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Conference Paper: Development of 3D Building Models Using Multi-Source Data: A Study of High-Density Urban Area in Hong Kong
Title | Development of 3D Building Models Using Multi-Source Data: A Study of High-Density Urban Area in Hong Kong |
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Authors | |
Issue Date | 2017 |
Publisher | Heriot-Watt University. |
Citation | 2017 Lean and Computing in Construction Congress (LC3 2017): Volume I – Proceedings of the Joint Conference on Computing in Construction (JC3), Heraklion, Crete, Greece, 4-7 July 2017, p. 609-616 How to Cite? |
Abstract | There has been a world-wide interest in using 3D building models to support urban planning, design, and management. For high-density urban areas with complex topographic conditions, how to fast develop such models with adequate accuracy remains a challenge, particularly when a single data source is utilized. This study seeks to develop such quality models by integrating multi-source data including the topographic map and LiDAR data. A total of 1,361 high-rise buildings located in Hong Kong are chosen as the subjects. The topographic map is used to develop a level of detail 1 (LoD1) model of each building. The LiDAR data is then used to fine-tune building shapes, in particular roofs, so that more accurate models with LoD2 can be derived. It is found that the integration of topographic map and LiDAR data can improve the completeness and accuracy of building models. The speed and computations to operate the integration are acceptable. Future studies are recommended to achieve LoD3 building models by utilizing other data sources (e.g., semantic information of individual buildings, and points of interest). |
Persistent Identifier | http://hdl.handle.net/10722/243676 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Chen, K | - |
dc.contributor.author | Xue, F | - |
dc.contributor.author | Lu, W | - |
dc.date.accessioned | 2017-08-25T02:58:06Z | - |
dc.date.available | 2017-08-25T02:58:06Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | 2017 Lean and Computing in Construction Congress (LC3 2017): Volume I – Proceedings of the Joint Conference on Computing in Construction (JC3), Heraklion, Crete, Greece, 4-7 July 2017, p. 609-616 | - |
dc.identifier.isbn | 9780956595164 | - |
dc.identifier.uri | http://hdl.handle.net/10722/243676 | - |
dc.description.abstract | There has been a world-wide interest in using 3D building models to support urban planning, design, and management. For high-density urban areas with complex topographic conditions, how to fast develop such models with adequate accuracy remains a challenge, particularly when a single data source is utilized. This study seeks to develop such quality models by integrating multi-source data including the topographic map and LiDAR data. A total of 1,361 high-rise buildings located in Hong Kong are chosen as the subjects. The topographic map is used to develop a level of detail 1 (LoD1) model of each building. The LiDAR data is then used to fine-tune building shapes, in particular roofs, so that more accurate models with LoD2 can be derived. It is found that the integration of topographic map and LiDAR data can improve the completeness and accuracy of building models. The speed and computations to operate the integration are acceptable. Future studies are recommended to achieve LoD3 building models by utilizing other data sources (e.g., semantic information of individual buildings, and points of interest). | - |
dc.language | eng | - |
dc.publisher | Heriot-Watt University. | - |
dc.relation.ispartof | Lean and Computing in Construction Congress - Volume 1: Proceedings of the Joint Conference on Computing in Construction (JC3) | - |
dc.title | Development of 3D Building Models Using Multi-Source Data: A Study of High-Density Urban Area in Hong Kong | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Xue, F: xuef@hku.hk | - |
dc.identifier.email | Lu, W: wilsonlu@hku.hk | - |
dc.identifier.authority | Xue, F=rp02189 | - |
dc.identifier.authority | Lu, W=rp01362 | - |
dc.identifier.doi | 10.24928/JC3-2017/0252 | - |
dc.identifier.hkuros | 274401 | - |
dc.identifier.spage | 609 | - |
dc.identifier.epage | 616 | - |
dc.publisher.place | Edinburgh | - |