Assessing the Accuracy of Digital Surface Models Derived from Optical Imagery Acquired with Unmanned Aerial Systems

Abstract

Small unmanned aerial systems (UASs) equipped with an optical camera are a cost-effective strategy for topographic surveys. These low-cost UASs can provide useful information for three-dimensional (3D) reconstruction even if they are equipped with a low-quality navigation system. To ensure the production of high-quality topographic models, careful consideration of the flight mode and proper distribution of ground control points are required. To this end, a commercial UAS was adopted to monitor a small earthen dam using different combinations of flight configurations and by adopting a variable number of ground control points (GCPs). The results highlight that optimization of both the choice and combination of flight plans can reduce the relative error of the 3D model to within two meters without the need to include GCPs. However, the use of GCPs greatly improved the quality of the topographic survey, reducing error to the order of a few centimeters. The combined use of images extracted from two flights, one with a camera mounted at nadir and the second with a 20° angle, was found to be beneficial for increasing the overall accuracy of the 3D model and especially the vertical precision.

Uav-Based Cadastral Mapping: An Assessment of the Impact of Flight Parameters and Ground Truth Measurements on the Absolute Accuracy of Derived Orthoimages

“…As the inclusion of perpendicular strips has proven to increase the quality of the camera self-calibration (Gerke and Przybilla, 2016) All flight missions were processed with three ground truthing scenarios including 0 GCPs, 1 GCP and 6 GCPs and remaining reference points as CP (see table 2last column). This setup provides insights on the of f as particularly for small image blocks in a rectangular shape, six GCPs covering four corner points and two centrally located points, geometric accuracies stabilize (Manfreda et al, 2019). The other flight mission with setup ii) were carried out with varying numbers of GCPs and a regular flight pattern.…”

Comparing sUAS Photogrammetrically-Derived Point Clouds with GNSS Measurements and Terrestrial Laser Scanning for Topographic Mapping

“…The combination of several or a single factor may influence the overall accuracy. For example, Manfreda et al [32] evaluated different flight combinations and the distribution and number of ground control points (GCPs) to reduce the error of the 3D model for monitoring a dam. However, their study sample is limited to evaluating sixteen checkpoints and not several thousands of points as those found in point clouds, which is necessary to deeply understand the behavior of the derived 3D model.…”

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“…To follow, the impact of the number of GCPs on the geometric quality of the derived photogrammetric products was also studied. Several criteria discussed in many scientific works allow the assessment of the model quality in terms of its 3D coordinates accuracy (Manfreda et al 2019). Commonly, these checks are based on comparing some estimated ground-points by SfM-algorithms and the same points measured with high accuracy, i.e.…”

“…Different factors may affect the precision of UAV-derived data, such as flight parameters, image quality, processing software, the morphology of the studied area and, above all, the modalities of georeferencing. The ordinary use of Ground Control Points (GCPs) greatly improves the precision of SfM products, but at the same time their collection represents a laborious and time-intensive part of UAV campaigns (Manfreda et al 2019). For this reason, several works in literature have been focused on finding an effective and sustainable GCPs-survey strategy to limit costs and work times (Agüera-Vega, Carvajal-Ramírez, and Martínez-Carricondo 2017; Rangel, Gonçalves, and Pérez 2018; Sanz-Ablanedo et al 2018; Skarlatos et al 2013).…”

“…It has already been proved that at least three GCPs are necessary for the software platform to take advantage of such information, but the minimum number of GCPs needed to produce an optimal quality is still uncertain. On this topic, (Manfreda et al 2019) proposes a useful table to review the accuracy values obtained by varying the GCPs number extrapolated by different UAV-works. (James et al 2017) recommends a minimum of five GCPs, combined with an accurate calibration of the camera, for reliable achievements.…”