scholarly journals Determining the Suitable Number of Ground Control Points for UAS Images Georeferencing by Varying Number and Spatial Distribution

2020 ◽  
Vol 12 (5) ◽  
pp. 876 ◽  
Author(s):  
Valeria-Ersilia Oniga ◽  
Ana-Ioana Breaban ◽  
Norbert Pfeifer ◽  
Constantin Chirila

Currently, products that are obtained by Unmanned Aerial Systems (UAS) image processing based on structure-from-motion photogrammetry (SfM) are being investigated for use in high precision projects. Independent of the georeferencing process being done directly or indirectly, Ground Control Points (GCPs) are needed to increase the accuracy of the obtained products. A minimum of three GCPs is required to bring the results into a desired coordinate system through the indirect georeferencing process, but it is well known that increasing the number of GCPs will lead to a higher accuracy of the final results. The aim of this study is to find the suitable number of GCPs to derive high precision results and what is the effect of GCPs systematic or stratified random distribution on the accuracy of the georeferencing process and the final products, respectively. The case study involves an urban area of about 1 ha that was photographed with a low-cost UAS, namely, the DJI Phantom 3 Standard, at 28 m above ground. The camera was oriented in a nadiral position and 300 points were measured using a total station in a local coordinate system. The UAS images were processed using the 3DF Zephyr software performing a full BBA with a variable number of GCPs i.e., from four up to 150, while the number and the spatial location of check points (ChPs) was kept constant i.e., 150 for each independent distribution. In addition, the systematic and stratified random distribution of GCPs and ChPs spatial positions was analysed. Furthermore, the point clouds and the mesh surfaces that were automatically derived were compared with a terrestrial laser scanner (TLS) point cloud while also considering three test areas: two inside the area defined by GCPs and one outside the area. The results expressed a clear overview of the number of GCPs needed for the indirect georeferencing process with minimum influence on the final results. The RMSE can be reduced down to 50% when switching from four to 20 GCPs, whereas a higher number of GCPs only slightly improves the results.

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
Margaret Kalacska ◽  
Oliver Lucanus ◽  
J. Pablo Arroyo-Mora ◽  
Étienne Laliberté ◽  
Kathryn Elmer ◽  
...  

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.


Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 15 ◽  
Author(s):  
Salvatore Manfreda ◽  
Petr Dvorak ◽  
Jana Mullerova ◽  
Sorin Herban ◽  
Pietro Vuono ◽  
...  

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.


2019 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze

Abstract. High quality 3D point clouds generated from repeat camera-equipped unmanned aerial vehicle (UAV) surveys are increasingly being used to investigate landscape changes and geomorphic processes. Point cloud quality can be expressed as accuracy in a comparative (i.e., from survey to survey) and absolute (between survey and an external reference system) sense. Here we present a simple workflow for calculating pairs or sets of point clouds with a high comparative accuracy, without the need for ground control points or a dGPS equipped UAV. We demonstrate the efficacy of the new approach using a consumer-grade UAV in two contrasting landscapes: the coastal cliffs on the Island of Rügen, Germany, and the tectonically active Daan River gorge in Taiwan. Compared to a standard approach using ground control points, our workflow results in a nearly identical distribution of measured changes. Compared to a standard approach without ground control, our workflow reduces the level of change detection from several meters to 10–15 cm. This approach enables robust change detection using UAVs in settings where ground control is not possible.


2019 ◽  
Vol 7 (4) ◽  
pp. 1009-1017 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze

Abstract. High-quality 3-D point clouds generated from repeat camera-equipped unmanned aerial vehicle (UAV) surveys are increasingly being used to investigate landscape changes and geomorphic processes. Point cloud quality can be expressed as accuracy in a comparative (i.e., from survey to survey) and absolute (between survey and an external reference system) sense. Here we present a simple workflow for calculating pairs or sets of point clouds with a high comparative accuracy, without the need for ground control points or a differential GNSS (dGNSS)-equipped UAV. The method is based on the automated detection of common tie points in stable portions of the survey area. We demonstrate the efficacy of the new approach using a consumer-grade UAV in two contrasting landscapes: the coastal cliffs on the island of Rügen, Germany, and the tectonically active Daan River gorge in Taiwan. Compared to a standard approach using ground control points, our workflow results in a nearly identical distribution of measured changes. Compared to a standard approach without ground control, our workflow reduces the level of change detection from several meters to 10–15 cm. This approach enables robust change detection using UAVs in settings where ground control is not feasible.


Author(s):  
Salvatore Manfreda ◽  
Petr Dvorak ◽  
Jana Mullerova ◽  
Sorin Herban ◽  
Pietro Vuono ◽  
...  

Small unmanned aerial systems (UAS) represent a cost-effective strategy for topographic surveys. These low-cost drones can provide useful information for 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 flight mode and proper distribution of ground control points is required. To this end a commercial drone has been adopted to monitor a small earthen dam using different combinations of flight configurations and adopting a variable number of ground control points (GCPs). Results highlighted that both choice and combination of flight plans can reduce the relative error of the 3D model up to a few meters without the need of including GCPs. The use of GCPs allows the quality of topographic survey to be greatly improved, reducing error to the order of a few centimeters. In particular, the combined use of images extracted from two flights, one with a camera mounted at nadir and the second with a 20° angle, proves extremely beneficial to increase the overall accuracy of the 3D model and especially of the vertical precision.


