Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects
UAV-Enabled Corridor Photogrammetry is applied to survey linear transport infrastructure projects’ sites. The corridor flight missions cause a misalignment of the point cloud called the “bowl” effect. The purpose of this study is to offer a methodology based on statistical compensation methods to mi...
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| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/6/387 |
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| author | Sara Ait-Lamallam Rim Lamrani Wijdane Mastari Mehdi Kechna |
| author_facet | Sara Ait-Lamallam Rim Lamrani Wijdane Mastari Mehdi Kechna |
| author_sort | Sara Ait-Lamallam |
| collection | DOAJ |
| description | UAV-Enabled Corridor Photogrammetry is applied to survey linear transport infrastructure projects’ sites. The corridor flight missions cause a misalignment of the point cloud called the “bowl” effect. The purpose of this study is to offer a methodology based on statistical compensation methods to mitigate this effect and to improve the accuracy and density of the generated point cloud. The aerial images’ post-processing was carried out by varying the aerotriangulation methods. Subsequently, the accuracy improvement was completed by integrating the coordinates of the ground control points (GCPs) through different spatial distributions. Finally, Mean and RANSAC compensations were proposed to address the errors induced by the “bowl” effect on the coordinates of the images’ perspective centres (PCs). The findings indicate that the optimised aerotriangulation using Post-Processed Kinematic (PPK) data significantly contribute to reducing the “bowl” effect. Moreover, the GCP pyramidal spatial distribution allows accuracy improvement to a centimetre level. The Mean compensation method yields optimal outcomes in accuracy. It also helps to optimise on-site survey time and computing resources. RANSAC compensation optimises the accuracy and allows the retrieval of a 5-times-denser point cloud. Furthermore, the results give better accuracy compared to some current approaches. |
| format | Article |
| id | doaj-art-e9c8c1a5b8654d439454c6da5dea935d |
| institution | Matheson Library |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-e9c8c1a5b8654d439454c6da5dea935d2025-06-25T13:43:21ZengMDPI AGDrones2504-446X2025-05-019638710.3390/drones9060387Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor ProjectsSara Ait-Lamallam0Rim Lamrani1Wijdane Mastari2Mehdi Kechna3Department of Cartography and Photogrammetry, College of Geomatics and Surveying Engineering, Agronomic and Veterinary Institute Hassan II, Rabat 10101, MoroccoDepartment of Cartography and Photogrammetry, College of Geomatics and Surveying Engineering, Agronomic and Veterinary Institute Hassan II, Rabat 10101, MoroccoDepartment of Cartography and Photogrammetry, College of Geomatics and Surveying Engineering, Agronomic and Veterinary Institute Hassan II, Rabat 10101, MoroccoMILLENIUM TOPO CHARIF MED, Surveying Company, Rabat 12200, MoroccoUAV-Enabled Corridor Photogrammetry is applied to survey linear transport infrastructure projects’ sites. The corridor flight missions cause a misalignment of the point cloud called the “bowl” effect. The purpose of this study is to offer a methodology based on statistical compensation methods to mitigate this effect and to improve the accuracy and density of the generated point cloud. The aerial images’ post-processing was carried out by varying the aerotriangulation methods. Subsequently, the accuracy improvement was completed by integrating the coordinates of the ground control points (GCPs) through different spatial distributions. Finally, Mean and RANSAC compensations were proposed to address the errors induced by the “bowl” effect on the coordinates of the images’ perspective centres (PCs). The findings indicate that the optimised aerotriangulation using Post-Processed Kinematic (PPK) data significantly contribute to reducing the “bowl” effect. Moreover, the GCP pyramidal spatial distribution allows accuracy improvement to a centimetre level. The Mean compensation method yields optimal outcomes in accuracy. It also helps to optimise on-site survey time and computing resources. RANSAC compensation optimises the accuracy and allows the retrieval of a 5-times-denser point cloud. Furthermore, the results give better accuracy compared to some current approaches.https://www.mdpi.com/2504-446X/9/6/387UAV photogrammetry“bowl” effectcorridor flightpoint cloud |
| spellingShingle | Sara Ait-Lamallam Rim Lamrani Wijdane Mastari Mehdi Kechna Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects Drones UAV photogrammetry “bowl” effect corridor flight point cloud |
| title | Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects |
| title_full | Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects |
| title_fullStr | Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects |
| title_full_unstemmed | Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects |
| title_short | Effective Strategies for Mitigating the “Bowl” Effect and Optimising Accuracy: A Case Study of UAV Photogrammetry in Corridor Projects |
| title_sort | effective strategies for mitigating the bowl effect and optimising accuracy a case study of uav photogrammetry in corridor projects |
| topic | UAV photogrammetry “bowl” effect corridor flight point cloud |
| url | https://www.mdpi.com/2504-446X/9/6/387 |
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