Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W2, 23-32, 2016
https://doi.org/10.5194/isprs-archives-XLII-2-W2-23-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
05 Oct 2016
A ROADMAP FOR GENERATING SEMANTICALLY ENRICHED BUILDING MODELS ACCORDING TO CITYGML MODEL VIA TWO DIFFERENT METHODOLOGIES
G. Floros, D. Solou, I. Pispidikis, and E. Dimopoulou School of Rural and Surveying Engineering, National Technical University of Athens, 9 Iroon Polytechneiou str, 15780 Zografou, Greece
Keywords: 3D Modeling, Trimble SketchUp, CityEngine, FME, CityGML, 3DCitiesProject, 3DCIM, Semantics Abstract. The methodologies of 3D modeling techniques have increasingly increased due to the rapid advances of new technologies. Nowadays, the focus of 3D modeling software is focused, not only to the finest visualization of the models, but also in their semantic features during the modeling procedure. As a result, the models thus generated are both realistic and semantically enriched. Additionally, various extensions of modeling software allow for the immediate conversion of the model’s format, via semi-automatic procedures with respect to the user’s scope. The aim of this paper is to investigate the generation of a semantically enriched Citygml building model via two different methodologies. The first methodology includes the modeling in Trimble SketchUp and the transformation in FME Desktop Manager, while the second methodology includes the model’s generation in CityEngine and its transformation in the CityGML format via the 3DCitiesProject extension for ArcGIS. Finally, the two aforesaid methodologies are being compared and specific characteristics are evaluated, in order to infer the methodology that is best applied depending on the different projects’ purposes.
Conference paper (PDF, 1085 KB)


Citation: Floros, G., Solou, D., Pispidikis, I., and Dimopoulou, E.: A ROADMAP FOR GENERATING SEMANTICALLY ENRICHED BUILDING MODELS ACCORDING TO CITYGML MODEL VIA TWO DIFFERENT METHODOLOGIES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W2, 23-32, https://doi.org/10.5194/isprs-archives-XLII-2-W2-23-2016, 2016.

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