OGC Indoor GML Pilot

Liz Sanderson
Liz Sanderson
  • Updated

FME Version

  • FME 2019.x


For the OGC Indoor Pilot project, Safe Software produced the Navigation Modeler to transform CityGML to OGC IndoorGML using FME. The workspace reads the CityGML 2.0 PS ADE data and transforms it to IndoorGML v1.1 with PS extension. Because FME uses a model based approach, the transformation rules are tied to the underlying CityGML and IndoorGML schemas and are not dependent on particular datasets. This means that once the transformation was defined for one dataset, it was possible to use the same CityGML to IndoorGML model to transform other datasets, all without any coding. Some minor configurations were required, but these are mostly limited to mitigating deficiencies in individual datasets, or introducing custom business rules to auto-generate public safety content that was missing in a particular dataset.


Transformation Steps

The primary transformation steps involved were:

  1. Mapping schema from CityGML to IndoorGML, generation of IDs, parent IDs, and parent property types to satisfy IndoorGML schema / UML requirements, and establish required nesting and parent child feature relationships.
  2. Business rules were added to generate default values required for each feature type.
    • Some are onstants and some are based on feature context including public safety information.
  3. Navigation network topology was generated and decomposed into node and linkages to support navigation.

The navigation network was auto-generated within the cell spaces of the Indoor GML using the state and transition feature types. The basic approach was to generate a TIN and then remove all the edges that crossed wall boundaries. Doors were used to cut holes in the walls to allow the network to traverse the building. In some datasets a few key doors were missing so a few transition features were added to better support network connectivity. Finally the output was validated against the IndoorGML PS extension schemas to make sure that the results were consistent with the requirements of the IndoorGML standard.

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