Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods
Airborne light detection and ranging (LiDAR) data are increasingly used in various fields such as topographic mapping, urban planning, and emergency management. A necessary processing step in the application of airborne LiDAR data is the elimination of mismatch errors. This paper proposes a new meth...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/23/5447 |
| _version_ | 1797399648527187968 |
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| author | Zhenxing Sun Ruofei Zhong Qiong Wu Jiao Guo |
| author_facet | Zhenxing Sun Ruofei Zhong Qiong Wu Jiao Guo |
| author_sort | Zhenxing Sun |
| collection | DOAJ |
| description | Airborne light detection and ranging (LiDAR) data are increasingly used in various fields such as topographic mapping, urban planning, and emergency management. A necessary processing step in the application of airborne LiDAR data is the elimination of mismatch errors. This paper proposes a new method for airborne LiDAR strip adjustment based on point clouds with planar neighborhoods; this method is intended to eliminate errors in airborne LiDAR point clouds. Initially, standard pre-processing tasks such as denoising, ground separation, and resampling are performed on the airborne LiDAR point clouds. Subsequently, this paper introduces a unique approach to extract point clouds with planar neighborhoods which is designed to enhance the registration accuracy of the iterative closest point (ICP) algorithm within the context of airborne LiDAR point clouds. Following the registration of the point clouds using the ICP algorithm, tie points are extracted via a point-to-plane projection method. Finally, a strip adjustment calculation is executed using the extracted tie points, in accordance with the strip adjustment equation for airborne LiDAR point clouds that was derived in this study. Three sets of airborne LiDAR point cloud data were utilized in the experiment outlined in this paper. The results indicate that the proposed strip adjustment method can effectively eliminate mismatch errors in airborne LiDAR point clouds, achieving a registration accuracy and absolute accuracy of 0.05 m. Furthermore, this method’s processing efficiency was more than five times higher than that of traditional methods such as ICP and LS3D. |
| first_indexed | 2024-03-09T01:44:09Z |
| format | Article |
| id | doaj.art-8dde1e11f7b74a78b083f6117ba34c49 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T01:44:09Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-8dde1e11f7b74a78b083f6117ba34c492023-12-08T15:24:39ZengMDPI AGRemote Sensing2072-42922023-11-011523544710.3390/rs15235447Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar NeighborhoodsZhenxing Sun0Ruofei Zhong1Qiong Wu2Jiao Guo3Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, ChinaKey Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, ChinaChina Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, ChinaZhengtu 3D (Beijing) Laser Technology Co., Ltd., Beijing 100176, ChinaAirborne light detection and ranging (LiDAR) data are increasingly used in various fields such as topographic mapping, urban planning, and emergency management. A necessary processing step in the application of airborne LiDAR data is the elimination of mismatch errors. This paper proposes a new method for airborne LiDAR strip adjustment based on point clouds with planar neighborhoods; this method is intended to eliminate errors in airborne LiDAR point clouds. Initially, standard pre-processing tasks such as denoising, ground separation, and resampling are performed on the airborne LiDAR point clouds. Subsequently, this paper introduces a unique approach to extract point clouds with planar neighborhoods which is designed to enhance the registration accuracy of the iterative closest point (ICP) algorithm within the context of airborne LiDAR point clouds. Following the registration of the point clouds using the ICP algorithm, tie points are extracted via a point-to-plane projection method. Finally, a strip adjustment calculation is executed using the extracted tie points, in accordance with the strip adjustment equation for airborne LiDAR point clouds that was derived in this study. Three sets of airborne LiDAR point cloud data were utilized in the experiment outlined in this paper. The results indicate that the proposed strip adjustment method can effectively eliminate mismatch errors in airborne LiDAR point clouds, achieving a registration accuracy and absolute accuracy of 0.05 m. Furthermore, this method’s processing efficiency was more than five times higher than that of traditional methods such as ICP and LS3D.https://www.mdpi.com/2072-4292/15/23/5447airborne LiDARpoint clouds with planar neighborhoodspoint cloud registrationstrip adjustment |
| spellingShingle | Zhenxing Sun Ruofei Zhong Qiong Wu Jiao Guo Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods Remote Sensing airborne LiDAR point clouds with planar neighborhoods point cloud registration strip adjustment |
| title | Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods |
| title_full | Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods |
| title_fullStr | Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods |
| title_full_unstemmed | Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods |
| title_short | Airborne LiDAR Strip Adjustment Method Based on Point Clouds with Planar Neighborhoods |
| title_sort | airborne lidar strip adjustment method based on point clouds with planar neighborhoods |
| topic | airborne LiDAR point clouds with planar neighborhoods point cloud registration strip adjustment |
| url | https://www.mdpi.com/2072-4292/15/23/5447 |
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