![]() For instance, there are at least 26 different ways of representing a simple square through GML ( ‐madness.html). One of the main reasons for CityGML’s poor interoperability is the complex and verbose nature of its main encoding, which is based on GML. Meanwhile, loading CityGML successfully in open‐source GIS software requires complicated and fragile processes using external tools ( ‐around‐with‐citygml‐on‐gdal‐2.2.html). Furthermore, the support is mainly through proprietary tools, such as FME ( ‐desktop/) and ArcGIS ( ‐arcgis), where the high cost of acquisition restricts access for researchers and practitioners. Although it has been available for more than a decade, there exists only a limited amount of support for handling CityGML files in GIS software. ![]() As a result, more organizations, such as national agencies, are investing in and producing 3D city models, mainly offering them as open data (Ho, Crompvoets, & Stoter, 2018).ĬityGML is the most popular standard for the representation of 3D city models (Open Geospatial Consortium, 2012). For instance, such models have been used for applications such as 3D cadastres, facilities management and emergency response. We intend to use the plugin for educational purposes in our university and we believe it can be proven a worthy tool for researchers and practitioners.įor many years three‐dimensional (3D) city models were mainly used for visualization purposes, but recently an increased demand for processing applications based on 3D urban data has been identified (Biljecki, Stoter, Ledoux, Zlatanova, & Çöltekin, 2015). We undertook this issue by providing various methods on how geometries from the model are loaded as QGIS features. One of the biggest challenges we faced, though, was mapping CityJSON’s hierarchical data structure to the relational model of QGIS. CityJSON parsing was proven to be straightforward and consistent when tested against several open datasets. Then, the geometry and attributes of every city object are transformed into QGIS features and divided into layers according to user preferences. The plugin parses a CityJSON file and analyses its tree structure to identify all city objects. In order to add support for 3D city models in QGIS, we have developed a plugin that enables CityJSON datasets to be loaded. Together, this opened the possibility to support semantic 3D city models in the popular open‐source GIS software for the first time. At the same time, CityJSON has been developing as an easy‐to‐use JavaScript Object Notation (JSON) encoding for 3D city models using the CityGML 2.0 data model. When QGIS 3.0 was released in 2018, it added support for 3D visualisation. ![]()
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