| Title |
An Ground And Under-Ground Urban Roads Surveying Approach Using Integrated 3D Lidar And 3D Gpr Technology |
| ID_Doc |
40700 |
| Authors |
Zhou, YB; Hu, QW; Zhang, J; Zhao, PC; Yu, F; Ai, MY |
| Title |
An Ground And Under-Ground Urban Roads Surveying Approach Using Integrated 3D Lidar And 3D Gpr Technology |
| Year |
2022 |
| Published |
|
| DOI |
10.5194/isprs-annals-X-3-W2-2022-101-2022 |
| Abstract |
Digitalization of urban roads is an important part of smart city construction. In addition to having a basic understanding of the structure of the transportation network, we need to have a preliminary understanding of the information around the road, the current status of the road, and the impact that municipal projects may have on the road. At present, the three-dimensional information of the ground parts of roads can be obtained efficiently and accurately on a large scale by using three-dimensional scanning technology. However, there is a lack of comprehensive and intuitive understanding of the under-ground information and a lack of synergistic consideration of the ground and under-ground information. In this paper, a ground and under-ground urban road surveying system based on 3D LiDAR and 3D ground penetrating radar (GPR) is presented. The system covers multi-sensor coordinated control, time-space datum setup, and post-processing data. Experiments show that the system can realize the integrated ground and under-ground 3D surveying for urban roads, generate intuitive three-dimensional point cloud map model of ground and under-ground of urban roads, and provide effective technical support for smart city construction. |
| Author Keywords |
LiDAR; Ground Penetrating Radar; Point-cloud; GPR C-Scan; Road Surveying; Smart City |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001185905400015 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Remote Sensing |
| Research Area |
Computer Science; Remote Sensing |
| PDF |
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-3-W2-2022/101/2022/isprs-annals-X-3-W2-2022-101-2022.pdf
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