Accuracy Assessment of Coastal Topography Derived From Uav Images

Long, Nathalie; Millescamps, Bastien; Pouget, Frédéric; Dumon, Antoine; Lachaussée, Nicolas; Bertin, Xavier

doi:10.5194/isprs-archives-xli-b1-1127-2016

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…The majority of errors did not exceed 4 pixels (8 cm) for the 3 surveys. Such a result is very similar to that found in [33,59,61,62], even though, in those surveys, UAV was used to identified elements on land instead of under water.…”

Section: Discussionsupporting

confidence: 77%

Application of Unmanned Aerial Vehicles and Image Processing Techniques in Monitoring Underwater Coastal Protection Measures

et al. 2022

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A prerequisite for solving issues associated with surf zone variability, which affect human activity in coastal zones, is an accurate estimation of the effects of coastal protection methods. Therefore, performing frequent monitoring activities, especially when applying new nature-friendly coastal defense methods, is a major challenge. In this manuscript, we propose a pipeline for performing low-cost monitoring using RGB images, accessed by an unmanned aerial vehicle (UAV) and a four-level analysis architecture of an underwater object detection methodology. First, several color-based pre-processing activities were applied. Second, contrast-limited adaptive histogram equalization and the Hough transform methodology were used to automatically detect the underwater, circle-shaped elements of a hybrid coastal defense construction. An alternative pipeline was used to detect holes in the circle-shaped elements with an adaptive thresholding method; this pipeline was subsequently applied to the normalized images. Finally, the concatenation of the results from both the methods and the validation processes were performed. The results indicate that our automated monitoring tool works for RGB images captured by a low-cost consumer UAV. The experimental results showed that our pipeline achieved an average error of four pixels in the test set.

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Section: Discussionsupporting

confidence: 77%

Application of Unmanned Aerial Vehicles and Image Processing Techniques in Monitoring Underwater Coastal Protection Measures

et al. 2022

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“…Unfavorable conditions can introduce errors, distortions, and limitations during data acquisition. To ensure precision, it is crucial to use sensors designed for robustness in diverse conditions, employ appropriate calibration and filtering techniques, and consider environmental factors during data collection [55]. Adequate lighting is essential for precise depth sensing, and issues such as low light or strong shadows can lead to inaccuracies in in-depth measurements and impact overall 3D point cloud quality.…”

Section: Advantages and Disadvantages Of Using Uas-based Photogrammet...mentioning

confidence: 99%

Unmanned Aerial Systems (UAS)-Derived 3D Models for Digital Twin Construction Applications

G. Martinez,

A. Alarcon,

Wandahl

2024

Applications of Point Cloud Technology

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The advent of Construction 4.0 has marked a paradigm shift in industrial development, integrating advanced technologies such as cyber-physical systems (CPS), sensors, unmanned aerial systems (UAS), building information modeling (BIM), and robotics. Notably, UASs have emerged as invaluable tools seamlessly embedded in construction processes, facilitating the comprehensive monitoring and digitization of construction projects from the early design phase through construction to the post-construction phases. Equipped with various sensors, such as imaging sensors, light detection and rangers (LiDAR), and thermal sensors, UASs play an important role in data collection processes, especially for 3D point cloud generation. Presently, UASs are recognized as one of the most effective means of generating a Digital Twin (DT) of construction projects, surpassing traditional methods in terms of speed and accuracy. This chapter provides a comprehensive overview of the applications of UAS-derived 3D models in DT, outlining their advantages and barriers and offering recommendations to augment their quality and accuracy.

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“…Images captured by UAVs and processed by structure-from-motion (SfM) photogrammetry are a combination of mature photogrammetry principles and modern computer vision technology [2] (hereafter UAV SfM). UAV SfM is widely used in Earth and Environmental Sciences to generate highresolution topography (HRT) data [3,4], including precision agriculture [5,6], landslide monitoring [7,8], coastal change [9,10], and glacier dynamics [11,12].…”

Section: Introductionmentioning

confidence: 99%

Accuracy Assessment of a UAV Direct Georeferencing Method and Impact of the Configuration of Ground Control Points

Liu

Lian

Yang³

et al. 2022

Drones

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Unmanned aerial vehicles (UAVs) can obtain high-resolution topography data flexibly and efficiently at low cost. However, the georeferencing process involves the use of ground control points (GCPs), which limits time and cost effectiveness. Direct georeferencing, using onboard positioning sensors, can significantly improve work efficiency. The purpose of this study was to evaluate the accuracy of the Global Navigation Satellite System (GNSS)-assisted UAV direct georeferencing method and the influence of the number and distribution of GCPs. A FEIMA D2000 UAV was used to collect data, and several photogrammetric projects were established. Among them, the number and distribution of GCPs used in the bundle adjustment (BA) process were varied. Two parameters were considered when evaluating the different projects: the ground-measured checkpoints (CPs) root mean square error (RMSE) and the Multiscale Model to Model Cloud Comparison (M3C2) distance. The results show that the vertical and horizontal RMSE of the direct georeferencing were 0.087 and 0.041 m, respectively. As the number of GCPs increased, the RMSE gradually decreased until a specific GCP density was reached. GCPs should be uniformly distributed in the study area and contain at least one GCP near the center of the domain. Additionally, as the distance to the nearest GCP increased, the local accuracy of the DSM decreased. In general, UAV direct georeferencing has an acceptable positional accuracy level.

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Accuracy Assessment of Coastal Topography Derived From Uav Images

Cited by 10 publications

References 14 publications

Application of Unmanned Aerial Vehicles and Image Processing Techniques in Monitoring Underwater Coastal Protection Measures

Application of Unmanned Aerial Vehicles and Image Processing Techniques in Monitoring Underwater Coastal Protection Measures

Unmanned Aerial Systems (UAS)-Derived 3D Models for Digital Twin Construction Applications

Accuracy Assessment of a UAV Direct Georeferencing Method and Impact of the Configuration of Ground Control Points

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