ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume II-2/W1
https://doi.org/10.5194/isprsannals-II-2-W1-247-2013
https://doi.org/10.5194/isprsannals-II-2-W1-247-2013
13 Sep 2013
 | 13 Sep 2013

A REPOSITORY OF INFORMATION VISUALIZATION TECHNIQUES TO SUPPORT THE DESIGN OF 3D VIRTUAL CITY MODELS

C. Métral, N. Ghoula, V. Silva, and G. Falquet

Keywords: 3D visualization, information visualization, 3D city model, 3D virtual environment, 3D GIS, knowledge base

Abstract. Virtual 3D city models are used for different applications such as urban planning, navigation, pedestrian behaviour, historical information, and disaster management. These applications require rich information models that associate urban objects not only with their geometric properties but also with other types of information. When designing such models the choice of visualization techniques is far from trivial because the city objects must be displayed together with additional information, such as historical facts, planning projects, pollutant concentration, noise level, etc. Finding relevant techniques depends on a set of criteria such as the type of information, but also on the tasks that will be performed and the associated context. Furthermore, a technique that is relevant when used in isolation may generate visual incompatibilities when used in conjunction with another one. We have defined a model for the representation of information visualization techniques in 3D city models. We have implemented this model in the form of an ontology and a knowledge base of techniques currently used in 3D city models or 3D GIS. The goal of such an approach is to provide a knowledge repository to support the design of 3D virtual city models in which non-geometric information must be presented. In this paper we describe the model and the ontology of information visualization techniques that we designed. We also show how the associated knowledge base can be used for the selection of visualization techniques depending on different criteria including task and context, and for the detection of visual incompatibilities between techniques when used in the same scene.