ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume IV-4/W9
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W9, 19–26, 2019
https://doi.org/10.5194/isprs-annals-IV-4-W9-19-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W9, 19–26, 2019
https://doi.org/10.5194/isprs-annals-IV-4-W9-19-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Sep 2019

30 Sep 2019

A REQUIREMENT ANALYSIS ON EXTENDING SEMANTIC 3D CITY MODELS FOR SUPPORTING TIME-DEPENDENT PROPERTIES

K. Chaturvedi and T. H. Kolbe K. Chaturvedi and T. H. Kolbe
  • Technische Universität München, Chair of Geoinformatics, 80333 Munich, Germany

Keywords: Semantic 3D City Models, Timeseries, Sensors, IoT, Patterns, CityGML, IFC, INSPIRE

Abstract. Semantic 3D City Models are used worldwide for different application domains ranging from Smart Cities, Simulations, Planning to History and Archeology. Well-defined data models like CityGML, IFC and INSPIRE Data Themes allow describing spatial, graphical and semantic information of physical objects. However, cities and their properties are not static and change with respect to time. Hence, it is important that such semantic data models handle different types of changes that take place in cities and their attributes over time. This paper provides a systematic analysis and recommendations for extensions of Semantic 3D City Models in order to support time-dependent properties. This paper reviews different application domains in order to identify key requirements for temporal and dynamic extensions and proposes ways to incorporate these extensions. Over the last couple of years, different extensions have been proposed for these standards to deal with temporal attributes. This paper also presents an analysis to which degree these extensions cover the requirements for dynamic city models.