Reducing systematic dome errors in digital elevation models through better UAV flight design

Abstract

It is well established that digital elevation models (DEMs) derived from unmanned aerial vehicle (UAV) images and processed by structure from motion may contain important systematic vertical errors arising from limitations in camera geometry modelling. Even when significant, such ‘dome’‐shaped errors can often remain unnoticed unless specific checks are conducted. Previous methods used to reduce these errors have involved: the addition of convergent images to supplement traditional vertical datasets, the usage of a higher number of ground control points, precise direct georeferencing techniques (RTK/PPK) or more refined camera pre‐calibration. This study confirms that specific UAV flight designs can significantly reduce dome errors, particularly those that have a higher number of tie points connecting distant images, and hence contribute to a strengthened photogrammetric network. A total of 22 flight designs were tested, including vertical, convergent, point of interest (POI), multiscale and mixed imagery. Flights were carried out over a 300 × 70 m2 flat test field area, where 143 ground points were accurately established. Three different UAVs and two commercial software packages were trialled, totalling 396 different tests. POI flight designs generated the smallest systematic errors. In contrast, vertical flight designs suffered from larger dome errors; unfortunately, a configuration that is ubiquitous and most often used. By using the POI flight design, the accuracy of DEMs will improve without the need to use more ground control or expensive RTK/PPK systems. Over flat terrain, the improvement is especially important in self‐calibration projects without (or with just a few) ground control points. Some improvement will also be observed on those projects using camera pre‐calibration or with stronger ground control. © 2020 John Wiley & Sons, Ltd.

Ground Control Point Distribution for Accurate Kilometre-Scale Topographic Mapping Using an RTK-GNSS Unmanned Aerial Vehicle and SfM Photogrammetry

“…However, their study area was limited to 300 × 70 m of flat topography. It is notable that errors arising from flight designs with crossed strips of convergent imagery, used in our Feshie investigation, yielded similar dome sizes to single and cross strip POI imagery [45]: Table 5. To avoid systematic errors for small survey areas, users should consider POI flight designs.…”

“…The results of this study coupled with Taddia's [41] demonstrate the applicability of a double grid flight plan for high resolution topographic survey of elongate geomorphic features, such as a coastline or a river corridor. However, Sanz-Ablanedo et al [45] and James et al [11] note that oblique images taken at an angle of 15 degrees or less are suboptimal due to the fact they are more likely to cause surface deformation errors such as doming effects. These studies also found surface deformation to be more pronounced when surveying low-relief topography.…”

“…These studies also found surface deformation to be more pronounced when surveying low-relief topography. Sanz-Ablanedo [45] show that Point Of Interest (POI) flights, where images are angled to always point towards the centre of the area of interest at ground level, generate the smallest systematic errors. However, their study area was limited to 300 × 70 m of flat topography.…”

“…Many previous studies have explored and have proposed mitigation for systematic errors, specifically doming, in geomorphic datasets via improved camera modelling [26,38]. Other approaches to reduce or eliminate systematic errors that have been considered include: the addition of oblique images in conjunction with a Nadiral datasets [41]; use of GCPs [45]; Direct Georeferencing techniques [42]; camera precalibration [46]; and, point of interest (POI) flight planning [45,47]. Of these approaches, POI is perhaps the most generally applicable but, for spatially extensive surveys along elongate corridors such as river valleys, double grids of convergent imagery (e.g., [41]), remains the most commonly used approach to acquiring images and warrants further error analysis.…”

“…Of these approaches, POI is perhaps the most generally applicable but, for spatially extensive surveys along elongate corridors such as river valleys, double grids of convergent imagery (e.g., [41]), remains the most commonly used approach to acquiring images and warrants further error analysis. As Sanz-Ablanedo et al [45] state, a limitation of the POI design is that the surveyed area cannot be more than four to five times the UAV flight height due to excessive convergence angles beyond this limit.…”