Automatic gbXML Modeling from LiDAR Data for Energy Studies
This paper proposes an efficient and simplified procedure for the 3D modelling of buildings, based on the semi-automatic processing of point clouds acquired with mobile LiDAR scanners. The procedure is designed with the aim at generating BIM, in gbXML format, from the point clouds. In this way, the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/17/2679 |
| _version_ | 1797557004114329600 |
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| author | Roi Otero Ernesto Frías Susana Lagüela Pedro Arias |
| author_facet | Roi Otero Ernesto Frías Susana Lagüela Pedro Arias |
| author_sort | Roi Otero |
| collection | DOAJ |
| description | This paper proposes an efficient and simplified procedure for the 3D modelling of buildings, based on the semi-automatic processing of point clouds acquired with mobile LiDAR scanners. The procedure is designed with the aim at generating BIM, in gbXML format, from the point clouds. In this way, the main application of the procedure is the performance of energy analysis, towards the increase of the energy efficiency in the construction sector, and its consequent contribution to the mitigation of the climate change. Thus, the main contribution of the methodology proposed is its easiness of use and its level of automation, which allow its utilization by users who are experts in the use of energy in buildings but non-experts on 3D modelling. The software provides a solution for the 3D modelling of complex point clouds of various millions of points in times of execution less than 10 minutes. The system is evaluated through its application to three different real-world scenarios and compared with manual modelling. Moreover, the results are used for an example of an energy application, proving their performance against manually elaborated models. |
| first_indexed | 2024-03-10T17:11:05Z |
| format | Article |
| id | doaj.art-6db22939307b422aae458401401d9703 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T17:11:05Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6db22939307b422aae458401401d97032023-11-20T10:39:25ZengMDPI AGRemote Sensing2072-42922020-08-011217267910.3390/rs12172679Automatic gbXML Modeling from LiDAR Data for Energy StudiesRoi Otero0Ernesto Frías1Susana Lagüela2Pedro Arias3Centro de Investigación en Tecnoloxías, Enerxía e Procesos Industriais (CINTECX), Applied Geotechnologies Research Group, Campus Universitario de Vigo, Universidade de Vigo, As Lagoas, Marcosende, 36310 Vigo, SpainCentro de Investigación en Tecnoloxías, Enerxía e Procesos Industriais (CINTECX), Applied Geotechnologies Research Group, Campus Universitario de Vigo, Universidade de Vigo, As Lagoas, Marcosende, 36310 Vigo, SpainPolytechnic School of Ávila, University of Salamanca, Calle Hornos Caleros, 05003 Ávila, SpainCentro de Investigación en Tecnoloxías, Enerxía e Procesos Industriais (CINTECX), Applied Geotechnologies Research Group, Campus Universitario de Vigo, Universidade de Vigo, As Lagoas, Marcosende, 36310 Vigo, SpainThis paper proposes an efficient and simplified procedure for the 3D modelling of buildings, based on the semi-automatic processing of point clouds acquired with mobile LiDAR scanners. The procedure is designed with the aim at generating BIM, in gbXML format, from the point clouds. In this way, the main application of the procedure is the performance of energy analysis, towards the increase of the energy efficiency in the construction sector, and its consequent contribution to the mitigation of the climate change. Thus, the main contribution of the methodology proposed is its easiness of use and its level of automation, which allow its utilization by users who are experts in the use of energy in buildings but non-experts on 3D modelling. The software provides a solution for the 3D modelling of complex point clouds of various millions of points in times of execution less than 10 minutes. The system is evaluated through its application to three different real-world scenarios and compared with manual modelling. Moreover, the results are used for an example of an energy application, proving their performance against manually elaborated models.https://www.mdpi.com/2072-4292/12/17/2679BIMgbXMLpoint cloudthermalenergy analysis |
| spellingShingle | Roi Otero Ernesto Frías Susana Lagüela Pedro Arias Automatic gbXML Modeling from LiDAR Data for Energy Studies Remote Sensing BIM gbXML point cloud thermal energy analysis |
| title | Automatic gbXML Modeling from LiDAR Data for Energy Studies |
| title_full | Automatic gbXML Modeling from LiDAR Data for Energy Studies |
| title_fullStr | Automatic gbXML Modeling from LiDAR Data for Energy Studies |
| title_full_unstemmed | Automatic gbXML Modeling from LiDAR Data for Energy Studies |
| title_short | Automatic gbXML Modeling from LiDAR Data for Energy Studies |
| title_sort | automatic gbxml modeling from lidar data for energy studies |
| topic | BIM gbXML point cloud thermal energy analysis |
| url | https://www.mdpi.com/2072-4292/12/17/2679 |
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