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3D point cloud data processing and infrastructure information models: methods and findings from safeway project

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dc.contributor.author Soilán Rodríguez, Mario
dc.contributor.author Justo Dominguez, Andrés
dc.contributor.author Sánchez Rodríguez, Ana
dc.contributor.author Lamas Novoa, Daniel
dc.contributor.author Riveiro Rodríguez, Belén
dc.date.accessioned 2021-07-05T08:55:13Z
dc.date.available 2021-07-05T08:55:13Z
dc.date.issued 2021-06-28
dc.identifier.citation ISPRS - International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, XLIII-B2-2021, 239-246 (2021) spa
dc.identifier.issn 21949034
dc.identifier.uri http://hdl.handle.net/11093/2309
dc.description.abstract Monitoring and digitalization are key to improve the resilience of the infrastructure network in the context of assessing its disaster management cycle. SAFEWAY is a project funded by the H2020 framework that aims to assess infrastructure resilience integrating multiscale information attending to all modes of disaster management cycle. This work presents the methodologies developed in the project for road and rail infrastructure monitoring and modelling, using remotely sensed data from Mobile Mapping Systems (MMS). First, 3D point clouds of both road and rail infrastructure are heuristically processed, obtaining geometric and semantic information from the most relevant assets, as well as the alignment, which is a key entity for generating information models. Such models are computed following the specifications of the Industry Foundation Classes (IFC) 4.1 schema, considering its current limitations and future potential for linear infrastructure modelling. Finally, the information is centralized in a core software platform where a user interface has been developed to aid visualization and interpretation of the resulting data. spa
dc.description.sponsorship Agencia Estatal de Investigación | Ref. RTI2018-095893-B-C21 spa
dc.description.sponsorship Agencia Estatal de Investigación | Ref. FJC2018-035550-I spa
dc.language.iso eng spa
dc.publisher The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences spa
dc.relation info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095893-B-C21/ES/EVALUACION DE CICLO DE VIDA DE ESTRUCTURAS DE PUENTES EXISTENTES UTILIZANDO DATOS MULTIESCALA Y MULTIFUENTES
dc.relation info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FJC2018-035550-I/ES
dc.rights Atribución 4.0 Internacional
dc.rights.uri https://creativecommons.org/licenses/by/4.0/deed.es
dc.title 3D point cloud data processing and infrastructure information models: methods and findings from safeway project en
dc.type article spa
dc.rights.accessRights openAccess spa
dc.relation.projectID info:eu-repo/grantAgreement/EU/H2020/769255 spa
dc.identifier.doi 10.5194/isprs-archives-XLIII-B2-2021-239-2021
dc.identifier.editor https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2021/239/2021/ spa
dc.publisher.departamento Enxeñaría dos materiais, mecánica aplicada e construción spa
dc.publisher.grupoinvestigacion Xeotecnoloxías Aplicadas spa
dc.subject.unesco 3311.02 Ingeniería de Control spa
dc.date.updated 2021-07-05T08:14:30Z
dc.references This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 769255. This document reflects only the views of the authors. Neither the Innovation and Networks Executive Agency (INEA) nor the European Commission is in any way responsible for any use that may be made of the information it contains. This work has been partially supported by the Spanish Ministry of Science, Innovation and Universities through the LASTING project Ref. RTI2018-095893-B-C21 and through grant FJC2018-035550-I. spa


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