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Linked Open Data
3D Point cloud to BIM: semi-automated framework to define IFC alignment entities from MLS-acquired LiDAR data of highway roads
Identificadores del recurso
Remote Sensing, 12(14): 2301 (2020)
20724292
http://hdl.handle.net/11093/1718
10.3390/rs12142301
https://www.mdpi.com/2072-4292/12/14/2301
Procedència
(Investigo)

Fitxa

Títol:
3D Point cloud to BIM: semi-automated framework to define IFC alignment entities from MLS-acquired LiDAR data of highway roads
Tema:
3311.02 Ingeniería de Control
3305.06 Ingeniería Civil
3307.07 Dispositivos láser
Descripció:
Building information modeling (BIM) is a process that has shown great potential in the building industry, but it has not reached the same level of maturity for transportation infrastructure. There is a standardization need for information exchange and management processes in the infrastructure that integrates BIM and Geographic Information Systems (GIS). Currently, the Industry Foundation Classes standard has harmonized different infrastructures under the Industry Foundation Classes (IFC) 4.3 release. Furthermore, the usage of remote sensing technologies such as laser scanning for infrastructure monitoring is becoming more common. This paper presents a semi-automated framework that takes as input a raw point cloud from a mobile mapping system, and outputs an IFC-compliant file that models the alignment and the centreline of each road lane in a highway road. The point cloud processing methodology is validated for two of its key steps, namely road marking processing and alignment and road line extraction, and a UML diagram is designed for the definition of the alignment entity from the point cloud data.
Ministerio de Ciencia, Innovación y Universidades | Ref. RTI2018-095893-B-C21
Ministerio de Ciencia e Innovación y Universidades | Ref. FJC2018-035550-I
Idioma:
English
Relació:
info:eu-repo/grantAgreement/EC/H2020/769255
Autor/Productor:
Soilán Rodríguez, Mario
Justo Dominguez, Andrés
Sánchez Rodríguez, Ana
Riveiro Rodríguez, Belén
Editor:
Remote Sensing
Enxeñaría dos recursos naturais e medio ambiente
Enxeñaría dos materiais, mecánica aplicada e construción
Xeotecnoloxías Aplicadas
Drets:
Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/
openAccess
Data:
2021-02-01T07:54:48Z
2020-07-17
2021-01-27T11:25:19Z
Tipo de recurso:
article

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mods

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