Evaluating horizontal positional accuracy of low-cost UAV orthomosaics over forest terrain using ground control points extracted from different sources

2017 ◽  
Author(s):  
Giorgos Mallinis ◽  
Petros Patias ◽  
Fotis Giagkas ◽  
Charalampos Georgiadis ◽  
Dimitris Kaimaris ◽  
...  
Keyword(s):  
Low Cost ◽  
Ground Control ◽  
Control Points ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Different Sources

scholarly journals Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
Margaret Kalacska ◽  
Oliver Lucanus ◽  
J. Pablo Arroyo-Mora ◽  
Étienne Laliberté ◽  
Kathryn Elmer ◽  
...  
Keyword(s):  
Low Cost ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Model Errors ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Digital Elevation ◽  
High Level ◽  
Aerial Systems

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.

scholarly journals THE INFLUENCE OF GROUND CONTROL POINTS CONFIGURATION AND CAMERA CALIBRATION FOR DTM AND ORTHOMOSAIC GENERATION USING IMAGERY OBTAINED FROM A LOW-COST UAV

2020 ◽  
Vol V-1-2020 ◽  
pp. 239-244
Author(s):  
M. V. Y. Garcia ◽  
H. C. Oliveira
Keyword(s):  
Low Cost ◽  
Digital Terrain Model ◽  
Flying Height ◽  
Ground Control ◽  
Optimum Number ◽  
Control Points ◽  
Digital Products ◽  
Positional Accuracy ◽  
Terrain Model ◽  
Ground Control Points

Abstract. Technological improvement of Unmanned Aerial Vehicles (UAVs) and computer vision algorithms, such as Structured-from-Motion (SfM) and Multi-view Stereo (MVS) have provided the possibility for high-resolution mapping and high-density point cloud generation using low-cost equipment and sensors. Orthomosaics and Digital Terrain Model (DTM) are the main digital products considering mapping purposes. Their quality is directly related to the sensors boarded on the UAV and data processing. Ground Control Points (GCPs) are used in the process of indirect georeferencing and also to model the lens distortions. The number of GCPs used in this process affects the positional accuracy of the final products. This study aims to determine the optimum number of GCPs to achieve high accuracy orthomosaics and DTM. To obtain this optimum number, an area of 3.85 ha was mapped with a low-cost UAV DJI Phantom 4 Advanced at 31 m flying height, lateral and longitudinal overlap of 90% and 80%, respectively, and using 22 checkpoints for quality assessment. For the experiments, different configuration were used both for the number of GCPs and for the use of self-calibration process or pre-calibrated camera IOP (Interior Orientation Parameters). The results show that for the flight configuration used in this work and for the mentioned UAV, a total of 5 GCPs, with pre-calibrated camera IOP, yields an accuracy of 0.023 m for X, 0.031 m for Y and 0.033 m for Z.

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

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 15 ◽  
Author(s):  
Salvatore Manfreda ◽  
Petr Dvorak ◽  
Jana Mullerova ◽  
Sorin Herban ◽  
Pietro Vuono ◽  
...  
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Careful Consideration ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Earthen Dam ◽  
Ground Control Points ◽  
Aerial Systems

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.

scholarly journals CORRECTION OF MOBILE MAPPING TRAJECTORIES IN GNSS-DENIED ENVIRONMENTS USING AERIAL NADIR AND AERIAL OBLIQUE IMAGES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1649-1654
Author(s):  
P. Fanta-Jende ◽  
F. Nex ◽  
M. Gerke ◽  
J. Lijnen ◽  
G. Vosselman
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Image Data ◽  
City Centre ◽  
Ground Control ◽  
Control Points ◽  
Mobile Mapping ◽  
Ground Control Points ◽  
Before And After ◽  
Oblique Images

<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>

scholarly journals FISHEYE LENS IMAGE CAPTURE ANALYSIS FOR INDOOR 3D RECONSTRUCTION AND EVALUATION

2019 ◽  
Vol XLII-2/W17 ◽  
pp. 179-186 ◽  
Author(s):  
H. A. León-Vega ◽  
M. I. Rodríguez-Laitón
Keyword(s):  
Low Cost ◽  
Ground Control ◽  
Control Points ◽  
Digital Cameras ◽  
Image Capture ◽  
Fisheye Lens ◽  
Ground Control Points ◽  
Wide Range ◽  
Lens Image ◽  
Made In

Abstract. The following article has as its purpose to solve a series of questions related to the acquisition of fisheye lens images made in the Benchmark FINE, making use of this data and images to generate a reconstruction to the tower of the chapel of San Vigilio in 3D using SFM photogrammetry and its application methodologies using low-cost instruments and sensors such as non-metric digital cameras. The fisheye lens has a wide range of focus and field of view that makes it possible to capture a scene with a limited number of images more quickly and efficiently. An analysis is intended to be carried out on the basis of the results obtained by assessing their accuracy and quality to determine the feasibility in the proposed initial use for the assessment of spaces difficult access by maintaining geometry without distances, scale, defined orientation in images, or ground control points (GPCs).

scholarly journals Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points

2019 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
3D Point Clouds ◽  
Tectonically Active ◽  
Comparative Accuracy

