Automatic conversion of IFC datasets to geometrically and semantically correct CityGML LOD3 buildings

Abstract

Although the international standard CityGML has five levels of detail (LODs), the vast majority of available models are the coarse ones (up to LOD2, ie block-shaped buildings with roofs). LOD3 and LOD4 models, which contain architectural details such as balconies, windows and rooms, nearly exist because, unlike coarser LODs, their construction requires several datasets that must be acquired with different technologies, and often extensive manual work is needed. We investigate in this paper an alternative to obtaining CityGML LOD3 models: the automatic conversion from already existing architectural models (stored in the IFC format). Existing conversion algorithms mostly focus on the semantic mappings and convert all the geometries, which yields CityGML models having poor usability in practice (spatial analysis is for instance not possible). We present a conversion algorithm that accurately applies the correct semantics from IFC models and that constructs valid CityGML LOD3 buildings by performing a series of geometric operations in 3D. We have implemented our algorithm and we demonstrate its effectiveness with several real-world datasets. We also propose specific improvements to both standards to foster their integration in the future.

Processing BIM and GIS Models in Practice: Experiences and Recommendations from a GeoBIM Project in The Netherlands

“…This method will however yield buildings with several holes as several surfaces (e.g., those for a roof overhang, or small ones near a window sill) will not be visible from the finite set of points of view. Donkers et al [27] convert IFC models to LOD3 models by selecting a subset of the objects and then extracting the exterior envelope by using a series of Boolean set operations in 3D. Their algorithm does not yield holes/gaps if the input does not contain any and they can close small gaps by buffering all primitives; this however introduces artefacts in the entire model.…”

“…Thus, all geometries in every IFC file were extracted to an easily-parsable format while preserving the most relevant semantic information present in the original input file. This allowed us to overcome a shortcoming of the methodology of Donkers et al [27].…”

Automation of Building Permission by Integration of BIM and Geospatial Data

“…There are, however, challenges in the transformation. Donkers et al [12], among others, pointed out that different semantic properties are attached to the geometric primitives in IFC and CityGML. Furthermore, different geometric representations are employed, where IFC is using solids, such as constructive solid geometry (CSG) or sweep volumes, while CityGML uses boundary representation (B-Rep) (for description of these representations, see, e.g., [13]).…”

“…A method, focusing on the semantics, for unidirectional transformation between IFC and CityGML with the aid of a unified building model was suggested by El-Mekawy et al [17]. Donkers et al [12] develop an automatic transformation from IFC models to CityGML LOD3 models based on three steps: (1) filtering and mappings of the semantics; (2) 3D geometric transformations to extract the exterior envelope of a building; and (3) refinements that ensure that the output is a valid CityGML file also from a geometric perspective. GeoBIM is a research project in the Netherlands aiming at developing an interface to reuse BIM data in the GIS domain and vice versa and to create guidelines on the modelling process to facilitate the transformation between CityGML and IFC [18].…”

The effect of acquisition error and level of detail on the accuracy of spatial analyses

“…These LODs roughly reflect the different outcomes of different acquisition techniques (Biljecki, Ledoux, & Stoter, 2016b). For instance, LOD1 is usually produced by extruding footprints (Ledoux & Meijers, 2011), LOD2 can be acquired automatically from lidar data (Kada & McKinley, 2009), while LOD3 usually involves substantial manual work or is obtained after conversion from architectural sources (Donkers, Ledoux, Zhao, & Stoter, 2016). Examples of buildings modeled in these LODs will be exhibited in the next sections (Figures 4 and 5).…”