Improving Linear Projects Georeferencing to Create Digital Models Using UAV Imagery

Abstract

Global Positioning System (GPS) on Unmanned Aerial Vehicles (UAV) platform relies on Micro Electro Mechanical Systems (MEMS) technology with a precision of 10 m at shooting time at UAV camera stations positions. Nonetheless, obstacles to the GPS signal at the finest flight altitude can prevent accurate camera stations positions retrieval. In this research, three different georeferencing techniques were compared with geometric precision. The first is Direct Georeferencing (DG), which mainly depends on using Navigation GPS onboard without using any Ground Control Points (GCPs). The second is Indirect Georeferencing (IG), which mainly depends on three GCPs used to assist Aero-Triangulation (AT). The third is Modified technique depends on the same three GCPs used in the second method and enhanced location of camera stations usage of the Linear Relation Model (LR Model). The study area was in the south of the Moscow Region, Russia. Threeimaging strips have been taken using the DJI PHANTOM 4 PRO UAV. The accuracy assessment was carried out using image-derived coordinates and checkpoints (CPs) residuals. This study emphasizes that the Modified methodology using enhanced camera stations positions gave better accuracy than using the drone GPS camera stations positions.

Unmanned Aerial Vehicle Photogrammetric Products Accuracy Assessment: A Review

“…Additional research is also necessary to assess the accuracy of UAV-SfM in surveying applications, such as profiles, cross-sections, and volumetric analyses. Sensor resolution, image overlap, flight height, GCPsnumbers, distribution, and accuracy are the key determinants of DEM accuracy as well as Processing software also plays a significant role There is no published research on how the quantity of GCPs affects the accuracy of a UAV SfM analysis, and a number of results are either ambiguous or ambiguous, if not conflicting (Elsheshtawy & Gavrilova, 2021). Summary of the most recent articles is presented in Table 1.…”

Algorithms for improving the position determination of an UAV equipped with a single-frequency GPS receiver for low-altitude photogrammetry

“…GPS singlefrequency positioning has its direct impact on photogrammetric and remote sensing applications in UAV technology. The following research developments can be mentioned for these applications: the impact of GPS single-frequency positioning quality on the development of map products in professional photogrammetry [33], detection and localization of moving objects in aerial photographs taken from low altitude by UAVs [34], determination of exterior orientation elements in the process of digital aerotriangulation based on the use of data from a single-frequency GPS receiver mounted on a UAV [35], determination of approximate accuracy of control points for photogrammetric applications [36][37][38], detection and localization of a standing object in aerial photographs taken from low altitude by a UAV [39], analysis of the accuracy of the digital aerotriangulation process for alignment of a block of aerial photographs taken by a UAV [40,41], application of UAV technology in navigation in heavily and poorly urbanized areas [42], UAV positioning improvements for GPS/RADAR solution [43] and GPS/INS/LiDAR [44].…”

Simultaneous Localization and Mapping (SLAM) and Data Fusion in Unmanned Aerial Vehicles: Recent Advances and Challenges

“…The ground-truth trajectory is composed of multiple layers of different sizes that generate odometry edges from n − 1 to n [87]. The edges between layers add observation noise to each edge and reset the initial value of the reference position according to the noisy odometry data [159]. The accumulated error from the initial values of the noisy data approximates the true UAV position q x , q y , q z to respond to the image data for real-time SLAM, UAV tracking and landmark mapping [160].…”