期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：VI-4-W1-2020
页码：93-99
DOI：10.5194/isprs-annals-VI-4-W1-2020-93-2020
语种：English
出版社：Copernicus Publications
摘要：Solar energy simulations are used to quantify the potential of the passive use (daylight, solar gains) and the active use (photovoltaics and solar thermal) of solar energy. The simulations can be performed at different scales e.g. buildings, neighbourhoods and cities, with different requirements on the data. For example, for the neighbourhood simulations we need simplified building geometries that can be retrieved from city models, and window information that can be extracted from BIM models (as in many cases window information is missing in city models). In this context, city models and BIM need to be integrated and reconciled. In this paper, we investigate two approaches to integrate and retrieve such information in a case study, where the BIM data is stored in IFC and the city model in CityGML (LOD2). The first approach is to perform a schema matching in an ETL tool, so as to convert and import window information from the IFC file into the CityGML model to create a LOD2-3 building model. We also investigate an alternative avenue, namely a semantic web approach, in which both the BIM and city models are transformed into knowledge graphs (linked data). City models and BIM utilize their respective but interlinked domain ontologies. Particularly, two ontologies are investigated for BIM data, i.e., the ifcOWL ontology and the building topology ontology (BOT). This paper compares different paths of such integrative data retrieval, as well as discloses the gaps mainly with the semantic web approach to further unlock its potential.
