# Review of Photogrammetric and Lidar Applications of UAV
## 6 Discussion
### Discussion on Applications of UAVs
#### 6.2.2 Environmental Activities  
The agricultural industry uses UAVs to monitor crops. Agricultural terraces in China were mapped by the authors using a DJI Phantom 4 Pro UAV in [108]. For surveying agricultural fields of winter wheat, in [109], they used a DJI Matrice 100 UAV on which an Odroid XU4 lidar sensor was placed. Other authors, in [110], used DJI Matrice 210 UAV with a CMOS sensor in the Emilia-Romagna region in Northern Italy for mapping and monitoring in precise agriculture. The authors of [111] used a UAV hexacopter with a Canon EOS M color camera for soil and crop mapping in a maize field. As a result, they produced a digital surface model (DSM) of the bare soil and crops and a multispectral orthopicture. UAVs are also used in agriculture to control irrigation and pests using T16 UAV [112]. Some UAVs can perform fertilization and crop spraying [113]. UAVs allow farmers to carry out critical measures related to irrigation, crop disease [114], or unpredictable weather quickly, time-efficiently, and less labor-intensively. Both UAV photogrammetry and lidar methods are suitable for crop monitoring in the agricultural industry. Lidar is more suitable for crop volume estimation, and UAV photogrammetry is recommended for tracking crop development at different stages or maximizing crop productivity, which requires up-to-date, accurate, and georeferenced crop information. UAVs without any sensors are often used in agriculture. For more efficient work in the fields, UAV carriers are used for irrigation, fertilization, or pest control. In forestry, UAVs are used to map forest structures [63,64] and tree heights, assess tree pruning [60] and forest inventory [66], or peorm various other forestry function [115,116]. The study [64] used a multi-rotor GV1300 with a Velodyne Puck VLP-16 laser scanner to monitor forest structures in Eastern China. The authors of [63] observed the forest structure. They combined a Canon 550D digital SLR camera and an Ibeo LUX laser scanner on a multi-rotor Droidworx Skyjib oc octopoter. [PERSON] et al. [60] investigated tree crop feature extraction using a Parrot Sequia sensor mounted on a 3 DR Solo quadcopter. They assessed pruning effects on 189 trees in a lychee orchard southeast of Brisbane, Australia. In [66], forest inventory applications were investigated using a multi-rotor VTOL UAV OctoCopter Droidworx/Microopter AD-8 with an Ibeo LUX laser scanner. In [115], the authors conducted a young forestry trial survey within the central North Island of New Zealand using UAV laser scanning and SfM methods. A Lidar USA Snoopy V-series system with an integrated Riegl MiniVUX-1 scanner mounted on a DJI Matrice 600 Pro UAV was used for the UAV aerial scanning. The data reconstructed by the SfM method were captured using a DJI Phantom 4 Pro UAV with an integrated 1-inch 20 MP RGB camera. A DJI Matrice 210 UAV was used for forestry applications, on which four laser scanners--RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE--were mounted [116]. The collected data were used to demonstrate the effectiveness of deriving forest inventory attributes. For forest inventory and sustainable forest management regarding the provision of accurate estimates of forest attributes, UAV photogrammetry and lidar data are equally applicable. However, the difference is visible in the estimates of the vertical structure (the range of tree crown density), when ALS provides more accurate results than photogrammetry. UAV remote sensing is a suitable tool for monitoring changes in tree structure. Different flight heights can be used, but increasing flight height reduces the accuracy of the tree crown perimeter and area. Both UAV-based methods are reliable for the accurate measurement of the position, height, and width of trees. Applying UAVs to wild plant counts [117; 118; 119; 120] and animals [121; 122; 123] is a modern application. In [117], research was devoted to detecting the number of plants from UAV images present in a plantation.