GEOMETRIC AND SEMANTIC INTEGRATION OF BIM AND GIS FOR THE PROTECTION OF CULTURAL HERITAGE ASSETS AGAINST NATURAL DISASTERS

Natural disasters have a catastrophic impact on cultural heritage structures. To preserve
heritage buildings, digitalization plays a crucial role. Building Information Modeling (BIM),
Geometric Information System (GIS), and Semantic Web (SW) technologies offer promising
solutions in this context. BIM, specifically Heritage Building Information Modeling (HBIM),
enables the parametric representation of historic buildings. GIS technology allows for the
analysis of the surrounding environment and the visualization of 3D building models on a
map, incorporating environmental parameters. This project aims to present a semantically
enriched HBIM model within a GIS platform. By doing so, the model can be visualized in a
GIS environment where environmental data can be associated with building damages.
Semantic web technologies and linked data provide the means to link and query the building
data and damages. The project utilizes IFC for the BIM model and CityGML for GIS data, with
IFC representing building information and CityGML serving spatial analysis purposes. The
project focuses on a historic church as a case study to assess damages resulting from natural
phenomena. The digital BIM model, obtained from point cloud data, is transferred to a GIS
environment for investigating environmental characteristics and detected damages from
building surveys. GIS cartographic environmental data is sourced from regional geoportals.
The transformation of the BIM model to GIS format is achieved by converting the IFC file
into CityGML using the FME workflow. Information regarding building damages and
environmental elements is added to a semantically enriched RDF model of the church,
requiring manual work. The conversion of BIM data to GIS data presents challenges due to
differences in reference systems, spatial scale, level of detail, geometric representation
methods, storage, access methods, and semantic mismatches between BIM and GIS data
models. The final RDF graph is queried in GIS using Pystardog, a Python wrapper library that
facilitates communication with the Stardog Knowledge Graph and allowed the Stardog
knowledge graph to be hosted in QGIS python console. By transferring the HBIM model to a
GIS platform and enriching it with the observed damages, a comprehensive understanding
of the building and its context is achieved. This facilitates improved decision-making
regarding the preservation of cultural heritage buildings.