate cadastre. The local investigation of ownership relations and measurement of omitted objects is still necessary. The authors of the articles [94; 95; 96; 97; 98; 99; 100] have devoted themselves to research in the industrial sector. The article [94] dealt with using UAVs to calculate the volume of gravel reserves. This volume was surveyed using a Leica TS06 total station and a DJI Mavic UAV. A total of 128 images were acquired at a height of 50 m AGL. After processing, DEM and TIN models were generated. A volume of 2686.3 m\({}^{3}\) was calculated using the UAV, and a volume of 2830.7 m\({}^{3}\) was calculated using the total station. In the article [95], the authors wanted to create a model to generate an optimal flight plan for UAVs. This model would manage safety in the oil and gas industry. The article [96] reviews UAV platforms and sensor systems designed for the oil industry and environmental monitoring. The described UAVs are divided into different categories, such as fixed-wing UAVs and rotary-wing UAVs. The brands and types of UAVs such as Mavinci Sirius, Trimble Gatewing X100, Aibot X6, and Matrice200 are listed. Sensors such as gas detectors, radar, lidar, and thermal infrared (IR) cameras are also listed. The brands of these sensors, Yuneec CGOETUS, Optris PI 450, FLIR Quark 640, ICI Mirage HC, Workswell GIS-320, MosaicMill Rikola, HySpex Mjolnir VS-620, Riegl VUX-1 UAV, VelodyneHDL-32 E, LeddartechVu8, and others, are also listed. The authors in the article also mention the UAV application, which they describe uniquely. The research in [97] discusses the design of a two-mode network analysis framework to quantify the spillover effects of UAV technology in various industries using U.S. Patent and Trademark Office patent citation data. In [98], the authors studied the fog-assisted computing problem of UAV in Industry 4.0 smart factories. The simulation results show that the proposed online algorithm can achieve near-optimal task allocation with an optimality difference of no more than 7.5% compared to offline. The authors of [99] discussed research on monitoring CO\({}_{2}\) gas levels in smart factories because CO\({}_{2}\) harms humans. According to the study, the UAV would securely transmit the sensor data to the MEC server to analyze them and make an automatic decision. The result shows of the analysis show the successful monitoring and detection of CO\({}_{2}\) levels in factories. The research in [100] deals with imaging complex sites and areas in sugarcane factories in San Joaquin and the Aguila aqueduct in Spain. A DJI Mavic Pro Platinum with a 13 Mpix sensor was used for the imaging. According to the results, UAV technology is more accurate, time-saving, and suitable than standard methods. UAVs offer great potential for creating mathematical models in the oil and gas industry. Among other things, gaps and open issues were defined for this technology, which are connected to the field of the detection of oil spills at sea and oil spill detection, monitoring of gas pipelines, sensing of gas emissions, remote control of equipment, exploration of deposits and offshore oil spill detection, oil leakage detection, pipeline monitoring, gas emission sensing, remote facility inspection, and petroleum exploration. The authors have discussed UAV applications in architecture in [101; 102; 103; 104; 105; 106; 107]. The article [101] focused on 3D model and texture generation using a ground-based laser scanner and UAV. The object investigated was the Torre Pelosa watchtower, located in the city of Bari, Italy. The TLS RIEGL VZ-400 scanner, with maximal scanspeed of 122,000 points/sec, was applied. An external Nikon D700 camera with 10 Mpix quality was connected to the scanner. The UAV Microgeo's AeroMax600 with a 12 Mpix Canon S100 camera sensor was used. For indirect georeferencing, GCP was used. The image processing method was SfM.