| Title |
Graph-Based Classification and Urban Modeling of Laser Scanning and Imagery: Toward 3D Smart Web Services |
| ID_Doc |
41870 |
| Authors |
Namouchi, S; Farah, IR |
| Title |
Graph-Based Classification and Urban Modeling of Laser Scanning and Imagery: Toward 3D Smart Web Services |
| Year |
2022 |
| Published |
Remote Sensing, 14, 1 |
| DOI |
10.3390/rs14010114 |
| Abstract |
Recently, remotely sensed data obtained via laser technology has gained great importance due to its wide use in several fields, especially in 3D urban modeling. In fact, 3D city models in urban environments are efficiently employed in many fields, such as military operations, emergency management, building and height mapping, cadastral data upgrading, monitoring of changes as well as virtual reality. These applications are essentially composed of models of structures, urban elements, ground surface and vegetation. This paper presents a workflow for modeling the structure of buildings by using laser-scanned data (LiDAR) and multi-spectral images in order to develop a 3D web service for a smart city concept. Optical vertical photography is generally utilized to extract building class, while LiDAR data is used as a source of information to create the structure of the 3D building. The building reconstruction process presented in this study can be divided into four main stages: building LiDAR points extraction, piecewise horizontal roof clustering, boundaries extraction and 3D geometric modeling. Finally, an architecture for a 3D smart service based on the CityGML interchange format is proposed. |
| Author Keywords |
graph; LiDAR; point cloud; smart city; segmentation; 3D web service; 3D urban modeling |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000758867100001 |
| WoS Category |
Environmental Sciences; Geosciences, Multidisciplinary; Remote Sensing; Imaging Science & Photographic Technology |
| Research Area |
Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging Science & Photographic Technology |
| PDF |
https://www.mdpi.com/2072-4292/14/1/114/pdf?version=1640685503
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