HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA
Several advancements are going with Unmanned Aerial Systems (UAS) with the addition of multiple sensors and simultaneous data acquisition to obtain detailed geo-data for various applications. However, simultaneous data acquisition with multiple sensors, namely camera, and LiDAR, will also result in...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/633/2023/isprs-archives-XLVIII-1-W2-2023-633-2023.pdf |
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| author | Y. Yadav Y. Yadav B. Alsadik F. Nex F. Remondino P. Glira |
| author_facet | Y. Yadav Y. Yadav B. Alsadik F. Nex F. Remondino P. Glira |
| author_sort | Y. Yadav |
| collection | DOAJ |
| description | Several advancements are going with Unmanned Aerial Systems (UAS) with the addition of multiple sensors and simultaneous data acquisition to obtain detailed geo-data for various applications. However, simultaneous data acquisition with multiple sensors, namely camera, and LiDAR, will also result in possible discrepancies associated with them, and they need to be solved to use a reliable and accurate final product. Several errors can be associated with both camera and LiDAR datasets due to the different characteristics of the sensors and terrain conditions. This research paper aimed to minimize the errors between LiDAR and the image datasets simultaneously acquired with an Unmanned Aerial System (UAS) by implementing a hybrid adjustment approach with a criterion for the roughness and threshold angle between surface normals. The initial trajectory of the UAS, raw LiDAR measurements, and image observations were the inputs used for the hybrid adjustment. The hybrid adjustment workflow minimizes the discrepancies with a least-squares-based simultaneous adjustment for both LiDAR and image datasets. For the hybrid adjustment process, three types of correspondences were established, namely: between image pairs, overlapping LiDAR strips, and between Image tie points and LiDAR strips. For quality control, mean Cloud-to-Cloud distances (C2C) were compared between both LiDAR and camera point clouds before and after hybrid adjustment. The surface-level analysis of the results was also carried out to analyze the errors before and after hybrid adjustment at a surface level for different types of surfaces. The results showed that the alignment between the point clouds has significantly improved from the range of meters to a centimeter-level after implementing the hybrid adjustment process. The proposed hybrid adjustment workflow can be used in mapping applications where a centimeter-level accuracy is requested. |
| first_indexed | 2024-03-08T23:44:09Z |
| format | Article |
| id | doaj.art-dba3232c9b014c4489576270a07483ea |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-03-08T23:44:09Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-dba3232c9b014c4489576270a07483ea2023-12-14T01:54:17ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-12-01XLVIII-1-W2-202363364010.5194/isprs-archives-XLVIII-1-W2-2023-633-2023HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATAY. Yadav0Y. Yadav1B. Alsadik2F. Nex3F. Remondino4P. Glira5Department of Earth Observation, Faculty ITC, University of Twente, Enschede, the NetherlandsInter-University Department of Regional & Urban Studies and Planning (DIST), Politecnico di Torino, ItalyDepartment of Earth Observation, Faculty ITC, University of Twente, Enschede, the NetherlandsDepartment of Earth Observation, Faculty ITC, University of Twente, Enschede, the Netherlands3D Optical Unit, Bruno Kessler Foundation (FBK), Trento, ItalyCompetence Center Autonomous Systems, Austrian Institute of Technology, Vienna, AustriaSeveral advancements are going with Unmanned Aerial Systems (UAS) with the addition of multiple sensors and simultaneous data acquisition to obtain detailed geo-data for various applications. However, simultaneous data acquisition with multiple sensors, namely camera, and LiDAR, will also result in possible discrepancies associated with them, and they need to be solved to use a reliable and accurate final product. Several errors can be associated with both camera and LiDAR datasets due to the different characteristics of the sensors and terrain conditions. This research paper aimed to minimize the errors between LiDAR and the image datasets simultaneously acquired with an Unmanned Aerial System (UAS) by implementing a hybrid adjustment approach with a criterion for the roughness and threshold angle between surface normals. The initial trajectory of the UAS, raw LiDAR measurements, and image observations were the inputs used for the hybrid adjustment. The hybrid adjustment workflow minimizes the discrepancies with a least-squares-based simultaneous adjustment for both LiDAR and image datasets. For the hybrid adjustment process, three types of correspondences were established, namely: between image pairs, overlapping LiDAR strips, and between Image tie points and LiDAR strips. For quality control, mean Cloud-to-Cloud distances (C2C) were compared between both LiDAR and camera point clouds before and after hybrid adjustment. The surface-level analysis of the results was also carried out to analyze the errors before and after hybrid adjustment at a surface level for different types of surfaces. The results showed that the alignment between the point clouds has significantly improved from the range of meters to a centimeter-level after implementing the hybrid adjustment process. The proposed hybrid adjustment workflow can be used in mapping applications where a centimeter-level accuracy is requested.https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/633/2023/isprs-archives-XLVIII-1-W2-2023-633-2023.pdf |
| spellingShingle | Y. Yadav Y. Yadav B. Alsadik F. Nex F. Remondino P. Glira HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA |
| title_full | HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA |
| title_fullStr | HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA |
| title_full_unstemmed | HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA |
| title_short | HYBRID ADJUSTMENT OF UAS-BASED LiDAR AND IMAGE DATA |
| title_sort | hybrid adjustment of uas based lidar and image data |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/633/2023/isprs-archives-XLVIII-1-W2-2023-633-2023.pdf |
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