RT Journal Article
T1 3D point cloud data processing and infrastructure information models: methods and findings from safeway project
A1 Soilán Rodríguez, Mario
A1 Justo Dominguez, Andrés
A1 Sánchez Rodríguez, Ana
A1 Lamas Novoa, Daniel
A1 Riveiro Rodríguez, Belén
K1 3305.06 Ingeniería Civil
K1 3310.04 Ingeniería de Mantenimiento
K1 3323.02 Equipo Ferroviario
AB 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.
PB The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
SN 21949034
YR 2021
FD 2021-06-28
LK http://hdl.handle.net/11093/2309
UL http://hdl.handle.net/11093/2309
LA eng
NO ISPRS - International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, XLIII-B2-2021, 239-246 (2021)
NO Agencia Estatal de Investigación | Ref. RTI2018-095893-B-C21
DS Investigo
RD 24-mar-2025