Author(s):  
P. Fanta-Jende ◽  
F. Nex ◽  
M. Gerke ◽  
J. Lijnen ◽  
G. Vosselman

<p><strong>Abstract.</strong> Mobile mapping enables highly accurate as well as high-resolution image data capture at low cost and high speed. As a terrestrial acquisition technique predominately employed in urban, and thus built-up areas, non-line-of-sight and multipath effects challenge its absolute positioning capabilities provided by GNSS. In conjunction with IMU drift, the platform’s trajectory has an unknown accuracy, which influences the quality of the data product. By employing a highly accurate co-registration technique for identifying tie correspondences between mobile mapping images and aerial nadir as well as aerial oblique images, reliable ground control can be introduced into an adjustment solution. We exemplify the performance of our registration results by showcasing adjusted mobile mapping trajectories in four different test areas, each with about 100 consecutive recording locations (approx. 500&amp;thinsp;m length) in the city centre of Rotterdam, The Netherlands. The mobile mapping data has been adjusted in different configurations, i.e. with nadir or oblique aerial correspondences only and if possible in conjunction. To compare the horizontal as well as the vertical accuracy before and after the respective adjustments, more than 30 ground control points were surveyed for these experiments. In general, the aim of our technique is not only to correct mobile mapping trajectories in an automated fashion but also to verify their accuracy without the need to acquire ground control points. In most of our test cases, the overall accuracy of the mobile mapping image positions in the trajectory could be improved. Depending on the test area, an RMSE in 3D between 15 and 21&amp;thinsp;cm and an RMSE in 2D between 11 and 18&amp;thinsp;cm is achievable.</p>


Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 352 ◽  
Author(s):  
Valeria-Ersilia Oniga ◽  
Ana-Ioana Breaban ◽  
Florian Statescu

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 49 ◽  
Author(s):  
Jae Jin Yu ◽  
Dong Woo Kim ◽  
Eun Jung Lee ◽  
Seung Woo Son

The rapid development of drone technologies, such as unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs), has led to the widespread application of three-dimensional (3D) point clouds and digital surface models (DSMs). Due to the number of UAS technology applications across many fields, studies on the verification of the accuracy of image processing results have increased. In previous studies, the optimal number of ground control points (GCPs) was determined for a specific area of a study site by increasing or decreasing the amount of GCPs. However, these studies were mainly conducted in a single study site, and the results were not compared with those from various study sites. In this study, to determine the optimal number of GCPs for modeling multiple areas, the accuracy of 3D point clouds and DSMs were analyzed in three study sites with different areas according to the number of GCPs. The results showed that the optimal number of GCPs was 12 for small and medium sites (7 and 39 ha) and 18 for the large sites (342 ha) based on the overall accuracy. If these results are used for UAV image processing in the future, accurate modeling will be possible with minimal effort in GCPs.


2021 ◽  
Author(s):  
Zachary M Miller ◽  
Joseph Hupy ◽  
Aishwarya Chandrasekaran ◽  
Guofan Shao ◽  
Songlin Fei

Abstract Unmanned Aerial Systems (UAS) serve as an excellent remote-sensing platform to fulfill an aerial imagery data collection niche previously unattainable in forestry by satellites and manned aircraft. However, for UAS-derived data to be spatially representative, a precise network of ground control points (GCP) is often required, which can be tedious and limit the logistical benefits of UAS rapid deployment capabilities, especially in densely forested areas. Therefore, methods for efficient data collection without GCPs are highly desired in UAS remote sensing. Here, we demonstrate the use of postprocessing kinematic (PPK) technology to obtain subcentimeter precision in datasets of forested areas without the need for placing GCPs. We evaluated two key measures, positional variability and time efficiency, of the PPK technology by comparing them to traditional GCP methods. Results show that PPK displays consistently higher positional precision than traditional GCP approaches. Moreover, PPK surveys and processing take less time to complete than traditional GCP methods and require fewer logistical steps, especially in image acquisition. The time and resource savings with PPK as compared to GCP processing are undeniable. We conclude that PPK technology provides a practical means to produce precise aerial forest surveys. Study Implications Unmanned Aerial Systems (UAS) have enormous potential for lowering costs and streamlining practices in the forestry management and research community. Despite this potential, however, UAS forestry applications have been limited in scope and precision because of a reliance on using ground-based GPS technology to survey ground control points (GCP), which are time intensive and require an open view of the sky. Such a need for a ground-based GCP survey, along with forest canopy serving to limit and scatter incoming GPS signals, diminishes the potential for rapid deployment and precision mapping offered by UAS. Fortunately, Postprocessing-Kinematic (PPK) GPS technology lowers these barriers by providing the means to seamlessly gather highly precise UAS imagery without needing to conduct time-intensive ground-based surveys. This study compares the precision and time-effectiveness between traditional GCP marker surveys and PPK correction methods.


Author(s):  
T. J. B. Dewez

Coastal cliff collapse hazard assessment requires measuring cliff face topography at regular intervals. Terrestrial laser scanner techniques have proven useful so far but are expensive to use either through purchasing the equipment or through survey subcontracting. In addition, terrestrial laser surveys take time which is sometimes incompatible with the time during with the beach is accessible at low-tide. By comparison, structure from motion techniques (SFM) are much less costly to implement, and if airborne, acquisition of several kilometers of coastline can be done in a matter of minutes. In this paper, the potential of GPS-tagged oblique airborne photographs and SFM techniques is examined to reconstruct chalk cliff dense 3D point clouds without Ground Control Points (GCP). The focus is put on comparing the relative 3D point of views reconstructed by Visual SFM with their synchronous Solmeta Geotagger Pro2 GPS locations using robust estimators. With a set of 568 oblique photos, shot from the open door of an airplane with a triplet of synchronized Nikon D7000, GPS and SFM-determined view point coordinates converge to X: ±31.5 m; Y: ±39.7 m; Z: ±13.0 m (LE66). Uncertainty in GPS position affects the model scale, angular attitude of the reference frame (the shoreline ends up tilted by 2&deg;) and absolute positioning. Ground Control Points cannot be avoided to orient such models.


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