ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume VI-4/W1-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W1-2020, 109–118, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-109-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W1-2020, 109–118, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-109-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  03 Sep 2020

03 Sep 2020

ARE YOUR INDOORGML FILES VALID?

H. Ledoux H. Ledoux
  • Delft University of Technology, the Netherlands

Keywords: IndoorGML, data quality, 3D modelling

Abstract. IndoorGML datasets allow us to represent both (1) the geometry of the interior of a building, which is subdivided into cells (eg rooms, corridors, staircases); and (2) the navigation graph between these cells, which also acts as a mechanism to store the topological relationships between the cells. To be used in applications such as indoor routing or emergency evacuation, IndoorGML files should be valid and structured according to the specifications of the OGC. In practice, achieving this is challenging because two different representations of the indoor space must be modelled and linked together; other 3D formats usually only store one representation. In this paper, I present a new methodology to validate IndoorGML files. It builds upon previous work on the validation of 3D geometries and city models, and it contains six specific tests. These tests have been implemented in the open source software val3dity, and I present and discuss experiments I ran with all the publicly available IndoorGML datasets I could find.