Show simple item record

dc.contributor.authorOtero Alonso, Roi 
dc.contributor.authorFrías Nores, Ernesto 
dc.contributor.authorLagüela López, Susana 
dc.contributor.authorArias Sánchez, Pedro 
dc.date.accessioned2020-09-28T10:42:03Z
dc.date.available2020-09-28T10:42:03Z
dc.date.issued2020-08-19
dc.identifier.citationRemote Sensing, 12(17): 2679 (2020)spa
dc.identifier.issn20724292
dc.identifier.urihttp://hdl.handle.net/11093/1552
dc.description.abstractThis 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.spa
dc.description.sponsorshipXunta de Galicia | Ref. IN852A 2018/59spa
dc.description.sponsorshipXunta de Galicia | Ref. I948131H646011spa
dc.language.isoengspa
dc.publisherRemote Sensingspa
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleAutomatic gbXML modeling from LiDAR data for energy studiesen
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/H2020/769255spa
dc.identifier.doi10.3390/rs12172679
dc.identifier.editorhttps://www.mdpi.com/2072-4292/12/17/2679spa
dc.publisher.departamentoEnxeñaría dos recursos naturais e medio ambientespa
dc.publisher.grupoinvestigacionXeotecnoloxías Aplicadasspa
dc.subject.unesco3305.22 Metrología de la Edificaciónspa
dc.subject.unesco1207.02 Sistemas de Controlspa
dc.date.updated2020-09-09T13:28:02Z
dc.computerCitationpub_title=Remote Sensing|volume=12|journal_number=17|start_pag=2679|end_pag=spa


Files in this item

[PDF]

    Show simple item record

    Attribution 4.0 International
    Except where otherwise noted, this item's license is described as Attribution 4.0 International