Mapping and 3D modelling using quadrotor drone and GIS software

Abstract

Background The main obstacle for local and daily or weekly time-series mapping using very high-resolution satellite imagery is the high price and availability of data. These constraints are currently obtaining solutions in line with the development of improved UAV drone technology with a wider range and imaging sensors that can be used. Findings Research conducted using Inspire 2 quadcopter drones with RGB cameras, developing 3D models using photogrammetric and situation mapping uses geographic information systems. The drone used has advantages in a wider range of areas with adequate power support. The drone is also supported by a high-quality camera with dreadlocks for image stability, so it is suitable for use in mapping activities. Conclusions Using Google earth data at two separate locations as a benchmark for the accuracy of measurement of the area at three variations of flying height in taking pictures, the results obtained were 98.53% (98.68%), 95.2% (96.1%), and 94.4% (94.7%) for each altitude of 40, 80, and 100 m. The next research is to assess the results of the area for more objects from the land cover as well as for the more varied polygon area so that the reliability of the method can be used in general

Enhancing Scan Matching Algorithms via Genetic Programming for Supporting Big Moving Objects Tracking and Analysis in Emerging Environments

“…Future works will be directed towards the extension of the described hybrid algorithms to the 3-D case, and higher dimensions. Also, we plan to make our comprehensive framework suitable to the emerging big data trend (e.g., [8][9][10][22][23][24]), as to make it able of dealing with specific features of such innovative settings, like also dictated by some recent studies (e.g., [17][18][19]25]).…”

A Deep-Learning-Based Approach for Wheat Yellow Rust Disease Recognition from Unmanned Aerial Vehicle Images

“…We used an unmanned aerial vehicle (UAV) to collect wheat growth in the study area, mark the details of the different categories, and finally combine the field survey data with the stitched images of the wheat fields in Xigolou Village to complete the sample labeling in ArcMap 10.4.1 [ 25 ]. Three categories were marked: healthy wheat, wheat with stripe rust, and bare soil.…”

Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator

“…In recent years, Unmanned Aerial Vehicles (UAVs) have been developing toward miniaturization and intelligence, as a kind of aerial robot. In particular, due to their Vertical Take-Off and Landing (VTOL) and hovering capabilities, multi-rotor UAVs have been used in many military or civil fields, such as photography [ 1 ], mapping [ 2 ], agriculture [ 3 , 4 ], inspection [ 5 ], monitoring [ 6 , 7 ], and data collection [ 8 , 9 ]. However, these applications are utilized for observation and perception, which have no direct contact with the surrounding environment.…”