In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.
Figure 4. Representing 3D climate data by series of horizontal 2D planes or by a 3D point cloud; (A) representing 3D data by series of 2D planes; (B) exploring the use of transparency when visualizing data through series of 2D planes; (C) representing 3D data by series of 2D point clouds; (D) representing 3D data by a 3D cloud of regularly spaced points; (E) representing 3D data by a 3D cloud of randomly spaced points; (F) animation of a moving slice of a 3D point cloud along a horizontal axis; (G) varying points size and density in the 3D cloud according to climate data value; (H) filtering points of the 3D cloud according to climate data value; (I) using animation to display data value intervals one after the other.
Keywords: 3D visualization, co-visualization, urban climate, climate visualization, 3D field data.
How to cite this article: Jacques Gautier, Sidonie Christophe, M Brédif. Visualizing 3D climate data in urban 3D models. International Archives of the Photogrammetry, Remote sensing and Spatial Information Sciences, Copernicus GmbH (Copernicus Publications), In press. hal-02877424