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

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.