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.

scholarly journals Smartphone: An alternative to ground control points for orienting virtual outcrop models and assessing their quality

Geosphere ◽  
2019 ◽  
Vol 15 (6) ◽  
pp. 2043-2052 ◽  
Author(s):  
Stefano Tavani ◽  
Amerigo Corradetti ◽  
Pablo Granado ◽  
Marco Snidero ◽  
Thomas D. Seers ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Image Data ◽  
Ground Control ◽  
Control Points ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Test Models ◽  
Surface Reconstructions ◽  
The Cost ◽  
Range Error

Abstract The application of structure from motion–multiview stereo (SfM-MVS) photogrammetry to map metric- to hectometric-scale exposures facilitates the production of three-dimensional (3-D) surface reconstructions with centimeter resolution and range error. In order to be useful for geospatial data interrogation, models must be correctly located, scaled, and oriented, which typically requires the geolocation of manually positioned ground control points with survey-grade accuracy. The cost and operational complexity of portable tools capable of achieving such positional accuracy and precision is a major obstacle in the routine deployment of SfM-MVS photogrammetry in many fields, including geological fieldwork. Here, we propose a procedure to overcome this limitation and to produce satisfactorily oriented models, which involves the use of photo orientation information recorded by smartphones. Photos captured with smartphones are used to: (1) build test models for evaluating the accuracy of the method, and (2) build smartphone-derived models of outcrops, used to reference higher-resolution models reconstructed from image data collected using digital single-lens reflex (DSLR) and mirrorless cameras. Our results are encouraging and indicate that the proposed workflow can produce registrations with high relative accuracies using consumer-grade smartphones. We also find that comparison between measured and estimated photo orientation can be successfully used to detect errors and distortions within the 3-D models.

scholarly journals Analysis of the impacts on the quality of UAV photogrammetric products

2020 ◽  
Vol 64 (04) ◽  
pp. 489-507
Author(s):  
Mojca Kosmatin Fras ◽  
Urška Drešček ◽  
Anka Lisec ◽  
Dejan Grigillo
Keyword(s):  
Data Acquisition ◽  
Unmanned Aerial Vehicles ◽  
Spatial Data ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Aerial Vehicles

Unmanned aerial vehicles, equipped with various sensors and devices, are increasingly used to acquire geospatial data in geodesy, geoinformatics, and environmental studies. In this context, a new research and professional field has been developed – UAV photogrammetry – dealing with photogrammetry data acquisition and data processing, acquired by unmanned aerial vehicles. In this study, we analyse the selected factors that impact the quality of data provided using UAV photogrammetry, with the focus on positional accuracy; they are discussed in three groups: (a) factors related to the camera properties and the quality of images; (b) factors related to the mission planning and execution; and (c) factors related to the indirect georeferencing of images using ground control points. These selected factors are analysed based on the detailed review of relevant scientific publications. Additionally, the influence of the number of ground control points and their spatial distribution on point clouds' positional accuracy has been investigated for the case study. As the conclusion, key findings and recommendations for UAV photogrammetric projects are given; we have highlighted the importance of suitable lighting and weather conditions when performing UAV missions for spatial data acquisition, quality equipment, appropriate parameters of UAV data acquisition, and a sufficient number of ground control points, which should be determined with the appropriate positional accuracy and their correct distribution in the field.

scholarly journals A New Method for Positional Accuracy Analysis in Georeferenced Satellite Images without Independent Ground Control Points

2020 ◽  
Vol 12 (24) ◽  
pp. 4132
Author(s):  
Miguel Sánchez ◽  
Aurora Cuartero ◽  
Manuel Barrena ◽  
Antonio Plaza
Keyword(s):  
Spatial Data ◽  
Traditional Method ◽  
Satellite Images ◽  
New Method ◽  
Ground Control ◽  
Landsat 8 ◽  
Control Points ◽  
Positional Accuracy ◽  
National Geographic ◽  
Ground Control Points

This paper introduces a new method to analyze the positional accuracy of georeferenced satellite images without the use of ground control points. Compared to the traditional method used to carry out this kind of analysis, our approach provides a semiautomatic way to obtain a larger number of control points that satisfy the requirements of current standards regarding the size of the set of sample points, the positional accuracy of such points, the distance between points, and the distribution of points in the sample. Our methodology exploits high quality orthoimages, such as those provided by the Aerial Orthography National Plan (PNOA)—developed by the Spanish National Geographic Institute—and has been tested on spatial data from Landsat 8. Our method works under the current international standard (ASPRS 2014) and exhibits similar performance than other well-known methods to analyze the positional accuracy of georeferenced images based on the use of independent ground control points. More specifically, the positional accuracy achieved for a Landsat 8 dataset evaluated by the traditional method is 5.22 ± 1.95 m, and when evaluated with the proposed method, it exhibits a typical accuracy of 5.76 ± 0.50 m. Our experimental results confirm that the method is equally effective and less expensive than other available methods to analyze the positional accuracy of satellite images.

scholarly journals Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points

2019 ◽  
Vol 7 (4) ◽  
pp. 1009-1017 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Tectonically Active ◽  
Comparative Accuracy ◽  
Coastal Cliffs

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.

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